Prediksi Iklim untuk Ketahanan Pangan

Authors

Ibnu Fathrio, Pusat Riset Iklim dan Atmosfer - BRIN; Danang Eko Nuryanto; Woro Estiningtyas, Badan Riset dan Inovasi Nasional; Bayu Dwi Apri Nugroho; Prawira Yudha Kombara; Suciantini, Badan Riset dan Inovasi Nasional; Robi Muharsyah, Universitas Gadjah Mada; Septrial Arafat; Januardi, Universitas Padjajaran; Noersomadi, Badan Riset dan Inovasi Nasional; Muhammad Agung Sunus, Kementerian Pertanian; Tania June, Institut Pertanian Bogor; Bhaskara Anggarda Gathot Subrata, Universitas Gadjah Mada
DOI: https://doi.org/10.55981/brin.1244

Keywords:

prediksi, model, adaptasi, Mitigasi

Synopsis

Ketahanan pangan merupakan isu penting yang menjadi perhatian negara-negara di dunia. Proyeksi pada tahun 2020, sekitar 690 juta orang berada dalam kondisi kelaparan.  Diperkirakan angka penduduk malnutrisi berjumlah lebih dari 760 juta pada tahun 2021, dan akan mencapai lebih dari 800 juta pada tahun 2030. Salah satu faktor yang berpengaruh terhadap ketersediaan dan produksi pangan adalah variabilitas dan perubahan iklim. Hal ini  dapat berpotensi mengakibatkan frekuensi kejadian cuaca eksrim meningkat yang dapat memperburuk kondisi ketahanan pangan global terutama di daerah-daerah yang rentan dengan kelaparan dan malnutrisi. Aksesibilitas pangan, ketersediaan pangan dan pemanfaatan pangan yang merupakan merupakan variabel ketahanan pangan yang rentan terhadap variabilitas Iklim (García-Díez dkk, 2021). Selain itu, kebijakan dan strategi pemerintah   juga berperan penting dalam stabilitas produksi pangan dalam menghadapai tantangan ini.

Kemajuan sains dan teknologi dalam bidang klimatologi seperti pemanfaatan satelit cuaca, radar cuaca dan semakin luasnya jaringan pengamatan iklim dapat menjadi modal untuk dapat meningkatkan pemahaman tentang karakteristik iklim. Melalui pemahaman yang baik tentang iklim, diharapkan dapat dijalankan berbagai strategi dalam mewujudkan ketahanan pangan dalam pertanian dan perikanan, seperti program pertanian-perikanan berkelanjutan, pengembangan pertanian-pertanian  pintar, dan diversifikasi produksi pangan. Kemajuan teknologi komputasi berkinerja tinggi juga memiliki peranan dalam memprediksi iklim dan cuaca ekstrim lebih akurat. Hal ini dapat menjadi masukan bagi para pemangku keputusan seperti pemerintah pusat dan daerah dalam menerapkan kebijakan ketahanan pangan.

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Author Biographies

Woro Estiningtyas, Badan Riset dan Inovasi Nasional

Woro Estiningtyas dilahirkan di Kota Nganjuk, Provinsi Jawa Timur, 8 Oktober 1967. Menyelesaikan pendidikan S-1 pada program studi Agrometeorologi di Institut Pertanian Bogor tahun 1992 dengan kajian skripsi tentang Penentuan Waktu Panen Tanaman Tebu Berdasarkan Akumulasi Bahang. Melanjutkan pendidikan S-2 pada program studi Sains Atmosfer di Institut Teknologi Bandung dan lulus tahun 2004 dengan penelitian berjudul Prediksi Curah Hujan dengan Metode Filter Kalman Mendukung Perencanaan Tanam. S-3 dengan judul Pengembangan Model Asuransi Indeks Iklim untuk Meningkatkan Ketahanan Petani Padi dalam Menghadapi Perubahan Iklim.

Bayu Dwi Apri Nugroho

Bayu Dwi Apri Nugroho, S.T.P., M.Agr., Ph.D. dilahirkan di Yogyakarta pada 12 April 1979. Setelah lulus SMA pada 1997, penulis melanjutkan studi S-1 di Fakultas Teknologi Pertanian, Universitas Gadjah Mada. Kemudian, setelah lulus tahun 2002, beliau menjadi asisten peneliti di Fakultas Teknologi Pertanian dan pada 2007 mendapat kesempatan studi S-2 di Iwate University, Jepang, dengan beasiswa dari Hashiya Foundation dalam bidang environmental sciences, dan dilanjutkan program S-3 dengan kekhususan agro-meteorology dan climate change.

Suciantini, Badan Riset dan Inovasi Nasional

Suciantini merupakan peneliti di Pusat Riset Iklim dan Atmosfer (PRIMA) BRIN sejak tahun 2022. Sebelumnya, penulis merupakan peneliti ahli madya bidang tanah, agroklimat dan hidrologi di Badan Penelitian dan Pengembang­an Pertanian, Kementerian Pertanian. Di Pusat Riset Iklim dan Atmosfer, saat ini penulis tergabung di Kelompok Riset Perubahan Iklim dan Pembangunan Berkelanjutan. Penulis menyelesaikan Pendidikan dari S-1–S-3 di Institut Pertanian Bogor. Pendidikan S-3 diselesaikan pada program studi Klimatologi Terapan. Lingkup riset penulis di antaranya terkait adaptasi perubahan iklim dan pengelolaan risiko iklimnya pada sektor pertanian. E-mail: ser022@brin.go.id.

Robi Muharsyah, Universitas Gadjah Mada

Robi Muharsyah adalah pakar di bidang klimatologi dengan latar belakang pendidikan S-1 Matematika Universitas Andalas dan S-2 Sains Kebumian ITB. Penulis memiliki pengalaman kerja di BMKG, di antaranya bertugas di Balai Besar Wilayah V Jayapura, Papua (2008–2011) dan di Subbidang Analisa dan Informasi Iklim, Kedeputian Bidang Klimatologi, BMKG Pusat (2011–2024).

aat ini, beliau menjadi staf pengajar di Departemen Teknik Pertanian, Fakultas Teknologi Pertanian, UGM, dengan mata kuliah yang diampu Agroklimatologi, Ilmu Lingkungan, Sistem Informasi Geografi, dan Peme­taan Wilayah, baik di program S-1, S-2, maupun S-3. Beberapa penelitian sudah diterbitkan di jurnal internasional serta menjadi reviewer di beberapa jurnal internasional seperti Journal of Geography, Journal of Agricultural Sciences, International Journal of Agriculture and Crop Science, Paddy and Water Environment, Ecological Engineering and Environmental Technology serta Indonesian Journal of Geography. Saat ini beliau juga tergabung di beberapa asosiasi profesi, baik dalam maupun luar negeri, seperti di Perhimpunan Teknik Pertanian (Perteta), Asian Crop Science Association, Japan Meteorology Society, dan Agricultural Meteorology Society. Selain itu, beliau juga aktif sebagai penulis dibeberapa media cetak dan online. Tahun 2016, beliau menjadi Staf Ahli Litbang Pertanian Kementerian Pertanian Republik Indonesia dan saat ini juga menjadi Tenaga Ahli di salah satu BUMN Pangan dan Ketua Dewan Pakar DPP Pemuda Tani Indonesia.
Seiring bertransformasinya Badan Litbang Pertanin menjadi Badan Standardisasi Instrumen Pertanian pada 2022, Penulis beralih jabatan fungsional dari peneliti ahli madya menjadi analis kebijakan ahli madya. Berbagai publikasi berupa karya ilmiah dan hasil penelitian telah diterbitkan dalam bahasa Indonesia dan Inggris pada jurnal ilmiah, semi ilmiah, serta prosiding.
Sejak tahun 1987, penulis bekerja sebagai Peneliti di Balai Penelitian Tanah, Balai Besar Penelitian dan Pengembangan Sumberdaya Lahan Pertanian, Badan Penelitian dan Pengembangan Pertanian, Kementerian Pertanian. Pada Bulan Desember 2022–sekarang penulis bekerja sebagai peneliti ahli utama bidang Pengelolaan Lahan pada Organisasi Riset Pertanian dan Pangan, BRIN.
Sejak tahun 1987, penulis melakukan penelitian dan kajian bidang ilmu tanah, khususnya konservasi tanah dan rehabilitasi lahan. Selanjutnya, penulis aktif melakukan riset dan kajian tentang teknologi pengelolaan lahan untuk meningkatkan adaptasi dan mitigasi terhadap perubahan iklim. Hasil-hasil penelitian dan kajian yang dilakukan penulis telah diterbitkan baik dalam bentuk prosiding, buku, bagian dari buku, bunga rampai, jurnal nasional, maupun global.
Sejak tahun 1992, penulis bekerja sebagai peneliti di Pusat Penelitian Tanah dan Agroklimat (Puslittanak) yang selanjutnya bergabung di Balai Penelitian Agroklimat dan Hidrologi (Balitklimat), Balai Besar Penelitian dan Pengembangan Sumberdaya Lahan Pertanian (BBSDLP), Badan Penelitian dan Pengembangan Pertanian, Kementerian Pertanian. Sejak Juni 2022–saat ini, penulis bekerja sebagai peneliti pada Kelompok Riset Perubahan Iklim dan Pembangunan Berkelanjutan, Pusat Riset Riset Iklim dan Atmosfer, Organisasi Riset Kebumian dan Maritim, BRIN.
Sejak tahun 1992, penulis melakukan penelitian dan kajian di bidang iklim, hidrologi dan agroklimat, khususnya klimatologi terapan. Penulis aktif melakukan riset dan kajian tentang pengelolaan risiko iklim, kerentanan, asuransi indeks iklim, dan adaptasi perubahan iklim. Hasil-hasil penelitian dan kajian yang dilakukan penulis telah diterbitkan dalam bentuk prosiding, buku, artikel pada buku, bunga rampai, jurnal nasional maupun international, serta dalam bentuk Hak Kekayaan Intelektual (HAKI).
Sejak tahun 2009, penulis bekerja sebagai peneliti di Pusat Penelitian Tanah dan Agroklimat yang selanjutnya bergabung di Balai Penelitian Agroklimat dan Hidrologi, Balai Besar Penelitian dan Pengembangan Sumberdaya Lahan Pertanian, Badan Penelitian dan Pengembangan Pertanian, Kementerian Pertanian. Pada Bulan Juni 2022–sekarang penulis bekerja sebagai peneliti pada Kelompok Riset Perubahan Iklim dan Pembangunan Berkelanjutan, Pusat Riset Riset Iklim dan Atmosfer, Organisasi Riset Kebumian dan Maritim, BRIN.
Sejak tahun 2009, penulis melakukan penelitian dan kajian di bidang iklim, hidrologi, dan agroklimat khususnya perubahan iklim dan model simulasi tanaman. Penulis aktif melakukan riset dan kajian tentang pengelolaan risiko iklim dan adaptasi perubahan iklim terhadap produksi tanaman. Hasil-hasil penelitian dan kajian yang dilakukan penulis telah diterbitkan dalam bentuk prosiding, buku, bagian dari buku, jurnal nasional, maupun international.

Januardi, Universitas Padjajaran

Januardi atau yang akrab dipanggil Ardi memperoleh gelar Doctor of Philosophy (Ph.D) dari Department of Industrial Management, National Taiwan University of Science and Technology (NTUST), Taiwan. Fokus riset dari Ardi mencakup supervised learning untuk prediksi dengan program R dan permodelan optimasi di sistem kompetisi industri pertanian (agroindustri) dengan game theory. Saat ini, beliau adalah dosen tetap di Program Studi Sarjana Teknologi Industri Pertanian, Universitas Padjadjaran. E-mail: januardi@unpad.ac.id.

Muhammad Agung Sunus, Kementerian Pertanian

Muhammad Agung Sunusi menyelesaikan S-1 di Universitas Haluoleo Kendari, S-2 di Universitas Hasanuddin Makassar, dan S-3 di Universitas Negeri Jakarta dengan bidang keahlian Manajemen Lingkungan. Penulis bertugas di Direktorat Jenderal Hortikultura Kementerian Pertanian sejak 2002. Penulis adalah Pengamat OPT Madya dan saat ini berperan sebagai Ketua Kelompok Penanganan Dampak Perubahan Iklim, Direktorat Perlindungan Hortikultura.

Tania June, Institut Pertanian Bogor

Tania June memperoleh gelar insinyur dari program studi Agrometeorologi IPB dan menjadi dosen di Departemen Geofisika dan Meteorologi sejak 1988 hingga saat ini. Penulis mendapat beasiswa dari International Development Program, Australia untuk pendidikan master (S-2) di School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia dan memperoleh gelar Master pada tahun 1991 di bidang pertanian (agriculture). Kemudian, penulis mendapatkan beasiswa dari AUSAID untuk melanjutkan pendidikan jenjang doktoral (S-3) di Research School of Biological Sciences, pada bidang environmental biology di Australian National University Australia dan mendapat Gelar Ph.D di bidang plant sciences pada tahun 2002.
Penulis telah membimbing penelitian dan meluluskan 87 orang mahasiswa S-1, 45 orang mahasiswa S-2, dan 10 orang mahasiswa S-3, saat ini penulis ditugaskan menjadi penanggunggung jawab dan pengajar pada mata kuliah “Mikrometeorologi” (S-1), “Pertanian Innovatif” (S-1); “Geofisika Lingkungan” (S-2), “Iklim Mikro” (S-2), “Pertanian Cerdas Iklim” (S-2/S-3), “Bioklimatologi” (S-2/S-3), “Bioklimatologi Lingkungan” (S-2/S-3), serta “Perubahan Lingkungan Global dan Mitigasi Bencana” (S-3).
Penelitian yang dilakukan penulis berfokus pada proses biogeofisik dan biogeokimia, mencakup pertukaran energi, bahang laten, dan evapotranspirasi serta bahang terasa dan pertukaran CO2 pada permukaan bervegetasi (khususnya hutan dan tanaman pertanian). Penulis telah memperoleh sertifikasi Dosen Profesional di Bidang Kebumian dan Angkasa pada tahun 2009 dan diangkat menjadi Guru Besar di bidang ilmu Geofisika dan Meteorologi sejak 1 Desember 2020. Penulis mengembangkan dan menjadi penanggung jawab MK Pertanian Cerdas Iklim (Climate Smart Agriculture) di PS Klimatologi Terapan GFM Institut Pertanian Bogor dan buku ini dikembangkan dari bahan yang diajarkan pada MK tersebut.

References

Alkorta, I., Epelde, L., & Garbisu, C. (2017). Environmental parameters altered by climate change affect the activity of soil microorganisms involved in bioremediation. FEMS Microbiology Letters, 364(19). https://doi.org/10.1093/femsle/fnx200

Baldrian, P., López-Mondéjar, R., & Kohout, P. (2023). Forest microbiome and global change. Nature Reviews Microbiology, 21(8), 487–501. https://doi.org/10.1038/s41579-023-00876-4

Blanc, E., & Reilly, J. (2017). Approaches to assessing climate change impacts on agriculture: An overview of the debate. Review of Environmental Economics and Policy, 11(2). https://www.journals.uchicago.edu/doi/epdf/10.1093/reep/rex011

Charalampopoulos, I., & Droulia, F. (2024). A pathway towards climate services for the agricultural sector. Climate, 12(2), 18. https://doi.org/10.3390/cli12020018

Eftekhari, M. S. (2022). Impacts of climate change on agriculture and horticulture. Dalam S. A. Bandh (Ed.), Climate change: The social and scientific construct (117–131). Springer.

Garbisu, C., Alkorta, I., Kidd, P., Epelde, L., & Mench, M. (2020). Keep and promote biodiversity at polluted sites under phytomanagement. Environmental Science and Pollution Research, 27(36), 44820–44834. https://doi.org/10.1007/S-11356-020-10854-5

Hung, H., Halsall, C., Ball, H., Bidleman, T., Dachs, J., De Silva, A., Hermanson, M., Kallenborn, R., Muir, D., Sühring, R., Wang, X., & Wilson, S. (2022). Climate change influence on the levels and trends of persistent organic pollutants (POPs) and chemicals of emerging Arctic concern (CEACs) in the Arctic physical environment – a review. Environmental Science Processes & Impacts, 24(10), 1577–1615. https://doi.org/10.1039/d1em00485a

Porter, J. R., & Semenov, M. A. (2005). Crop responses to climatic variation. Philosophical Transactions of the Royal Society B Biological Sciences, 360(1463), 2021–2035. https://doi.org/10.1098/rstb.2005.1752

Wing, I. S., De Cian, E., & Mistry, M. N. (2021). Global vulnerability of crop yields to climate change. Journal of Environmental Economics and Management, 109, 102462. https://doi.org/10.1016/j.jeem.2021.102462

Abrol, D. B. (2013). Integrated pest management: Current concepts and ecological process. Academic Press.

Aldrian, E. (2023, 16 Mei). Pergeseran musim akibat pemanasan global. Republika. https://www.republika.id/posts/40789/pergeseran-musim-akibat-pemanasan-global.

Aldrian, E., & Djamil, S. D. (2006). Long term rainfall trend of the brantas catchment area, East Java. Indonesian Journal of Geography, 38(1), 27.

Aldrian, E., Surmaini, E., Marwanto, S., Apriyana, Y., Maftu’ah, E., Pramudia, A., Fanggidae, Y. R., Supari, Syafrianno, A. A., Khoir, A. N., Chandrasa, G. T., Muharsyah, R., Suradi, Perdinan, Anggraeni, L., Adi, R. F., Tjahjono, R. E. P., Infrawan, D. Y. D., & Sulistyowati, D. (2022). Dampak perubahan iklim terhadap sektor pertanian: Fokus komoditas padi dan kopi (arabika dan robusta) [Laporan Akhir]. PI-AREA.

Apriyana, Y, Susanti, E., Suciantini, Ramadhani, F. & Surmaini, E. (2016). Analisis dampak perubahan iklim terhadap produksi tanaman pangan pada lahan kering dan rancang bangun sistem informasinya, Analysis of climate change impacts on food crops production in dry land and design of information system. Badan Penelitian dan Pengembangan Pertanian, Kementerian Pertanian.

Arif, A. (2023, 10 Mei). Prediksi El Niño dan karhutla di Indonesia. Kompas. https://www.kompas.id/baca/humaniora/2023/05/08/prediksi-El Niño-dan-karhutla-di-indonesia-pada-2023.

Badan Nasional Penanggulangan Bencana. (2023). Data bencana Indonesia. Geoportal Data Bencana Indonesia. Diakses pada 25 Mei, 2023, dari https://dibi.bnpb.go.id/.

Badan Pusat Statistik. (2023). Jumlah penduduk pertengahan tahun (ribu jiwa), 2020–2022. https://www.bps.go.id/indicator/12/1975/1/jumlah-penduduk-pertengahan-tahun.html

Barani, A. M., Dariah, A., Suryotomo, A. P., Mulyani, A., Apriyanto, A., Hidayat, A., Sumawinata B., Kartiwa, B., Taniwiryono, D., Sadono, D., Fahamsaya, E., Widiastuti, H., Hermantoro, Palunggono, H. B., Ismail, I., Safitri, L., Tambusai, M.N., Ernawan, R., Saptomo, S. K., Siswanto, Sabiham, S., Suratman, Anwar, S., & Adhi. Y. A. (2021). Gambut, sawit, dan lingkungan (S. Sabiham, A. Dariah, Hermantoro, & I. Ismail, Ed.). IPB PRESS.

Boer, R. (2011, 9–10 November). Ancaman perubahan iklim terhadap ketahanan pangan [Presentasi makalah]. Workshop Nasional dan FGD: Adapatasi Perubahan Iklim. Balai Besar Sumber Daya Lahan Pertanian, Kementerian Pertanian, Bandung, Indonesia.

DaMatta, F. M., Grandis, A., Arenque, B. C., & Buckeridge, M. S. (2010). Impacts of climate changes on crop physiology and food quality. Food Research International, 43(7), 1814–1823.

Dariah, A., Nurida, N. L., Yustika, R. D., & Suryani, E. (2022). Annual upland agriculture as a vulnerable system to climate change. Dalam Strengthening agricultural resilience against climate change through climate smart agriculture (49–62). Indonesian Agency for Agricultural Research and Development (IAARD). https://www.researchgate.net/publication/361809945_Annual_Upland_Agriculture_as_a_Vulnerable_System_to_Climate_Change

Dariah, A., Nurida, N. L., & Sutono. (2013). The effect of biochar on soil quality and maize production in upland in dry climate region. Dalam Proceeding 11th international conference the East and Southeast Asia federation of Soil Science Societies.

Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH. (2017a). Better rice initiative Asia. Diakses dari https://www.giz.de/en/worldwide/57047.html

Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH. (2017b). Paket teknologi CSA di Jawa Tengah Kabupaten Purbalingga & Banyumas. Gesellschaft für Internationale Zusammenarbeit.

Direktorat Jenderal Sumber Daya Air. (2015). Irigasi faktor utama peningkatan pangan nasional. Diakses dari https://sda.pu.go.id/berita/view/irigasi_faktor_utama_peningkatan_pangan_nasional.

Estiningtyas, W., Boer, R., Las, I., & Buono, A. (2012). Analisis usahatani padi untuk mendukung pengembangan asuransi indeks iklim (Weather index insurance): Studi kasus di Kabupaten Indramayu. Jurnal Pengkajian dan Pengembangan Teknologi Pertanian, 15(2), 158–170.

Estiningtyas, W., Kartikasari, K., Perdinan, & Dermoredjo, S. K. (2022, November). Index-based insurance for climate risk management in Indonesia Agriculture. Dalam International conference on radioscience, equatorial atmospheric science and environment (621–629). Springer.

Estiningtyas, W., Mulyani, A., & Kartiwa, B. (2021a, Februari). Assessing the vulnerability of food farming system to support climate change adaptation: A case study in Java, Indonesia. Dalam IOP conference series: Earth and environmental science (Vol. 648, No. 1, Artikel 012093). IOP Publishing..

Estiningtyas, W., Surmaini, E., Suciantini, N., Susanti, E., Mulyani, A., Kartiwa, B., Sumaryanto, N., Perdinan, N., Apriyana, Y., & Alifia, A. D. (2024). Analysing food farming vulnerability in Kalimantan, Indonesia: Determinant factors and adaptation measures. PloS One, 19(1), Artikel e0296262. https://doi.org/10.1371/journal.pone.0296262.

Estiningtyas, W., Syahbuddin, H., Harmanto, Sumaryanto, Mulyani, A., Setyorini, D., Kartiwa, B., Susanti, E., Surmaini, E., Sujono, R., Haryono, Rakhman, A., Suciantini, Apriyana, Y., Pramudia, A., Sarvina, Y., Nengsusmoyo, C., Kurniawan, H., Nugroho, A. A., …, A. S. Hutami. (2016). Analisis dan pemetaan tingkat kerentanan usaha tani pangan dan risiko iklim [Laporan akhir]. Kementerian Pertanian.

Estiningtyas, W., Syahbuddin, H., Pramudia, A., & Dermoredjo, S. K. (2021b, April). Analysis of key locations as indicators for extreme climate impacts in supporting climate change adaptation in Indonesia. Dalam IOP conference series: Earth and environmental science (Vol. 724, No. 1, Artikel 012042). IOP Publishing.

Food and Agriculture Organization. (1996, 13–17 November). Rome Declaration on World Food Security and World Food Summit Plan of Action. World Food Summit, Rome.

Gatot, I. S., Duchesne, J., Forest, F., Perez, P., Cudennec, C., Prasetyo, T., & Karama, S. (1999, Mei). Rainfall-runoff harvesting for controlling erosion and sustaining upland agriculture development. Dalam Sustaining the global farm: Selected papers from the 10th international soil conservation organization meeting held (Vol. 24, 29).

Hairani, A., Noor, M., Alwi, M., Saleh, M., Rina, Y., Khairullah, I., Sosiawan, H., Heryani, N., Mukhlis, M., & Lenin, I. (2024). Freshwater swampland as food buffer during El Niño: Case study in South Kalimantan, Indonesia. Chilean journal of agricultural research, 84(1), 132–143.

Haryati, U., Abdurachman, A., & Subagyono, K. (2010). Efisiensi penggunaan air berbagai teknik irigasi untuk pertanaman cabai di lahan kering pada Typic Kanhapludutls Lampung. Dalam Prosiding semnas sumber daya lahan pertanian (25–45). BBSDLP.

Hermanto, F., Agus, T., Alihamsyah, Surmaini, E., Dariah, A., Estiningtyas, W., Susilawati, H. L., Heryani, N., Susanti, E., Tiesnamurti, B., Ikhsan, M., Zuziana, Chaidirsyah, R. M., Waryanto, B., Adhie, S., Senoadji, T., & Salampessy, Y. N. (2022). Grand design pembangunan berketahanan iklim dan rendah karbon di sektor pertanian. Kementerian Pertanian.

Hoogenboom, G. (2000). Contribution of agrometeorology to the simulation of crop production and its applications. Agricultural and forest meteorology, 103(1-2), 137–157.

Hosang, P. R., Tatuh, J., & Rogi, J. E. (2012). Analisis dampak perubahan iklim terhadap produksi beras Provinsi Sulawesi Utara tahun 2013–2030. Jurnal Eugenia, 18(3).

Irawan, B. (2006). Fenomena anomali iklim El Niño dan La Niña: Kecenderungan jangka panjang dan pengaruhnya terhadap produksi pangan. Forum Penelitian Agro Ekonomi, 24(1), 28–45.

Irawan, B. (2013). Dampak El Niño dan La Niña terhadap produksi padi dan palawija. Badan Penelitian dan Pengembangan Pertanian, Kementerian Pertanian.

Kementerian Lingkungan Hidup dan Kehutanan. (2020). Peta jalan Nationally Determined Contribution (NDC) aspek adaptasi. Kementerian Lingkungan Hidup dan Kehutanan.

Kementerian Pertanian. (2016). Petunjuk teknis budidaya padi jajar Legowo Super (58).

Kementerian PPN/Bappenas. (2021). Kebijakan pembangunan berketahanan iklim (Climate resilient development policy 2020–2045) [Ringkasan eksekutif]. Bappenas.

Lal, M., Singh, K. K., Rathore, L. S., Srinivasan, G., & Saseendran, S. A. (1998). Vulnerability of rice and wheat yields in NW India to future changes in climate. Agricultural and forest meteorology, 89(2), 101–114.

Lutz, F. (2014). Exploring the potential of soil and water conservation as an adaptation strategy to climate change.

Maxwell, S., & Smith, M. (1992). Household food security: a conceptual review. Household food security: Concepts, indicators, measurements, 1, 1–72.

Motha, R. P., & Baier, W. (2005). Impacts of present and future climate change and climate variability on agriculture in the temperate regions: North America. Climatic Change, 70(1–2), 137–164.

Munarso, Y. P. (2010). Sifat kegenjahan dan toleran kekeringan beberapa galur padi sebagai calon tetua. Agrovigor: Jurnal Agroekoteknologi, 3(2), 125–130.

Naylor, R. L., Battisti, D. S., Vimont, D. J., Falcon, W. P., & Burke, M. B. (2007). Assessing risks of climate variability and climate change for Indonesian rice agriculture. Proceeding of the National Academic of Science, 104(19), 7752–7757.

NDC. (2016). First nationally determined contribution Republic of Indonesia. https://unfccc.int/sites/default/files/NDC/2022-06/First%20NDC%20Indonesia_submitted%20to%20UNFCCC%20Set_November%20%202016.pdf

Nurida, N. L., & Rachman, A. (2012, Juni). Alternatif pemulihan lahan kering masam terdegradasi dengan formula pembenah tanah biochar di Typic Kanhapludults Lampung. Dalam I. G. P. Wigena, N. L. Nurida, D. Setyorini, E. Husen, & E. Suryani (Ed.), Prosiding seminar nasional teknologi pemupukan dan pemulihan lahan terdegradasi (639–648). Badan Penelitian dan Pengembangan Pertanian, Kementerian Pertanian.

Pawitan, H., Kartiwa B., Amien I., Sosiawan H., Surmaini E., & A. Hamdani. (2010). Analisis dampak perubahan iklim terhadap dinamika potensi sumberdaya air untuk pertanian: Konsorsium penelitian dan pengembangan perubahan iklim untuk mengurangi akibat dan resiko iklim pada sektor pertanian (KP3I). Badan Litbang Pertanian.

Pawitan, H., Redjekiningrum, P., Kartiwa, B., Sosiawan, H., & Rahayu, B. (2011). Analisis dampak perubahan iklim terhadap dinamika potensi sumberdaya air untuk pertanian: Konsorsium penelitian dan pengembangan perubahan iklim untuk mengurangi akibat dan resiko iklim pada sektor pertanian (KP3I). Badan Litbang Pertanian.

Perdinan, Kartikasari, K., & Malahayati, M. (2014). Climate resilience in rice and other crops national studies: Indonesia. CCROM.

Perdinan, P., Atmaja, T., Adi, R. F., & Estiningtyas, W. (2018a). Adaptasi perubahan iklim dan ketahanan pangan: Telaah inisiatif dan kebijakan. Jurnal Hukum Lingkungan Indonesia, 5(1), 60–87.

Perdinan. (2018b). Future of Food. Journal on Food, Agriculture and Society. Research Paper.

Perdinan. (2019). Pandangan terhadap perubahan iklim di Indonesia [Presentasi makalah]. Kerja sama KLHK dan GIZ.

Purba, G. N. (2015, 23 September). Pemanfaatan rawa lebak solusi tingkatkan produktivitas padi saat El Niño. medcom.id. https://www.medcom.id/ekonomi/mikro/8N0gJqYK-pemanfaatan-rawa-lebak-solusi-tingkatkan-produktivitas-padi-saat-El Niño#:~:text=Dirinya%20menambahkan%2C%20total%20luas%20lahan,bertambah%20sekitar%20237%2C7%20ha.

Rejekiningrum, P. (2014). Dampak perubahan iklim terhadap sumberdaya air: Identifikasi, simulasi dan rencana aksi. Jurnal Sumberdaya Lahan, 8(1), 1–15.

Reuter, T. & A. Dariah. (2019). Pertanian, ketahahan pangan, dan perubahan iklim. Dalam Siti Nurbaya (Ed.), Trilogi Indonesia menghadapi perubahan iklim (32–42). Penerbit Buku Kompas.

Ridwan, M., & Hendri. (2001, 1 November). Rancangan peraturan pemerintah (RPP) tentang perubahan iklim [Makalah]. Seminar Climate Change Institut Pertanian Bogor, Bogor, Indonesia.

Sahardjo, B. H. (2000). Evaluasi kerusakan lingkungan akibat kebakaran hutan dan lahan. Institut Pertanian Bogor.

Schindele, W. W, Thoma, W., & Panzer, K. (1989). the Forest Fire 1983/1988 in East Kalimantan, Part I. The Fire, The Effect, The Damage and Technical Solutions. Investigation of the step needed to Rehabiliate the Area of East Kalimantan Seriously Affected by Fire. FR-Project ITTO, GTZ, BPPK, and DES.

Schulze, R. E. (2000). Modelling hydrological responses to land use and climate change: A southern African perspective. Ambio, 12–22.

Semenza, J. C., Ploubidis, G. B., & George, L. A. (2011). Climate change and climate variability: Personal motivation for adaptation and mitigation. Environmental Health, 10, 1–12.

Sjarmidi, A., & Aryantha, N. P. (1997). Komunitas mikroba pasca kebakaran hutan. LIPI.

Suharyanto, H. (2011). Ketahanan pangan. Jurnal Sosial Humaniora (JSH), 4(2), 186–194.

Surmaini, E., Sarvina, Y., Susanti, E., Widiarta, I. N., Misnawati, M., Suciantini, S., Fanggidae, Y. R., Rahmini, R., & Dewi, E. R. (2024). Climate change and the future distribution of Brown Planthopper in Indonesia: A projection study. Journal of the Saudi Society of Agricultural Sciences (Online), 23(2), 130–141. https://doi.org/10.1016/j.jssas.2023.10.002

Susandi, A. (2006). Bencana perubahan iklim global dan proyeksi perubahan iklim Indonesia. Kelompok Keahlian Sains Atmosfer Fakultas Ilmu Kebumian dan Teknologi Mineral ITB: Bandung.

Susanti, E., Dewi, E. R., Surmaini, E., Sopaheluwakan, A., Linarko, A., & Syahputra, M. R. (2021). The projection of rice production in Java Island to support Indonesia as the world food granary. E3S Web of Conferences, 306, 01011. https://doi.org/10.1051/e3sconf/202130601011

Susanti, E., Surmaini, E., & Estiningtyas, W. (2018). Parameter iklim sebagai indikator peringatan dini serangan hama penyakit tanaman. Jurnal Sumberdaya Lahan, 12(1), 59–70.

Susilawati, A., & Nursyamsi, D. (2014). Sistem surjan: kearifan lokal petani lahan pasang surut dalam mengantisipasi perubahan iklim. Jurnal sumberdaya lahan, 8(1), 3–42.

Tubiello, F. N., Soussana, J. F., & Howden, S. M. (2007). Crop and pasture response to climate change. Proceedings of the National Academy of Sciences, 104(50), 19686–19690.

United Nations Environment Programme. (2014). The adaptation gap report. https://wedocs.unep.org/bitstream/handle/20.500.11822/9331/-Adaptation_gap_report_a_prel.pdf?sequence=2&isAllowed=y.

Verchot, L. V., Van Noordwijk, M., Kandji, S., Tomich, T., Ong, C., Albrecht, A., Mackensen, J., Bantilan, C., Anupama, K. V., & Palm, C. (2007). Climate change: Linking adaptation and mitigation through agroforestry. Mitigation and adaptation strategies for global change, 12, 901–918.

Wiyono, S. (2007). Perubahan iklim dan ledakan hama penyakit tanaman, keanekaragaman hayati di tengah perubahan iklim: Tantangan masa depan Indonesia. KEHATI.

World Bank. (1986). Poverty and hunger: Issues and options for food security in developing countries.

Yang, X., Chen, F., Lin, X., Liu, Z., Zhang, H., Zhao, J., Li, K., Ye, Q., Li, Y., Lv, S., Yang, P., Wenbin, W., Li, Z., Lal, R., & Tang, H. (2015). Potential benefits of climate change for crop productivity in China. Agricultural and Forest Meteorology, 208, 76–84.

Yu, O. Y., Raichle, B., & Sink, S. (2013). Impact of biochar on the water holding capacity of loamy sand soil. International Journal of Energy and Environmental Engineering, 4, 1–9. http://www.journal.ijeee.com/content/4/1/44.

Abbas, S., & Mayo, Z. (2020). Impact of temperature and rainfall on rice production in Punjab, Pakistan. Environment, Development and Sustainability, 23, 1706–1728. https://doi.org/10.1007/S-10668-020-00647-8.

Adhikari, U., Nejadhashemi, A., & Woznicki, S. (2015). Climate change and eastern Africa: a review of impact on major crops. Food and Energy Security, 4, 110–132. https://doi.org/10.1002/FES-3.61.

Kondisi geografis. (2016). NTTPROV.GO.ID. Diakses dari http://nttprov.go.id/ntt2016/index.php/profildaerah1/kondisi-geografis

Apriyana, Y., Pramudia, A., Koswara, M. R. S., & Misnawati. (2021). Adjusting planting time using water balance and rainfall prediction approaches. Dalam IOP conference series: Earth and environmental science (Vol. 648, Artikel 012108). https://doi.org/10.1088/1755-1315/648/1/012108.

qil, M., Bunyamin, Z., & Andayani, N. N. (2013). Inovasi teknologi adaptasi tanaman jagung terhadap perubahan iklim. Dalam Seminar nasional inovasi teknologi pertanian (39–48). https://www.academia.edu/10237128/INOVASI_TEKNOLOGI_ADAPTASI_TANAMAN_JAGUNG_TERHADAP_PERUBAHAN_IKLIM

Ariffin. (2019). Metode klasifikasi iklim di Indonesia. UB Press.

Blain, G., Sobierajski, G., Weight, E., Martins, L., & Xavier, A. (2022). Improving the interpretation of standardized precipitation index estimates to capture drought characteristics in changing climate conditions. International Journal of Climatology, 42, 5586–5608. https://doi.org/10.1002/joc.7550.

Boonwichai, S., Shrestha, S., Babel, M., Weesakul, S., & Datta, A. (2018). Climate change impacts on irrigation water requirement, crop water productivity and rice yield in the Songkhram River Basin, Thailand. Journal of Cleaner Production. https://doi.org/10.1016/J.JCLEPRO.2018.07.146.

Bunyamin, Z. D., & Aqil, M. (2010). Analisis iklim mikro tanaman jagung (Zea mays L) pada sistem tanaman sisip. Pekan Serealia Nasional. Maros: Kementan. https://www.academia.edu/7038026/ANALISIS_IKLIM_MIKRO_TANAMAN_JAGUNG_Zea_Mays_L_PADA_SISTEM_TANAM_SISIP.

Dai, F., Zhang, C., Jiang, X., Kang, M., Yin, X., Lü, P., Zhang, X., Zheng, Y., & Gao, J. (2012). RhNAC2 and RhEXPA4 are involved in the regulation of dehydration tolerance during the expansion of rose petals. PLANT PHYSIOLOGY, 160(4), 2064–2082. https://doi.org/10.1104/pp.112.207720

Dash, S., Debnath, S., & Behera, M. (2020). Evaluation of evapotranspiration methods for rice yield simulation in a tropical river basin. International Journal of Current Microbiology and Applied Sciences, 9, 2560–2566. https://doi.org/10.20546/ijcmas.2020.905.292.

Doorenbos, J. & W.O. Pruitt. (1977). Crop water requirements (FAO Irrigation and Drainage Paper No. 24) Food and Agric. Organiz. of the U.N https://openknowledge.fao.org/server/api/core/bitstreams/a60d6c27-3fe1-4eab-8b0f-679312c70a57/content

Gunarsih, A. (1988). Klimatologi. Bina Aksara.

Hairmansis, A., Supartono, Kustianto, B., Suwarno, & Pane, H., (2012). Perakitan dan pengembangan varietas unggul baru padi toleran rendaman air Inpara 4 dan Inpara 5 untuk daerah rawan banjir. Jurnal Penelitian dan Pengembangan Pertanian, 31(1–7). https://dx.doi.org/10.21082/jp3.v31n1.2012.p%p

Hulme, M. & Sheard, N. (1999). Climate change scenarios for Indonesia. Climatic Research Unit.

Jolánkai, M., Birkás, M., Tarnawa, Á., & Kassai, K. (2019). Agriculture and climate change. International Climate Protection. https://doi.org/10.1007/978-3-030-03816-8_10.

Karuniasa, M., & Pambudi, P. (2023). The analysis of the El Niño phenomenon in the East Nusa Tenggara Province, Indonesia. Journal of Water and Land Development. https://doi.org/10.24425/jwld.2022.140388.

Kedang, A. & Haruna. (2008). Pengkajian waktu tanam dan pola tanam pada agroekosistem lahan kering dan sawah tadah hujan di NTT [Laporan akhir tahun 2008]. Balai Pengkajian Teknologi Pertanian.

Liao, C. T., & Lin, C. H. (2001). Physiological adaptation of crop plants to flooding stress. Proceedings of the National Science Council, Republic of China. Part B, Life Sciences, 25(3), 148–157.

Mahmod, I.F., Barakbah, S. S., Osman, N., & Omar, O. (2014). Physiological response of local rice varieties to aerobic condition. International Journal of Agriculture and Biology, 16, 738–744.

Mapelli, S., Locatelli, F., & Bertani, A. (1995). Effect of anaerobic environment on germination and growth of rice and wheat: Endogenous levels of ABA and IAA. Bulg J Plant Physiol, 21(2–3), 33–41.

Mawardi, M. (2012). Rekayasa konservasi tanah dan air. Bursa Ilmu.

Nugroho, B., Arif, C., & Maftukhah, R. (2018). Cropping calendar scenario based on climate projections against regional climate change in the southern part of Indonesia. Dalam A. Sukartiko, T. Nuringtyas, S. Marliana, A. Isnansetyo, (Ed.), Proceeding of the 2nd international conference on tropical agriculture (15–23). Springer. https://doi.org/10.1007/978-3-319-97553-5_2.

Rachmawati, Y. (2016, 27 Mei). Lahan pertanian 59,7 ribu hektare di NTT alami gagal panen. Tribun News. http://www.tribunnews.com/regional/2016/05/27/lahan-pertanian-597-ribu-hektar-di-ntt-alami-gagal-panen

Rejekiningrum, P. & Kartiwa, B. (2015). Upaya meningkatkan produksi tanaman jagung menggunakan teknik irigasi otomatis di lahan kering Kabupaten Lombok Barat, Nusa Tenggara Barat. Dalam Prosiding seminar nasional masyarakat biodiversitas Indonesia (Vol. 1, No. 8, 2027-2033). Smujo International. https://smujo.id/psnmbi/article/download/1386/1341/1333

Ruminta, R. (2016). Analisis penurunan produksi tanaman padi akibat perubahan iklim di Kabupaten Bandung Jawa Barat. Kultivasi, 15(1). https://doi.org/10.24198/kultivasi.v15i1.12006

Ruminta., & Handoko. (2012). Kajian risiko dan adaptasi perubahan iklim pada sektor peranian di Sumatera Selatan [Laporan penelitian]. KLHJakarta.

Runtunuwu, E., Syahbuddin, H., & Ramadhani, F. (2013). Kalender tanam sebagai instrumen adaptasi perubahan iklim. Dalam H. Soeparno, E. Pasandaran, M. Syarwani, A. Dariah, S. M. Pasaribu, N. S. Saad (Ed.), Politik pembangunan pertanian menghadapi perubahan iklim (271–297). IAARD Press..

Siddiqi, M. (1992). Analysis of daily rainfall data to know the best planting dates of summer and winter season crops in Islamabad. Journal of Engineering and Applied Sciences, 11 (1).

Sopiana., & Angga. (2017). 5 Klasifikasi iklim menurut Koppen. Diakses pada tanggal 14 Mei, 2023, dari http://www.sridianti.com/klasifikasiiklim-menurut-koppen.html

Suwignyo, R. A. (2007). Ketahanan tanaman padi terhadap kondisi terendam: Pemahaman terhadap karakter fisiologis untuk mendapatkan kultivar padi yang toleran di lahan rawa lebak. Dalam Kongres ilmu pengetahuan wilayah Indonesia bagian barat.

Taslim, H., & Fagi, A. M. (1988). Ragam budi daya padi dalam padi Buku 1. Pusat Penelitian dan Pengembangan Tanaman Pangan, Badan Penelitian dan Pengembangan Pertanian, 319.

Wairata, E. J. (2012). Sistem penentuan prioritas tanaman di Kota Kupan berbasis analytical hierarchy process (AHP) [Disertasi]. Magister Sistem Informasi Program Pascasarjana FTI-UKSW.

Winarto, Y. T., Stigter, K., Dwisatrio, B., Nurhaga, M., & Bowolaksono, A. (2013). Agrometeorological learning increasing farmers’ knowledge in coping with climate change and unusual risks. Southeast Asian Studies, 2(2), 323-349. https://englishkyoto-seas.org/wp-content/uploads/SEAS_0202_Winarto-et-al..pdf

Wiyono, S. (2007, 28 Juni 2007). Tantangan masa depan Indonesia: Perubahan iklim dan ledakan hama penyakit tanaman [Presentasi makalah]. Seminar Sehari tentang Keanekaragaman Hayati di Tengah Perubahan Iklim, Indonesia.

Yohe, G., & Tol, R. S. (2002). Indicators for social and economic coping capacity—moving toward a working definition of adaptive capacity. Global Environmental Change, 12(1), 25–40. https://doi.org/10.1016/s0959-3780(01)00026-7

Ziolkowska, J. (2016). Socio-economic implications of drought in the agricultural sector and the state economy. Economies, 4, 19. https://doi.org/10.3390/ECONOMIES4030019.

Alsafadi, K., Bi, S., Abdo, H. G., Almohamad, H., Alatrach, B., Srivastava, A. K., Al-Mutiry, M., Bal, S. K., Chandran, M. A. S., & Mohammed, S. (2023). Modeling the impacts of projected climate change on wheat crop suitability in semi-arid regions using the AHP-based weighted climatic suitability index and CMIP6. Geoscience Letters, 10(1). https://doi.org/10.1186/s40562-023-00273-y

Arakawa, A. (1997). Interviewed by Paul N. Edwards (July 17-18, 1997). University of California.

MKG. (t.t.). Proyeksi Perubahan Iklim. BMKG. https://www.bmkg.go.id/iklim/indeks-enso.bmkg

Bourke, W. (1974). A multi-level spectral model. I. Formulation and hemispheric integrations. Mon. Wea. Rev, 102(10), 687-701.

Buontempo, C., Burgess, S. N., Dee, D., Pinty, B., Thépaut, J. N., Rixen, M., Almond, S., Armstrong, D., Brookshaw, A., Lopez, A. A., Bell, B., Bergeron, C., Cagnazzo, C., Comyn-Plat, E., Damasio-Da-Costa, E., Guillory, A., Hersbach, H., Horányi, A., Nicolas, J., … De Marcilla, J. G. (2022). The Copernicus climate change service climate science in action. Bulletin of the American Meteorological Society, 103(12), E2669–E2687. https://doi.org/10.1175/BAMS-D-21-0315.1

Eliasen, E., Machenhauer, B., & Rasmussen, E. (1970). On a numerical method for integration of the hydrodynamical equations with a spectral representation of the horizontal fields (p. 35pp). Kobenhavns Universitet, Institut for Teoretisk Meteorologi.

Goosse, H., Barriat, P. Y., Lefebvre, W., Loutre, M. F., & Zunz, V. (2008). Introduction to climate dynamics and climate modelling. https://climate.envsci.rutgers.edu/climdyn2019/Goosse.pdf

Hewitt, C. D., & Lowe, J. A. (2018). Toward a European climate prediction system. Bulletin of the American Meteorological Society, 99(10), 1997–2001. https://doi.org/10.1175/BAMS-D-18-0022.1

Hurrell, J., Meehl, G. A., Bader, D., Delworth, T. L., Kirtman, B., & Wielicki, B. (2009). A unified modeling approach to climate system prediction. Bulletin of the American Meteorological Society, 90(12), 1819–1832. https://doi.org/10.1175/2009BAMS-2752.1

Institute of Meteorology, University of Stockholm (1954). Results of forecasting with the barotropic model on an electronic computer (BESK). Tellus, 6(2), 139–149.

Johnson, D. R., & Arakawa, A. (1996). On the scientific contributions and insight of Professor Yale Mintz. Journal of climate, 9(12), 3211–3224.

Khadka, D., Babel, M. S., Abatan, A. A., & Collins, M. (2021). An evaluation of CMIP5 and CMIP6 climate models in simulating summer rainfall in the Southeast Asian monsoon domain. International Journal of Climatology, 42(2), 1181–1202. https://doi.org/10.1002/joc.7296

Kitoh, A. (2017). The Asian monsoon and its future change in climate models: A review. Journal of the Meteorological Society of Japan Ser II, 95(1), 7–33. https://doi.org/10.2151/jmsj.2017-002

Kurniadi, A., Weller, E., Kim, Y. H., & Min, S. K. (2022). Evaluation of Coupled Model Intercomparison Project Phase 6 model-simulated extreme precipitation over Indonesia. International Journal of Climatology, 43(1), 174–196. https://doi.org/10.1002/joc.7744

Langlois, W. E., & Kwok, H. C. W. (1969). Description of the Mintz-Arakawa numerical general circulation model. Department of Meteorology, University of California.

Manabe, S. J., Smagorinsky, and R. F. Strickler (1965). Simulated climatology of general circulation with a hydrologic cycle. Monthly Weather Rev. 93, 769–798.

Manabe, S. (1967). General circulation of the atmosphere. Trans Am Geophys Union, 48, 427-431.

Manabe, S. (1970, Juni). The dependence of atmospheric temperature on the concentration of carbon dioxide. Dalam Global effects of environmental pollution: A symposium Organized by the American Association for the Advancement of Science Held in Dallas, Texas, December 1968 (25–29). Springer.

Manabe, S., Bryan, K., & Spelman, M. J. (1975). A global ocean-atmosphere climate model. Part I. The atmospheric circulation. Journal of Physical Oceanography, 5(1), 3–29.

McGuffie, K., & Henderson-Sellers, A. (2005). A climate modelling primer. John Wiley & Sons, Ltd. https://doi.org/10.1002/0470857617.

Mintz, Y. (1958). Design of some numerical general circulation experiments. Bull. Res. Council of Israel, 76, 67–114.

McKenna, S., Santoso, A., Gupta, A. S., Taschetto, A. S., & Cai, W. (2020). Indian Ocean Dipole in CMIP5 and CMIP6: characteristics, biases, and links to ENSO. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-68268-9

Müller, C., Franke, J., Jägermeyr, J., Ruane, A. C., Elliott, J., Moyer, E., Heinke, J., Falloon, P. D., Folberth, C., Francois, L., Hank, T., Izaurralde, R. C., Jacquemin, I., Liu, W., Olin, S., Pugh, T. A. M., Williams, K., & Zabel, F. (2021). Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios. Environmental Research Letters, 16(3). https://doi.org/10.1088/1748-9326/abd8fc

Moon, S., & Ha, K. (2020). Future changes in monsoon duration and precipitation using CMIP6. Npj Climate and Atmospheric Science, 3(1). https://doi.org/10.1038/s41612-020-00151-w

Orszag, S. A. (1970). Transform method for the calculation of vector-coupled sums: Application to the spectral form of the vorticity equation. Journal of Atmospheric Sciences, 27(6), 890-895.

Osei, E., Jafri, S. H., Saleh, A., Gassman, P. W., & Gallego, O. (2023). Simulated climate change impacts on corn and soybean yields in Buchanan County, Iowa. Agriculture (Switzerland), 13(2). https://doi.org/10.3390/agriculture13020268

Platzman, G. W. (1979). The ENIAC Computations of 1950-gateway to numerical weather prediction. Bull. Am. Meteorolog. Soc., 60, 302–312.

Qalbi, H. B., Faqih, A., & Hidayat, R. (2017). Future rainfall variability in Indonesia under different ENSO and IOD composites based on decadal predictions of CMIP5 datasets. Dalam IOP conference series: Earth and environmental science (Vol. 54, Artikel 012043).. https://doi.org/10.1088/1755-1315/54/1/012043

Richardson, L. F. (1922). Weather prediction by numerical process. Cambridge University Press.

Silberman, I. (1953). Planetary waves in the atmosphere. New York University.

Smagorinsky, J. (1958). On the numerical integration of the primitive equations of motion for baroclinic flow in a closed region. Monthly Weather Review, 86(12), 457–466.

Smagorinsky, J. (1963). General circulation experiments with the primitive equations: I. The basic experiment. Monthly Weather Review, 91(3), 99–164.

Smagorjnsky, J. (1983). The beginnings of numerical weather prediction and general circulation modeling: early recollections. In Advances in geophysics (Vol. 25, 3–37). Elsevier.

Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y. T., Chuang, H. Y., Iredell, M., Ek, M., Meng, J., Yang, R., Mendez, M. P., Van Den Dool, H., Zhang, Q., Wang, W., Chen, M., & Becker, E. (2014). The NCEP climate forecast system version 2. Journal of Climate, 27(6), 2185–2208. https://doi.org/10.1175/JCLI-D-12-00823.1

Santoso, A., England, M. H., Kajtar, J. B., & Cai, W. (2022). Indonesian throughflow variability and linkage to ENSO and IOD in an ensemble of CMIP5 models. Journal of Climate, 35(10), 3161–3178. https://doi.org/10.1175/jcli-d-21-0485.1

Tabari, H., Paz, S. M., Buekenhout, D., & Willems, P. (2021). Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought. Hydrology and Earth System Sciences, 25(6), 3493–3517. https://doi.org/10.5194/hess-25-3493-2021

Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012). An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93(4), 485–498. https://doi.org/10.1175/BAMS-D-11-00094.1

Yang, S., Zhang, T., Li, Z., & Dong, S. (2019). Climate variability over the maritime continent and its role in global climate variation: A review. Journal of Meteorological Research, 33(6), 993–1015. https://doi.org/10.1007/S-13351-019-9025-x

Asian Development Bank. (2021). Climate risk country profile: Indonesia. https://www.adb.org/sites/default/files/publication/700411/climate-risk-country-profile-indonesia.pdf

Aldrian, E., & Susanto, R. D. (2003). Identification of three dominant rainfall regions within Indonesia and their relationship to sea surface temperature. International Journal of Climatology: A Journal of the Royal Meteorological Society, 23(12), 1435–1452. https://doi.org/10.1002/joc.950.

Aldrian, E., Surmaini, E., Marwanto, S., Apriyana, Y., Maftu’ah, E., Pramudia, A., Fanggidae, Y. R., Supari, Syafrianno, A. A., Khoir, A. N., Chandrasa, G. T., Muharsyah, R., Suradi, Perdinan, Anggraeni, L., Adi, R. F., Tjahjono, R. E. P., Infrawan, D. Y. D., & Sulistyowati, D. (2022). Dampak perubahan iklim terhadap sektor pertanian: Fokus komoditas padi dan kopi (arabika dan robusta). PI-AREA. https://pi-dev.co.id/pires/topik/26.

Apriyana, Y., Surmaini, E., Estiningtyas, W., Pramudia, A., Ramadhani, F., Suciantini, S., Susanti, E., Purnamayani, R., & Syahbuddin, H. (2021). The integrated cropping calendar information system: A coping mechanism to climate variability for sustainable agriculture in Indonesia. Sustainability, 13(11), 1–22. https://doi.org/10.3390/su13116495.

Arguez, A., & Vose, R. S. (2011). The definition of the standard WMO climate normal: The key to deriving alternative climate normals. Bulletin of the American Meteorological Society, 92(6), 699–704.

Arnell, N. W., Lowe, J. A., Challinor, A. J., & Osborn, T. J. (2019). Global and regional impacts of climate change at different levels of global temperature increase. Climatic Change, 155, 377–391. https://doi.org/10.1007/S-10584-019-02464-z.

BMKG. (2023). Buletin Informasi Iklim Juni Tahun MMXXIII No.06 Tahun 2023.

BNPB. (2023). Data informasi bencana Indonesia. Diakses pada 22 Juni, 2023, dari https://dibi.bnpb.go.id/home/index2.

Braganza, K., Karoly, D. J., & Arblaster, J. M. (2004). Diurnal temperature range as an index of global climate change during the twentieth century. Geophysical research letters, 31(13). https://doi.org/10.1029/2004GL019998.

Dariah, A., & Surmaini, E. (2019). Menyelaraskan pertanian adaptif terhadap perubahan iklim di era industri 4.0. Dalam F. Djufry, E. Pasandaran, B. Irawan, & M. Ariani (Ed.), Manajemen sumber daya alam dan produksi mendukung pertanian modern (91–121). IPB Press. https://balaikliringkehati.menlhk.go.id/wp-content/uploads/ManajemenSDA-dan-Produksi.pdf.

Doi, T., Behera, S. K., & Yamagata, T. (2016). Improved seasonal prediction using the SINTEX-F2 coupled model. J. Adv. Model. Earth Syst., 8, 1847–1867. https://doi.org/10.1002/2016MS000744.

Doi, T., Storto, A., Behera, S. K., Navarra, A., & Yamagata, T. (2017). Improved prediction of the Indian Ocean Dipole mode by use of subsurface ocean observations. J. Clim., 30, 7953–7970. https://doi.org/10.1175/JCLI-D-16-0915.1.

Dore, M. H. (2005). Climate change and changes in global precipitation patterns: What do we know?. Environment International, 31(8), 1167–1181. https://doi.org/10.1016/j.envint.2005.03.004.

Duan, W., & Wei, C. (2013). The “spring predictability barrier” for ENSO predictions and its possible mechanism: Results from a fully coupled model. International Journal of Climatology, 33(5), 1280–1292. https://doi.org/10.1002/joc.3513.

Fan, X., & Konold, T. R. (2018). Canonical correlation analysis. In The reviewer’s guide to quantitative methods in the social sciences (G. R. Hancock, L. M. Stapleton, & R. O. Mueller, Ed.). Routledge, New York. pp. 29–41. https://doi.org/10.4324/9781315755649.

Fanggidae, Y. R., Dermoredjo, S. K., & Estiningtyas, W. (2021). Farmer’s perception on climate-related disasters and their impacts to support food farming. E3S Web of Conferences, 306, Artikel 02028. https://doi.org/10.1051/e3sconf/202130602028

Faqih, A., & Nurussyifa, D. (2017). Intraseasonal rainfall variability in North Sumatra and its relationship with Boreal Summer Intraseasonal Oscillation (BSISO). Dalam IOP conference series: Earth and environmental science (Vol. 54, Artikel 012033). https://doi.org/10.1088/1755-1315/54/1/012033.

Fistikoglu, O., & Okkan, U. (2011). Statistical downscaling of monthly precipitation using NCEP/NCAR reanalysis data for Tahtali River Basin in Turkey. Journal of Hydrologic Engineering, 16(2), 157–164. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000300.

Gerlak, A. K., Mason, S. J., Daly, M., Liverman, D., Guido, Z., Soares, M. B., Vaughan, C., Knudson, C., Greene, C., Buizer, J., & Jacobs, K. (2020). The gnat and the bull: Do Climate Outlook forums make a difference? Bulletin of the American Meteorological Society, 101(6), E771–E784. https://doi.org/10.1175/BAMS-D-19-0008.1.

Ghadami, A. & Epureanu, B. I. (2022). Data-driven prediction in dynamical systems: Recent developments. Phil. Trans. R. Soc. A., 380, Artikel 20210213. https://doi.org/10.1098/rsta.2021.0213.

Giannakis, D., & Majda, A. J. (2012). Nonlinear Laplacian spectral analysis for time series with intermittency and low-frequency variability. Proceedings of the National Academy of Sciences, 109(7), 2222–2227. https://doi.org/10.1073/pnas.1118984109.

Gulev, S. K., Thorne, P. W., Ahn, J., Dentener, F. J., Domingues, C. M., Gerland, S., Gong, D., Kaufman, D. S., Nnamchi, H. C., Quaas, J., Rivera, J. A., Sathyendranath, S., Smith, S. L., Trewin, B., von Schuckmann, K., & Vose, R. S. (2021). Changing state of the climate system. Dalam V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Pean, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekci, R. Yu, & B. Zhou (Ed.), Climate change 2021: The physical science basis. Contribution of Working Group I to the sixth assessment report of the intergovernmental panel on climate change (287–422). Cambridge University Press.

Gulizia, C., & Camilloni, I. (2015). Comparative analysis of the ability of a set of CMIP3 and CMIP5 global climate models to represent precipitation in South America. International Journal of Climatology, 35(4), 583–595. https://doi.org/10.1002/joc.4005.

Hansen, J. E., Sato, M., Simons, L., Nazarenko, L. S., Sangha, I., Kharecha, P., Zachos, J. C., Von Schuckmann, K., Loeb, N. G., Osman, M. B., Jin, Q., Tselioudis, G., Jeong, E., Lacis, A., Ruedy, R., Russell, G., Cao, J., & Li, J. (2023). Global warming in the pipeline. Oxford Open Climate Change, 3(1). https://doi.org/10.1093/oxfclm/kgad008.

Hewitt, C. D., Allis, E., Mason, S. J., Muth, M., Pulwarty, R., Shumake-Guillemot, J., Bucher, A., Brunet, M., Fischer, A. M., Hama, A. M., & Kolli, R. K. (2020). Making society climate resilient: International progress under the global framework for climate services. Bulletin of the American Meteorological Society, 101(2), E237–E252.

Hidalgo, H. G., Dettinger, M. D., & Cayan, D. R. (2008). Downscaling with constructed analogues: Daily precipitation and temperature fields over the United States (PIER Final Project Report, CEC-500-2007-123). California Energy Commission. https://core.ac.uk/download/pdf/489442819.pdf.

Hoerling, M. P., & Kumar, A. (1997). Why do North American climate anomalies differ from one El Niño event to another? Geophysical Research Letters, 24(9), 1059–1062.

IPCC. (2021). Climate change 2021: The physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou, Ed.). Cambridge University Press. https://doi.org/10.1017/9781009157896.

IPCC. (2022). Annex I: Glossary (R. van Diemen, J. B. R. Matthews, V. Möller, J. S. Fuglestvedt, V. Masson-Delmotte, C. Méndez, A. Reisinger, & S. Semenov, Ed.). Dalam P. R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, & J. Malley (Ed.), Climate change 2022: Mitigation of climate change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. https://doi.org/10.1017/9781009157926.020.

Juang, J., & Pappa, R.S. (1985). An eigensystem realization algorithm for modal parameter identification and model reduction. Journal of Guidance, Control, and Dynamics, 8(5). https://doi.org/10.2514/3.20031.

Juneng, L., Tangang, F. T., Kang, H., Lee, W. J., & Seng, Y. K. (2010). Statistical downscaling forecasts for winter monsoon precipitation in Malaysia using multimodel output variables. Journal of Climate, 23(1), 17–27. https://doi.org/10.1175/2009JCLI2873.1.

Kang, H., An, K. H., Park, C. K., Solis, A. L. S., & Stitthichivapak, K. (2007). Multimodel output statistical downscaling prediction of precipitation in the Philippines and Thailand. Geophysical research letters, 34(15), L15710. https://doi.org/10.1029/2007GL030730.

Kementerian Pertanian. (2021). Kalender tanam tanaman padi. KATAM Musim Kemarau, April–September. SI Katam Terpadu 3.2. Kementerian Pertanian.

Koberl, J., François, H., Cognard, J., Carmagnola, C., Prettenthaler, F., Damm, A., & Morin, S. (2021). The demand side of climate services for real-time snow management in Alpine ski resorts: some empirical insights and implications for climate services development. Climate Services, 22, 100238. https://doi.org/10.1016/j.cliser.2021.100238.

Komalasari, K. E., Fajariana, Y., Nuraini, T. A., & Anggraeni, R. (2016). Aplikasi metode Ensemble Mean untuk meningkatkan reliabilitas prediksi HyBMG. Jurnal Meteorologi dan Geofisika, 17(1), 47–52.

Kusfirdianti, F., & Wiratmo, J. (2022). Rainfall prediction due to the Madden Julian Oscillation factor at the equator. Dalam Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) (Vol. 3). https://doi.org/10.29103/micoms.v3i.231.

Kutz, J. N., Brunton, S. L., Brunton, B. W., & Proctor, J. L. (2016) Dynamic mode decomposition: data-driven modeling of complex systems. SIAM.

Lai, A. W. C., Herzog, M., & Graf, H. F. (2018). ENSO forecasts near the spring predictability barrier and possible reasons for the recently reduced predictability. Journal of Climate, 31(2), 815–838. https://doi.org/10.1175/JCLI-D-17-0180.1.

Liu, S., Waqas, M. A., Wang, S. H., Xiong, X. Y., & Wan, Y. F. (2017). Effects of increased levels of atmospheric CO2 and high temperatures on rice growth and quality. PLoS One, 12(11), e0187724. https://doi.org/10.1371/journal.pone.0187724.

Lynas, M., Houlton, B. Z., & Perry, S. (2021). Greater than 99% consensus on human-caused climate change in the peer-reviewed scientific literature. Environmental Research Letters, 16(11), 114005. https://doi.org/10.1088/1748-9326/ac2966.

Ma, J., Wang, H., & Fan, K. (2015). Dynamic downscaling of summer precipitation prediction over China in 1998 using WRF and CCSM4. Advances in Atmospheric Sciences, 32(5), 577–584. https://doi.org/10.1007/s00376-014-4143-y.

Mahla, P., Lohani, A. K., Chandola, V. K., Thakur, A., Mishra, C. D., & Singh, A. (2019). Downscaling of precipitation using multiple linear regression over Rajasthan state. Current World Environment, 14(1), 68–98. http://dx.doi.org/10.12944/CWE.14.1.09.

Makmur, E. E. S., & Setiawan, A. M. (2013). Sistem dan teknologi peramalan iklim. Dalam Prosiding seminar nasional sains dan aplikasi komputasi (SENSAKOM).

Muharsyah, R., Ripaldi, A., Maharani, T., Fitrianti, N., Hanif, R. D., Denata, M., Eggy, A. C., & Wahyuni, N. (2020). Perbandingan model Kopel ECMWF System 4 dan CFSv2 untuk prediksi musim di Indonesia. Megasains, 11(1), 1–11.

Mulyaqin, T. (2020). The impact of El Niño and La Niña on fluctuation of rice production in Banten province. Agromet, 34(1), 34–41. https://doi.org/10.29244/j.agromet.34.1.34-41.

Nair, A., Mohanty, U. C., & Panda, T. C. (2015). Improving the performance of precipitation outputs from Global Climate Models to predict monthly and seasonal rainfall over the Indian subcontinent. Comptes Rendus Geoscience, 347(2), 53–63. https://doi.org/10.1016/j.crte.2015.03.004.

Naylor, R. L., Battisti, D. S., Vimont, D. J., Falcon, W. P., & Burke, M. B. (2007). Assessing risks of climate variability and climate change for Indonesian rice agriculture. Proceedings of the National Academy of Sciences, 104(19), 7752–7757.

Nuraini, T. A., Nuryanto, D. E., Komalasari, K. E., Satyaningsih, R., Fajariana, Y., Anggraeni, R., & Sopaheluwakan, A. (2019). Pengembangan model HyBMG 2.07 untuk prediksi iklim di Indonesia dengan menggunakan data Tropical Rainfall Measuring Mission (TRMM). Jurnal Meteorologi dan Geofisika, 20(2), 101–112.

Oettli, P., Nonaka, M., Richter, I., Koshiba, H., Tokiya, Y., Hoshino, I., & Behera, S. K. (2022). Combining dynamical and statistical modeling to improve the prediction of surface air temperatures 2 months in advance: A hybrid approach. Frontiers in Climate, 4, 862707. https://doi.org/10.3389/fclim.2022.862707.

Pai, D. S., Rao, A. S., Senroy, S., Pradhan, M., Pillai, P. A., & Rajeevan, M. (2017). Performance of the operational and experimental long-range forecasts for the 2015 southwest monsoon rainfall. Current Science, 112(1), 68–75.

Pandia, F. S., Sasmito, B., & Sukmono, A. (2019). Analisis pengaruh angin monsun terhadap perubahan curah hujan dengan penginderaan jauh (Studi kasus: Provinsi Jawa Tengah). Jurnal Geodesi Undip, 8(1), 278–287. https://doi.org/10.14710/jgundip.2019.22581.

Pendergrass, A. G., Knutti, R., Lehner, F., Deser, C., & Sanderson, B. M. (2017). Precipitation variability increases in a warmer climate. Scientific Reports, 7(1), 1–9. https://doi.org/10.1038/s41598-017-17966-y.

Penny, S. G., & Hamill, T. M. (2017). Coupled data assimilation for integrated earth system analysis and prediction. Bulletin of the American Meteorological Society, 98(7), ES-169–ES-172. https://www.jstor.org/stable/10.2307/26243775.

Perdinan, P., Atmaja, T., Adi, R. F., & Estiningtyas, W. (2019). Adaptasi perubahan iklim dan ketahanan pangan: telaah inisiatif dan kebijakan. Jurnal Hukum Lingkungan Indonesia, 5(1), 60–87. https://doi.org/10.38011/jhli.v5i1.75.

Pryor, S. C., & Schoof, J. T. (2020). Differential credibility assessment for statistical downscaling. Journal of Applied Meteorology and Climatology, 59(8), 1333–1349. https://doi.org/10.1175/JAMC-D-19-0296.1.

Qin, T., Wu, K., & Xiu, D. (2019). Data driven governing equations approximation using deep neural networks. Journal of Computational Physics, 395, 620–635. https://doi.org/10.1016/j.jcp.2019.06.042.

Rahman, S. (2018). Membangun pertanian dan pangan untuk mewujudkan kedaulatan pangan. Deepublish.

Ranasinghe, R., Ruane, A. C., Vautard, R., Arnell, N., Coppola, E., Cruz, F. A., Dessai, S., Islam, A. S., Rahimi, M., Ruiz Carrascal, D., Sillmann, J., Sylla, M. B., Tebaldi, C., Wang, W., & Zaaboul, R. (2021). Climate change information for regional impact and for risk assessment. Dalam V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou (Ed.), Climate change 2021: The physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (1767–1926). Cambridge University Press.

Sachindra, D. A., & Perera, B. J. C. (2016). Statistical downscaling of general circulation model outputs to precipitation accounting for Non-Stationarities in Predictor-Predictand Relationships. PLoS One, 11(12), e0168701. https://doi.org/10.1371/journal.pone.0168701

Sari, H. P., & Sari, S. K. (2022). Dampak perubahan iklim terhadap produksi padi. Science and Research Journal Of Mai Wandeu, 2(1), 87–94. https://doi.org/10.31933/srjmw.v2i1.71.

Slingo, J., & Palmer, T. (2011). Uncertainty in weather and climate prediction. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369(1956), 4751–4767. https://doi.org/10.1098/rsta.2011.0161.

Strazzo, S., Collins, D. C., Schepen, A., Wang, Q. J., Becker, E., & Jia, L. (2019). Application of a Hybrid Statistical–Dynamical System to Seasonal Prediction of North American Temperature and Precipitation. Monthly Weather Review, 147(2), 607–625.

Subagyono, K., Surmaini, E., Estiningtyas, W., & Susanti, E. (2022). Causes of climate change and its impacts on agriculture. Dalam E. Husen, S. Marwanto, & F. Agus (Ed), Strengthening agricultural resilience against climate change through climate smart agriculture. IAARD Press. https://repository.pertanian.go.id/server/api/core/bitstreams/c8960f0e-2e2D-4a3c-bcf7-0000b807a042/content

Surmaini, E. (2016). Pemantauan dan Peringatan dini kekeringan pertanian di Indonesia. Jurnal Sumberdaya Lahan, 10(1), 37–50.

Surmaini, E., & Agus, F. (2020). Pengelolaan resiko iklim untuk pertanian berkelanjutan di Indonesia: Sebuah tinjauan. Jurnal Penelitian dan Pengembangan Pertanian, 39(1), 48–60. https://doi.org/10.21082/jp3.v39n1.2020.p48-60.

Surmaini, E., & Faqih, A. (2016). Kejadian iklim ekstrem dan dampaknya terhadap pertanian tanaman pangan di Indonesia. Jurnal Sumberdaya Lahan, 10(2), 115–128. https://repository.pertanian.go.id/handle/123456789/2245.

Surmaini, E., & Hadi, T. W. (2020). Verifikasi prediksi curah hujan ensemble menggunakan metode Roc. Jurnal Meteorologi dan Geofisika, 21(1), 37–44. http://202.90.199.54/jmg/index.php/jmg/article/view/618.

Surmaini, E., & Syahbuddin, H. (2016). Kriteria awal musim tanam: tinjauan prediksi waktu tanam padi di Indonesia. Jurnal Litbang Pertanian, 35(2), 47–56.

Surmaini, E., Hadi, T. W., Subagyono, K., Pasarminggu, S. J., & Puspito, N. T. (2015). Prediction of drought impact on rice paddies in west Java using analogue downscaling method. Indonesian Journal of Agriculture Science, 16(1), 21–30. https://repository.pertanian.go.id/handle/123456789/42.

Susanti, E., Surmaini, E., & Estiningtyas, W. (2018). Parameter iklim sebagai indikator peringatan dini serangan hama penyakit tanaman. Jurnal Sumberdaya Lahan, 12(1), 59–70.

Sutardi, Apriyana, Y., Rejekiningrum, P., Alifia, A. D., Ramadhani, F., Darwis, V., & Fadwiwati, A. Y. (2022). The transformation of rice crop technology in Indonesia: Innovation and sustainable food security. Agronomy, 13(1), 1. https://doi.org/10.3390/agronomy13010001.

Utami, A. W., & Hardyastuti, S. (2011). El Niño, La Niña, dan penawaran pangan di Jawa, Indonesia. Jurnal Ekonomi Pembangunan, 12(2), 257–271.

Voss, H.U., Kolodner, P., Abel, M., & Kurths, J. (1999). Amplitude equations from spatiotemporal binary-fluid convection data. Phys. Rev. Lett., 83, 3422. https://doi:10.1103/PhysRevLett.83.3422.

Webb, L., Tozer, C., Bettio, L., Darbyshire, R., Robinson, B., Fleming, A., Tijs, S., Bodman, R., & Prakash, M. (2023). Climate services for agriculture: Tools for informing decisions relating to climate change and climate variability in the wine industry. Australian Journal of Grape and Wine Research, 2023(1). https://doi.org/10.1155/2023/5025359.

Wilks, D. S. (2011). Statistical methods in the atmospheric sciences (Vol. 100). Academic Press.

Williams, M. O., Kevrekidis, I. G., & Rowley, C. W. (2015). A data-driven approximation of the Koopman operator: Extending dynamic mode decomposition. Journal of Nonlinear Science, 25(6), 1307–1346. https://:10.1007/s00332-015-9258-5.

Winarno, G. D., Harianto, S. P., & Santoso, T. (2019). Klimatologi pertanian. Pusaka Media.

WMO. (2007). The role of climatological normals in a changing climate. World Meteorological Organization. WCDMP-No. 61, WMO-TD No. 1377.

WMO. (2021). State of the global climate 2020. World Meteorological Organization. WMO-No. 1264.

Yhang, Y. B., Sohn, S. J., & Jung, I. W. (2017). Application of dynamical and statistical downscaling to East Asian summer precipitation for finely resolved datasets. Advances in Meteorology, ID 2956373. https://doi.org/10.1155/2017/2956373.

Yuan, D., Wang, J., Xu, T., Xu, P., Hui, Z., Zhao, X., Luan, Y., Zheng, W., & Yu, Y. (2011). Forcing of the Indian Ocean Dipole on the interannual variations of the tropical Pacific Ocean: roles of the Indonesian throughflow. Journal of Climate, 24(14), 3593–3608. https://doi.org/10.1175/2011JCLI3649.1.

Zhang, X., & Yan, X. (2015). A new statistical precipitation downscaling method with Bayesian model averaging: a case study in China. Climate Dynamics, 45, 2541–2555. https://doi.org/10.1007/s00382-015-2491-7.

Zhao, J., Bindi, M., Eitzinger, J., Ferrise, R., Gaile, Z., Gobin, A., Holzkamper, A., Kersebaum, K., Kozyra, J., Kriauciuniene, Z., Loit, E., Nejedlik, P., Nendel, C., Niinemets, U., Palosuo, T., Peltonen-Sainio, P., Potopova, V., Ruiz-Ramos, M., Reidsma, P., . . . Olesen, J. E. (2022). Priority for climate adaptation measures in European crop production systems. European Journal of Agronomy, 138, 126516. https://doi.org/10.1016/j.eja.2022.126516.

Aldrian, E., & Susanto, R. D. (2003). Identification of three dominant rainfall regions within Indonesia and their relationship to sea surface temperature. International Journal of Climatology, 23(12), 1435–1452. https://doi.org/10.1002/joc.950.

Balsa, C., Rodrigues, C. V., Araújo, L., & Rufino, J. (2022). Cluster-based analogue ensembles for hindcasting with multistations. Computation, 10(6), 91. https://doi.org/10.3390/computation10060091.

BMKG. (2021a). Buku Pemutakhiran zona musim Indonesia periode 1991–2020. Pusat Informasi Perubahan Iklim.

BMKG. (2021b). Buku peta rata-rata curah hujan dan hari hujan periode 1991–2020 Indonesia. Pusat Informasi Perubahan Iklim.

BMKG. (2023). Buku prakiraan musim kemarau 2023. Pusat Informasi Perubahan Iklim.

BMKG. (2023). Pemutakhiran metode prediksi musim 2023. Pusat Informasi Perubahan Iklim.

BMKG. (2023). Pemutakhiran zona musim 2023. Pusat Informasi Perubahan Iklim.

Borema, B. (1926). Maps of the mean annual and monthly rainfall in Sumatra. Verhandelingen, Koninklijk Magnetisch En Meteorologisch Observatorium, Batavia.

Charles, A., Duell, R., Wang, X., & Watkins, A. (2015). Seasonal forecasting for Australia using a dynamical model: Improvements in forecast skill over the operational statistical model. Australian Meteorological and Oceanographic Journal, 65(3/4), 356–375. https://doi.org/10.22499/2.6503.005.

Diong, J. Y., Abdullah, M. F. A. B., Permana, D., Pura, A., Lam, H., & Xavier, P. (2023). Regional features of Boreal summer intraseasonal variability and their relationship with rainfall extremes over Southeast Asia [Preprint]. https://doi.org/10.21203/rs.3.rs-3039141/v1.

Hamill, T. M., Scheuerer, M., & Bates, G. T. (2015). Analog probabilistic precipitation forecasts using GEFS reforecasts and climatology-calibrated precipitation analyses*. Monthly Weather Review, 143(8), 3300–3309. https://doi.org/10.1175/MWR-D-15-0004.1.

Hamill, T. M., & Whitaker, J. S. (2006). Probabilistic quantitative precipitation forecasts based on reforecast analogs: Theory and application. Monthly Weather Review, 134(11), 3209–3229. https://doi.org/10.1175/MWR3237.1.

Horton, P., Obled, C., & Jaboyedoff, M. (2017). The analogue method for precipitation prediction: Finding better analogue situations at a subdaily time step. Hydrology and Earth System Sciences, 21(7), 3307–3323. https://doi.org/10.5194/hess-21-3307-2017.

IMD. (t.t.). Frequently asked Questions (FAQs) on Monsoon. https://mausam.imd.gov.in/imd_latest/monsoonfaq.pdf

Johnson, S. J., Stockdale, T. N., Ferranti, L., Balmaseda, M. A., Molteni, F., Magnusson, L., Tietsche, S., Decremer, D., Weisheimer, A., Balsamo, G., Keeley, S. P. E., Mogensen, K., Zuo, H., & Monge-Sanz, B. M. (2019). SEAS5: The new ECMWF seasonal forecast system. Geoscientific Model Development, 12(3), 1087–1117. https://doi.org/10.5194/gmd-12-1087-2019.

Lafon, T., Dadson, S., Buys, G., & Prudhomme, C. (2013). Bias correction of daily precipitation simulated by a regional climate model: A comparison of methods: Bias Correction of Daily Precipitation Simulated by a Regional Climate Model. International Journal of Climatology, 33(6), 1367–1381. https://doi.org/10.1002/joc.3518.

Latos, B., Lefort, T., Flatau, M. K., Flatau, P. J., Permana, D. S., Baranowski, D. B., Paski, J. A. I., Makmur, E., Sulystyo, E., Peyrillé, P., Feng, Z., Matthews, A. J., & Schmidt, J. M. (2021). Equatorial waves triggering extreme rainfall and floods in Southwest Sulawesi, Indonesia. Monthly Weather Review, 149(5), 1381–1401. https://doi.org/10.1175/MWR-D-20-0262.1.

Mamenun, M., Pawitan, H., & Sopaheluwakan, A. (2014). Validasi dan koreksi data satelit trmm pada tiga pola hujan di Indonesia. Jurnal Meteorologi dan Geofisika, 15(1). https://doi.org/10.31172/jmg.v15i1.169.

Molteni, F., Buizza, R., Palmer, T. N., & Petroliagis, T. (1996). The ECMWF ensemble prediction system: Methodology and validation. Quarterly Journal of the Royal Meteorological Society, 122(529), 73–119. https://doi.org/10.1002/qj.49712252905.

Nuraini, T. A., Nuryanto, D. E., Komalasari, K. E., Satyaningsih, R., Fajariana, Y., Anggraeni, R., & Sopaheluwakan, A. (2019). Pengembangan model HyBMG 2.07 untuk prediksi iklim di Indonesia dengan menggunakan data Tropical Rainfall Measuring Mission (TRMM). Jurnal Meteorologi dan Geofisika, 20(2), 101. https://doi.org/10.31172/jmg.v20i2.610.

Nury, A. H., Hasan, K., & Alam, M. J. B. (2017). Comparative study of wavelet-ARIMA and wavelet-ANN models for temperature time series data in northeastern Bangladesh. Journal of King Saud University - Science, 29(1), 47–61. https://doi.org/10.1016/j.jksus.2015.12.002.

NWS CPC. (2021). Long-lead forecast tool discussion and analysis. National Weather Service. https://www.cpc.ncep.noaa.gov/products/predictions/long_range/tools.html

Permana, D. S. & Supari. (2021). Impacts of the MJO on Rainfall at Different Seasons in Indonesia. Dalam IOP conference series: Earth and environmental science (Vol. 893, Artikel 012070). https://doi.org/10.1088/1755-1315/893/1/012070.

Ratri, D. N., Weerts, A., Muharsyah, R., Whan, K., Tank, A. K., Aldrian, E., & Hariadi, M. H. (2023). Calibration of ECMWF SEAS5 based streamflow forecast in Seasonal hydrological forecasting for Citarum river basin, West Java, Indonesia. Journal of Hydrology: Regional Studies, 45, 101305. https://doi.org/10.1016/j.ejrh.2022.101305.

Ratri, D. N., Whan, K., & Schmeits, M. (2019). A comparative verification of raw and bias-corrected ECMWF seasonal ensemble precipitation reforecasts in Java (Indonesia). Journal of Applied Meteorology and Climatology, 58(8), 1709–1723. https://doi.org/10.1175/JAMC-D-18-0210.1.

Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y.-T., Chuang, H., Iredell, M., Ek, M., Meng, J., Yang, R., Mendez, M. P., Van Den Dool, H., Zhang, Q., Wang, W., Chen, M., & Becker, E. (2014). The NCEP Climate Forecast System Version 2. Journal of Climate, 27(6), 2185–2208. https://doi.org/10.1175/JCLI-D-12-00823.1

Slingo. (2015). Tropical meteorology and climate | Monsoon: Overview. Dalam Encyclopedia of Atmospheric Sciences (Second). Elsevier.

Supari, Tangang, F., Salimun, E., Aldrian, E., Sopaheluwakan, A., & Juneng, L. (2018). ENSO modulation of seasonal rainfall and extremes in Indonesia. Climate Dynamics, 51(7–8), 2559–2580. https://doi.org/10.1007/s00382-017-4028-8.

Solis, A. L. S. (2023). Seasonal forecast in Philipina. GOVPH. https://bagong.pagasa.dost.gov.ph/climate/climate-prediction/seasonal-forecast

Thapliyal, V. (1997). Preliminary and final long range forecast for seasonal monsoon rainfall over India. Journal of Arid Environments, 36(3), 385–403. https://doi.org/10.1006/jare.1996.0233.

Tjasyono, B. (1999). Klimatologi umum. ITB.

Wati, T., Kusumaningtyas, S. D. A., & Aldrian, E. (2019). Study of season onset based on water requirement assessment. Dalam IOP conference series: Earth and environmental science (Vol. 299, Artikel 012042). https://doi.org/10.1088/1755-1315/299/1/012042.

Winarso, P. A. (2001). Sistem prakiraan cuaca dan iklim Indonesia.

Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration - Guidelines for computing crop water requirements (Paper-56). FAO - Food and Agriculture Organization of the United Nations. https://www.fao.org/3/X0490E/x0490e00.htm

Artikanur, S. D., Widiatmaka, Setiawan, Y., & Marimin. (2022). Normalized Difference Drought Index (NDDI) computation for mapping drought severity in Bojonegoro Regency, East Java, Indonesia. Dalam IOP conference series: Earth and environmental science (Vol. 1109, Artikel 012027). https://doi.org/10.1088/1755-1315/1109/1/012027.

Bachri, S., & Sulaeman, Y. (2015). SPKL: Program komputer untuk evaluasi kesesuaian lahan. Dalam Prosiding seminar nasional informatika pertanian 2015 (160–172). Fakultas Teknologi Industri Pertanian Universitas Padjajaran.

Bloomberg, J. (2018). Digitization, digitalization, and digital transformation: confuse them at your peril. Forbes.

IPCC. (2022). Fact Sheets. https://www.ipcc.ch/report/ar6/wg2/about/factsheets.

Lindgren, D. T. (1985). Land use planning and remote sensing. Springer. https://doi.org/10.1007/978-94-017-2035-9

Diyasti, F., & Amalia, A. W. (2021). Peran perubahan iklim terhadap kemunculan OPT baru. AGROSCRIPT: Journal of Applied Agricultural Sciences, 3(1), 57–69.

Doorenbos, J., Kassam, A. H., Bentvelsen, C., & Uittenbogaard, G. (1980). Yield Response to water-Paper 33. In Irrigation and Agricultural Development. FAO - Food and Agriculture Organization of the United Nations.

Estiningtyas W, Ramadhani F, & Aldrian E. (2007). Analisis korelasi curah hujan dan suhu permukaan laut wilayah Indonesia, serta implikasinya untuk prakiraan curah hujan (studi kasus Kabupaten Cilacap). Jurnal Agromet Indonesia, 21(2), 46–60.

Gabr, M. Els. (2022a). Management of irrigation requirements using FAO-CROPWAT 8.0 model: A case study of Egypt. Modeling Earth System and Environment, 8, 3127–3142. https://doi.org/https://doi.org/10.1007/s40808-021-01268-4

Gabr, M. Els. (2022b). Modelling net irrigation water requirements using FAO-CROPWAT 8.0 and CLIMWAT 2.0: A case study of Tina Plain and East South ElKantara regions, North Sinai, Egypt. Archives of Agronomy and Soil Science, 68(10), 1322–1337. https://doi.org/10.1080/03650340.2021.1892650

Hermans, K., & McLeman, R. (2021). Climate change, drought, land degradation and migration: Exploring the linkages. Current Opinion in Environmental Sustainability, 50, 236–244. https://doi.org/10.1016/j.cosust.2021.04.013

Hosang M. L. A. (2017, 9 Mei). Kajian potensi hama tanaman palma dan strategi pengendalian secara hayati. Simposium Kurma Tropika I,Balai Penelitian Tanaman Palma Bogor, Indonesia.

Roja, M., Deepthi, Ch., & Reddy, M. D. (2020). Estimation of crop water requirement of sunflower crop using FAO CROPWAT 8.0 model for North Coastal Andhra Pradesh. Agro Economist - An International Journal, 7(2), 13–18.

Makridakis S, Wheelwright S. C., & Hyndman R. J. (1998). Forecasting: Methods and applications (Edisi ke-3). John Wiley and Sons.

Mujiyo, M., Nurdianti, R., Komariah, & Sutarno. (2023). Agricultural land dryness distribution using the Normalized Difference Drought Index (NDDI) algorithm on Landsat 8 imagery in Eromoko, Indonesia.Environment and Natural Resources Journal, 21(2), 127–139. https://doi.org/10.32526/ennrj/21/202200157

Mulyani, A., Priyono, A., & Agus, F. (2013). Semiarid soils of eastern Indonesia: Soil classification and land uses. Dalam S. A. Shahid et al. (Ed.), Developments in soil classification, land use planning and policy implications: Innovative thinking of soil inventory for land use planning and management of land resources (449–466).

NASA. (2023). NASA POWER | DAV. Diakses 10 September, 2023, dari https://power.larc.nasa.gov/data-access-viewer/

Renza, D., Martinez, E., Arquero, A., & Sanchez, J. (2010, Mei). Drought estimation maps by means of multidate Landsat fused images. Dalam Proceedings of the 30th EARSeL Symposium (775–782). https://www.earsel.org/symposia/2010-symposium-Paris/Proceedings/EARSeL-Symposium-2010_17-03.pdf

Rismayatika, F., Saraswati, R., Shidiq, I. P. A., & Taqyyudin. (2020). Identification of dry areas on agricultural land using normalized difference drought index in Magetan Regency. Dalam IOP conference series: Earth and environmental science (Vol. 540, Artikel 012029). https://doi.org/10.1088/1755-1315/540/1/012029

Rizky, M. (2023). Petaka kekeringan hantam 27.000 ha pertanian RI efek El Niño. CNBC Indonesia. https://www.cnbcindonesia.com/news/20230809122706-4-461431/petaka-kekeringan-hantam-27000-ha-pertanian-ri-efek-El Niño.

Roja, M. (2020). Estimation of Crop Water Requirement of Maize Crop Using FAO CROPWAT 8.0 Model. Indian Journal of Pure & Applied Biosciences, 8(6), 222–228. https://doi.org/10.18782/2582-2845.8148

Smith, M. (1992). CROPWAT: A computer program for irrigation planning and management. Dalam FAO Irrigation and Drainage Paper 46 (46th ed., Issue 46). FAO.

Tono, Andayani, D. W., Hidayat, A., Maheswari, L. D.; Ulfa, N. A. (2022). Indeks ketahanan pangan tahun 2022. Badan Pangan Nasional.

Undang-Undang Republik Indonesia Nomor 18 Tahun 2012 tentang Pangan (2012). https://peraturan.bpk.go.id/Details/39100

Wang, W., Feng, Z., & Ma, M. (2022). Climate changes and hydrological processes. Water, 14(23), 3922. https://doi.org/10.3390/w14233922.

Yuliyani, L., Salam, R., Bahar, R. R., Hartoyo, T., & Pramita, D. A. (2023). Analisis efisiensi usahatani padi berdasarkan musim di Indonesia. Jurnal Agristan, 5(1), 74–87.

Aydinli, S., & Krochmann, J. (1987). Guide on daylighting of building interiors. Dalam Data on daylight and solar radiation, Draft, CIE.

Badan Pusat Statistik. (2022a). Kelembapan udara per bulan di Kota Bandung (persen), 2020-2022. BPS. https://bandungkota.bps.go.id/indicator/151/1249/1/kelembapan-udara-per-bulan-di-kota-bandung.html

Badan Pusat Statistik. (2022b). Penyinaran matahari per bulan di Kota Bandung (Persen), 2020-2022. BPS. https://bandungkota.bps.go.id/indicator/151/1250/1/penyinaran-matahari-per-bulan-di-kota-bandung.html

Bartoszek, K., & Matuszko, D. (2021). The influence of atmospheric circulation over Central Europe on the long-term variability of sunshine duration and air temperature in Poland. Atmospheric Research, 251(December 2020), 105427. https://doi.org/10.1016/j.atmosres.2020.105427

Black, K. (2023). Business statistics: For contemporary decision making. John Wiley & Sons.

Chatfield, C., & Xing, H. (2019). The analysis of time series: An introduction with R. CRC Press.

Choab, N., Allouhi, A., Maakoul, A. El, Kousksou, T., Saadeddine, S., & Jamil, A. (2021). Effect of greenhouse design parameters on the heating and cooling requirement of greenhouses in Moroccan climatic conditions. IEEE Access, 9, 2986–3003. https://doi.org/10.1109/ACCESS.2020.3047851

Dobin, A. (2010). Data mining techniques for the life sciences. Dalam O. Carugo & F. Eisenhaber (Eds.), Springer protocols - methods in molecular biology 609 (Vol. 609, Issue January 2010). Humana Press. https://doi.org/10.1007/978-1-60327-241-4

Hastie, T., Friedman, J., & Tibshirani, R. (2001). Additive models, trees, and related methods. Dalam The elements of statistical learning: Data mining, inference, and prediction (257–298). Springer. https://doi.org/10.1007/978-0-387-21606-5_9

Heino, M., Kinnunen, P., Anderson, W., Ray, D. K., Puma, M. J., Varis, O., Siebert, S., & Kummu, M. (2023). Increased probability of hot and dry weather extremes during the growing season threatens global crop yields. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-29378-2

Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression (3rd ed.). John Wiley & Sons. https://doi.org/10.1002/9781118548387

Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and practice. Otexts. https://otexts.com/fpp2/

Jeantet, A., Thirel, G., Lemaitre-Basset, T., & Tournebize, J. (2023). Uncertainty propagation in a modelling chain of climate change impact for a representative French drainage site. Hydrological Sciences Journal, 68(10), 1426–1442. https://doi.org/10.1080/02626667.2023.2203322

Johansson, I. (2010). Metrological thinking needs the notions of parametric quantities, units and dimensions. Metrologia, 47(3), 219–230. https://doi.org/10.1088/0026-1394/47/3/012

Korotcenkov, G. (2018). Handbook of humidity measurement, Volume 1: Spectroscopic methods of humidity measurement. CRC Press.

Korotcenkov, G. (2020). Handbook of Humidity Measurement, Volume 3: Sensing materials and technologies. CRC Press.

Liang, Y., Tabler, G. T., & Dridi, S. (2020). Sprinkler technology improves broiler production sustainability: From stress alleviation to water usage conservation: A mini review. Frontiers in Veterinary Science, 7(9), 1–8. https://doi.org/10.3389/fvets.2020.544814

Maafi, A., & Adane, A. (1998). Analysis of the performances of the first-order two-state Markov model using solar radiation properties. Renewable Energy, 13(2), 175–193. https://doi.org/10.1016/S0960-1481(97)00094-3

McClymont, H., Si, X., & Hu, W. (2023). Using weather factors and Google data to predict COVID-19 transmission in Melbourne, Australia: A time-series predictive model. Heliyon, 9(3), artikel e13782. https://doi.org/10.1016/j.heliyon.2023.e13782

Nagaraj, R., & Kumar, L. S. (2023). Univariate deep learning models for prediction of daily average temperature and relative humidity: The case study of Chennai, India. Journal of Earth System Science, 132(3). https://doi.org/10.1007/S-12040-023-02122-0

Nagarajan, G., & Minu, R. I. (2018). Wireless soil monitoring sensor for sprinkler irrigation automation system. Wireless Personal Communications, 98(2), 1835–1851. https://doi.org/10.1007/S-11277-017-4948-y

Panesar, A. (2021). Machine learning algorithms. Dalam Machine learning and AI for healthcare (85–144). Apress. https://doi.org/10.1007/978-1-4842-6537-6_4

Paolella, M. S. (2018). Linear models and time-series analysis: Regression, ANOVA, ARMA and GARCH. Wiley. https://doi.org/10.1002/9781119432036

Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babai, M. Z., Barrow, D. K., Ben Taieb, S., Bergmeir, C., Bessa, R. J., Bijak, J., Boylan, J. E., Browell, J., Carnevale, C., Castle, J. L., Cirillo, P., Clements, M. P., Cordeiro, C., Cyrino Oliveira, F. L., De Baets, S., Dokumentov, A., … Ziel, F. (2022). Forecasting: Theory and practice. International Journal of Forecasting, 38(3), 705–871. https://doi.org/10.1016/j.ijforecast.2021.11.001

Rahim, R., Baharuddin, & Mulyadi, R. (2004). Classification of daylight and radiation data into three sky conditions by cloud ratio and sunshine duration. Energy and Buildings, 36(7), 660–666. https://doi.org/10.1016/j.enbuild.2004.01.012

Rudin, C. (2019). Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence, 1(5), 206–215. https://doi.org/10.1038/s42256-019-0048-x

Rumble, J. (Ed.). (2017). CRC handbook of chemistry and physics (98th ed.). CRC Press.

Saadon, T., Lazarovitch, N., Jerszurki, D., & Tas, E. (2021). Predicting net radiation in naturally ventilated greenhouses based on outside global solar radiation for reference evapotranspiration estimation. Agricultural Water Management, 257(August), 107102. https://doi.org/10.1016/j.agwat.2021.107102

Sammut, C., & Webb, G. I. (Ed.). (2010). Encyclopedia of machine learning. Springer. https://doi.org/10.1007/978-0-387-30164-8

Santos, C. M. dos, Escobedo, J. F., de Souza, A., da Silva, M. B. P., & Aristone, F. (2021). Prediction of solar direct beam transmittance derived from global irradiation and sunshine duration using anfis. International Journal of Hydrogen Energy, 46(55), 27905–27921. https://doi.org/10.1016/j.ijhydene.2021.06.044

Sridhara, S., Manoj, K. N., Gopakkali, P., Kashyap, G. R., Das, B., Singh, K. K., & Srivastava, A. K. (2023). Evaluation of machine learning approaches for prediction of pigeon pea yield based on weather parameters in India. International Journal of Biometeorology, 67(1), 165–180. https://doi.org/10.1007/s00484-022-02396-x

Tabari, H., & Willems, P. (2023). Global risk assessment of compound hot-dry events in the context of future climate change and socioeconomic factors. Npj Climate and Atmospheric Science, 6(1). https://doi.org/10.1038/s41612-023-00401-7

Andrews, D. G., Leovy, C. B., & Holton, J. R. (2016). Middle atmosphere dynamics (Vol. 40). Academic Press.

Anthes, R. A. (2011). Exploring Earth’s atmosphere with radio occultation: contributions to weather, climate and space weather. Atmospheric Measurement Techniques, 4(6), 1077–1103.

Anthes, R. A., Bernhardt, P. A., Chen, Y., Cucurull, L., Dymond, K. F., Ector, D., Healy, S. B., Ho, S., Hunt, D. C., Kuo, Y., Liu, H., Manning, K., McCormick, C., Meehan, T. K., Randel, W. J., Rocken, C., Schreiner, W. S., Sokolovskiy, S. V., Syndergaard, S., . . . Zeng, Z. (2008). The COSMIC/FORMOSAT-3 Mission: Early results. Bulletin of the American Meteorological Society, 89(3), 313–334. https://doi.org/10.1175/bams-89-3-313

Anthes, R. A., Rocken, C., & Ying-Hwa, K. (2000). Applications of COSMIC to meteorology and climate. Terrestrial Atmospheric and Oceanic Sciences, 11(1), 115-156.

Ho, S., Anthes, R. A., Ao, C. O., Healy, S., Horanyi, A., Hunt, D., Mannucci, A. J., Pedatella, N., Randel, W. J., Simmons, A., Steiner, A., Xie, F., Yue, X., & Zeng, Z. (2020). The COSMIC/FORMOSAT-3 radio occultation mission after 12 years: Accomplishments, remaining challenges, and potential impacts of COSMIC-2. Bulletin of the American Meteorological Society, 101(7), E1107–E1136. https://doi.org/10.1175/bams-d-18-0290.1

Holton, J. R. (2004). An introduction to dynamic meteorology (4th ed.). Elsevier Academic Press.

Kirchengast, G. (1999). A simple analytical atmospheric model for radio occultation applications. Institute of Meteorology and Geophysics, University of Graz.

Lonitz, K. (2023). GNSS radio occultation (GNSS-RO): Principles and NWP use. ECMWF. https://events.ecmwf.int/event/334/contributions/3890/attachments/2235/3952/01_gpsro_lecture_KL_2023.pdf

Luntama, J., Kirchengast, G., Borsche, M., Foelsche, U., Steiner, A., Healy, S., Von Engeln, A., O'Clerigh, E., & Marquardt, C. (2008). Prospects of the EPS GRAS Mission for operational atmospheric applications. Bulletin of the American Meteorological Society, 89(12), 1863–1876. https://doi.org/10.1175/2008bamS-2399.1

Lutgens, F. K., Tarbuck, E. J., & Tasa, D. G. (2013). The atmosphere: An introduction to meteorology (12th ed.). Pearson.

NCEI-NOAA. (2018, 8 Februari). Integrated global radiosonde archive. Diakses 1 Juni, 2021, dari https://www.ncei.noaa.gov/products/weather-balloon/integrated-global-radiosonde-archive.

Noersomadi. (2019). Characteristics of tropical tropopause and stratospheric gravity waves analyzed using high resolution temperature profiles from GNSS radio occultation [Disertasi tidak diterbitkan]. Kyoto University.

Reigber, C., Luhr, H., & Schwintzer, P. (Ed.). (2012). First CHAMP mission results for gravity, magnetic and atmospheric studies. Springer Science & Business Media.

Rother, M., & Michaelis, I. (2019). CH-ME-3-MAG-CHAMP 1 Hz combined magnetic field time series (level 3). GFZ Data Services. https://doi.org/10.5880/GFZ.2.3.2019.004

Aldrian, E. (2016). Sistem peringatan dini menghadapi iklim ekstrem. Jurnal Sumberdaya Lahan, 10(2), 79–90.

BPS. (2018). Statistik Indonesia 2018. Badan Pusat Statistik.

Davis, A. M. (1993). Software requirements: objects, functions, and states. Prentice-Hall, Inc.

Döllner, J. (2020). Geospatial artificial intelligence: Potentials of machine learning for 3D point clouds and geospatial digital twins. PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science, 88(1), 15–24. https://doi.org/10.1007/s41064-020-00102-3

Garrett, K. A., Dendy, S. P., Frank, E. E., Rouse, M. N., & Travers, S. E. (2006). Climate change effects on plant disease: genomes to ecosystems. Annu. Rev. Phytopathol., 44(1), 489–509.

Hofmann, H. F., & Lehner, F. (2001). Requirements engineering as a success factor in software projects. IEEE software, 18(4), 58.

Jeger, M. J., & Pautasso, M. (2008). Plant disease and global change: The importance of long-term data sets. New Phytologist, 177(1), 8–11.

Kemper, H. (2022). Development of a drought early warning system based on the prediction of agricultural productivity: A data science approach. GI_Forum, 1, 58–76. https://doi.org/10.1553/giscience2022_01_s58

Khan, M. E. (2010). Different forms of software testing techniques for finding errors. International Journal of Computer Science Issues (IJCSI), 7(3), 24.

Laksono, S. S., & Nurgiyatna, N. (2020). Sistem pengukur curah hujan sebagai deteksi dini kekeringan pada pertanian berbasis internet of things (IoT). Emitor: Jurnal Teknik Elektro, 20(2), 117–121.

Leffingwell, D. (1997). Calculating the return on investment from more effective requirements management. American Programmer, 10(4), 13–16.

McCall, J. A., Richards, P. K., & Walters, G. F. (1977). Factors in software quality: Volume I. Concepts and definitions of software quality. General Electric Company.

Moisa, M. B., Gabissa, B. T., Hinkosa, L. B., Dejene, I. N., & Gemeda, D. O. (2022). Analysis of land surface temperature using Geospatial technologies in Gida Kiremu, Limu, and Amuru District, Western Ethiopia. Artificial Intelligence in Agriculture, 6, 90–99. https://doi.org/10.1016/j.aiia.2022.06.002

Mubyarto. (1983). Politik pertanian dan pembangunan pedesaan. Sinarharapan.

Natividad, J. G., & Mendez, J. M. (2018). Flood monitoring and early warning system using ultrasonic sensor. Dalam IOP conference series: Materials science and engineering (Vol. 325, Article 012020). https://doi.org/10.1088/1757-899x/325/1/012020

Nduru, S., Al Hafiz, A., & Pane, D. H. (2022). Implementasi metode fuzzy berbasis internet of things (IoT) untuk peringatan dini banjir. Jurnal Sistem Komputer Triguna Dharma (JURSIK TGD), 1(1), 26–33.

Nidhra, S., & Dondeti, J. (2012). Black box and white box testing techniques-a literature review. International Journal of Embedded Systems and Applications (IJESA), 2(2), 29–50.

Nurdin, S. P., & Si, M. (2011). Antisipasi perubahan iklim untuk keberlanjutan ketahanan pangan. Jurnal Dialog Kebijakan Publik, 4, 21–31.

Pramudia, A., & Y. Hilman, Y. (2017). Hubungan keragaan luas tanam bawang merah dengan pola curah hujan di sentra produksi bawang merah. Dalam Prosiding seminar nasional adaptasi dan mitigasi perubahan iklim (717–730). Balai Besar Penelitian dan Pengembangan Sumber daya Lahan Pertanian.

Pramudia, A., & Puspitasari. (2017). Karakteristik pola tanam di beberapa sentra produksi sebagai dasar penyusunan kalender tanam bawang merah. Dalam Prosiding seminar nasional adaptasi dan mitigasi perubahan iklim (211–220). Balai Besar Penelitian dan Pengembangan Sumberdaya Lahan Pertanian.

Pramudia, A., Riatma, D. L., Sunusi, M. A., Ripaldi, A., Susanti, E., & Fanggidae, Y. R. (2024). Modeling of climate parameters with planting area and pest attacked area on shallots for the development of early warning systems and horticultural cropping schedules. Dalam IOP conference series: Earth and environmental science (Vol. 1314, Article 012023). IOP Publishing.

Prasetyaningtyas, K. (2021, 30 Agustus). Prakiraan musim hujan 2021/2022 di Indonesia. BMKG. https://www.bmkg.go.id/berita/?p=prakiraan-musim-hujan-tahun-2021-2022-di-indonesia&lang=ID&s=detil

Pressman, R. S. (2010). Rekayasa perangkat lunak. Andi.

Raharjana, I. K., Siahaan, D., & Fatichah, C. (2019, Juli). User story extraction from online news for software requirements elicitation: A conceptual model. Dalam 2019 16th international joint conference on computer science and software engineering (JCSSE) (342–347). IEEE.

Rosyadi, I. (2013). Analisis dan perancangan sistem informasi persediaan barang dengan menggunakan metode FAST pada CV. Tri Jaya [Doctoral dissertation]. Universitas Brawijaya.

Sarmidi, & Rahmat, S. I. (2019). Sistem peringatan dini banjir menggunakan sensor ultrasonik berbasis Arduino Uno. Jurnal Manajemen dan Teknik Informatika JUMANTAKA, 03(1), 31–41. http://jurnal.stmik-dci.ac.id/index.php/jumantaka/

Siahaan, D. (2012). Analisis kebutuhan dalam rekayasa perangkat lunak. Andi Offset .

Siahaan, D., & Umami, I. (2012). Natural language processing for detecting forward reference in a document. IPTEK The Journal for Technology and Science, 23(4).

Sigvald, R. (2012). Risk assessments for pests and diseases of field crops, especially forecasting and warning systems. Reducing the Risks Associated with the Use of Plant Protection Products no 25. Sust. Agric, 1500, 185–201.

Sommerville, I. (2003). Software engineering (rekayasa perangkat lunak) (Jilid 2). Erlangga.

Song, Y., Kalacska, M., Gasparovic, M., Yao, J., & Najibi, N. (2023). Advances in geocomputation and geospatial artificial intelligence (GeoAI) for mapping. International Journal of Applied Earth Observation and Geoinformation, 120, 103300. https://doi.org/10.1016/j.jag.2023.103300

Susanti, E., Surmaini, E., & Estiningtyas, W. (2018). Parameter iklim sebagai indikator peringatan dini serangan hama penyakit tanaman. Jurnal Sumberdaya Lahan, 12(1), 59–70.

Sutanto, S. J., Van Der Weert, M., Blauhut, V., & Van Lanen, H. A. J. (2020). Skill of large-scale seasonal drought impact forecasts. Natural Hazards and Earth System Sciences, 20(6), 1595–1608. https://doi.org/10.5194/nhess-20-1595-2020.

Syaikhuddin, M. M., Anam, C., Rinaldi, A. R., & Conoras, M. E. B. (2018). Conventional software testing using white box method. Kinetik: Game technology, information system, computer network, computing, electronics, and control, 5(1), 65–72.

Tim EWS SIPANTARA. (2023). Peringatan dini dampak perubahan iklim hortikultura, aplikasi EWS beri peringatan dini mengenai perubahan iklim. Ditjen Hortikultura. https://ewssipantara.id/

Anggono, T., Kusumadewi, S., & Utomo, P. (2018). A review of disaster early warning system in Indonesia. Journal of Physics: Conference Series, 1025(1), 012017.

Badriyah, N., Ismoyo, H. W., & Nurhayati, A. (2020). Assessment of farmers' perception and adaptation to climate change in rice farming. Journal of Physics: Conference Series, 1463(1), 012039

Balitbangda Lampung Barat. (2018). Kajian komoditas unggulan kecamatan se Kabupaten Lampung Barat. Badan Penelitian dan Pengembangan Daerah Lampung Barat.

BMKG. (2015). Early warning system: strategy and plan of action for disaster risk reduction in Indonesia.

BNPB. (2018). National disaster risk reduction strategy.

Dercon, G., Tittonell, P., Wijk, M. T. V., Klapwijk, C. J., Baltenweck, I., & Zingore, S. (2019). Conservation agriculture in the Colombian Andes: Long-term effects on soil carbon stocks and crop yields. Agriculture, Ecosystems & Environment, 279, 111–121. https://doi.org/10.1016/j.agee.2019.04.027

Derpsch, R., Friedrich, T., Kassam, A., & Li, H. (2010). Current status of adoption of no-till farming in the world and some of its main benefits. International Journal of Agricultural and Biological Engineering, 3(1), 1-25.

Farooq, M., & Siddique, K. (2015). Conservation agriculture: Concepts, brief history, and impacts on agricultural systems. Dalam M. Farooq & K. Siddique (Ed.), Conservation agriculture (1–17). Springer.

Fitriani, R. A., Putri, A. S., & Yusuf, M. (2018). Early warning system for flash flood in Indonesia. Dalam IOP conference series: Earth and environmental science (Vol. 175, Artikel 012088). IOP Publishing.

Govaerts, B., Verhulst, N., Castellanos-Navarrete, A., Sayre, K. D., Dixon, J., & Dendooven, L. (2009). Conservation agriculture and soil carbon sequestration: Between myth and farmer reality. Critical Reviews in Plant Sciences, 28(2), 97–122.

Hairiah, K., Dewi, S., Agus, F., Velarde, S. J., & Ekadinata, A. (2010). Agroforestry for sustainable land-use: Fundamental research and its implementation in Indonesia. Agroforestry Systems, 80(2), 259–268.

Hobbs, P. R., Sayre, K., & Gupta, R. (2008). The role of conservation agriculture in sustainable agriculture. Philosophical Transactions of the Royal Society B: Biological Sciences, 363(1491), 543–555.

International Federation of Red Cross and Red Crescent Societies (IFRC). (2019). Community-based disaster risk reduction in Indonesia. IFRC.

Jovarauskas, D., Steponavicius, D., Kemzuraite, A., Zinkevicius, R., & Venslauskas, K. (2021). Comparative analysis of the environmental impact of conventional and precision spring wheat fertilization under various meteorological conditions. Journal of Environmental Management, 296, 113150.

June, T., & Sarvina, Y. (2023). Strategi mempertahankan produksi pertanian dalam menghadapi perubahan iklim pertanian cerdas iklim. IPB Press.

Lipper, L., Thornton, P., Campbell, B. M., Baedeker, T., Braimoh, A., Bwalya, M., Caron, P., Cattaneo, A., Garrity, D. P., Henry, K., Hottle, R., Jackson, L., Jarvis, A., Kossam, F., Mann, W., McCarthy, N., Meybeck, A., Neufeldt, H., Remington, T., . . . Torquebiau, E. (2014). Climate-smart agriculture for food security. Nature Climate Change, 4(12), 1068–1072. https://doi.org/10.1038/nclimate2437

Mardiastuti, A., & Nurrochmat, D. R. (2019). Agroforestry systems in Indonesia: a review of current status and future prospects. Biodiversitas Journal of Biological Diversity, 20(3), 656–673.

Mary, G. S., Sugumaran, P., Niveditha, S., Ramalakshmi, B., Ravichandran, P., & Seshadri, S. (2016). Production, characterization and evaluation of biochar from pod (Pisum sativum), leaf (Brassica oleracea) and peel (Citrus sinensis) wastes. International Journal of Recycling of Organic Waste in Agriculture, 5(1), 43–53. https://doi.org/10.1007/s40093-016-0116-8

Ministry of Agriculture. (2017). National agriculture disaster risk reduction and management plan. Ministry of Agriculture.

OECD. (2018). Agriculture and climate change. Diakses pada 28 Maret, 2023, dari https://www.oecd.org/greengrowth/sustainable-agriculture/agriculture-and-climate-change.htm

Pariwono, E., Kusuma, A., & Kuntjoro, T. (2018). Raising awareness on climate change among rice farmers in Indonesia. Dalam IOP conference series: Earth and environmental science (Vol. 125, Artikel 012056). IOP Publishing.

Paustian, K., Lehmann, J., Ogle, S., Reay, D., Robertson, G. P., & Smith, P. (2016). Climate-smart soils. Nature, 532(7597), 49–57. https://doi.org/10.1038/nature17174

Quintarelli, V., Radicetti, E., Allevato, E., Stazi, S. R., Haider, G., Abideen, Z., Bibi, S., Jamal, A., & Mancinelli, R. (2022). Cover crops for sustainable cropping systems: A review. Agriculture, 12(12), 2076. https://doi.org/10.3390/agriculture12122076

Roshetko, J. M., Purnomosidhi, P., & Pramono, A. A. (2014). Indonesian agroforestry: tree gardens for sustainable livelihoods. Small-scale Forestry, 13(3), 287–301.

Sarvina, Y., June, T., Sutjahjo, S. H., Nurmalina, R., & Surmaini, E. (2022). Pengembangan sistem pertanian berkelanjutan berbasis climate smart agriculture [Disertasi]. Institut Pertanian Bogor.

Sarvina, Y., June, T., Sutjahjo, S. H., Nurmalina, R., & Surmaini, E. (2022). Climatic suitability for robusta coffee in West Lampung under climate change. Dalam IOP conference series: Earth and environmental science (Vol. 950, Article 012015). IOP Publishing. https://doi.org/10.1088/1755-1315/950/1/012019

Sarvina, Y., June, T., Sutjahjo, S. H., Nurmalina, R., & Surmaini, E. (2021). The impacts of climate variability on coffee yield in five indonesian coffee production centers. Coffee Science, 16. https://doi.org/10.25186/.v16i.1917

Settle, W. H., Ariawan, H., Astuti, E. T., Cahyana, W., Hakim, A. L., Hindayana, D., Lestari, A. S., & Pajarningsih. (1996). Managing tropical rice pests through conservation of generalist natural enemies and alternative prey. Ecology, 77(7), 1975–1988.

Stella Mary, G., Sugumaran, P., Niveditha, S., Ramalakshmi, B., Ravichandran, P., & Seshadri, S. (2016). Production, characterization, and evaluation of biochar from pod (Pisum sativum), leaf (Brassica oleracea), and peel (Citrus sinensis) wastes. International Journal of Recycling of Organic Waste in Agriculture, 5, 43–53. https://doi.org/10.1007/s40093-016-0116-8

Suryadi, F. X., & Marwati, S. (2019). Adaptation strategies of agricultural sector towards climate change: Case study of paddy farming in Central Java, Indonesia. Journal of Physics: Conference Series, 1294(1), 012097.

UNDP. (2018). Building resilience to natural disasters in Indonesia.

UNEP. (2018). New analysis outlines climate change adaptation strategies Indonesia. Diakses pada 28 Maret, 2023, dari https://www.unep.org/gan/news/editorial/new-analysis-outlines-climate-change-adaptation-strategies-indonesia

UNFCCC. (2022). Enhanced nationally determined contribution Republic of Indonesia. https://unfccc.int/sites/default/files/NDC/2022-09/23.09.2022_Enhanced%20NDC%20Indonesia.pdf

Uphoff, N. (Ed.). (2015). Conservation agriculture in rice-based systems: Examples from practice in Southeast Asia. World Scientific Publishing.

Utaminingsih, W., & Hidayah, S. (2012). Mitigasi emisi gas rumah kaca melalui penerapan irigasi intermittent di lahan sawah beririgasi. Jurnal Irigasi, 7(2), 132–141.

Verhulst, N., Govaerts, B., Verachtert, E., Castellanos-Navarrete, A., Mezzalama, M., Wall, P. C., Chocobar, A., Deckers, J., & Sayre, K. D. (2014). Conservation agriculture, improving soil quality for sustainable production systems. Dalam R. Lal & B. A. Stewart (Ed.), Advances in soil science: Food security and soil quality (137–208). CRC Press.

Wardhana, M. G., Wijayanto, A., & Pujianto. (2019). Disaster early warning system in Indonesia. International Journal of Disaster Risk Reduction, 36, 101078.

Zhang, X., Sun, H., Xia, X., Yang, Z., & Zhu, S. (2024). Can a crop rotation and fallow system reduce the carbon emission intensity of agriculture? Land, 13(3), 293. https://doi.org/10.3390/land13030293.

Abbas, A., Waseem, M., Ahmad, R., khan, K. A., Zhao, C., & Zhu, J. (2022). Sensitivity analysis of greenhouse gas emissions at farm level: case study of grain and cash crops. Environmental Science and Pollution Research, 29(54), 82559–82573. https://doi.org/10.1007/S-11356-022-21560-9/FIGURES/1

ADB. (2023, Oktober 18). How can we incentivize reducing methane emission in rice farming in Asia? Asian Development Bank. https://www.adb.org/news/events/how-can-we-incentivize-reducing-methane-emission-rice-farming-asia

Adhya, T. K., Linquist, B., Searchinger, Reiner Wassmann, T., & Yan, X. (2014). Wetting and drying: Reducing greenhouse gas emissions and saving water from rice production. World Resources Institute. https://www.wri.org/research/wetting-and-drying-reducing-greenhouse-gas-emissions-and-saving-water-rice-production

Ahmed, M., Fayyaz-ul-Hassan, & Ahmad, S. (2017). Climate variability impact on rice production: Adaptation and mitigation strategies. Dalam Quantification of climate variability, adaptation and mitigation for agricultural sustainability (91–111). Springer. https://doi.org/10.1007/978-3-319-32059-5_5

Alam, T., Suryanto, P., Supriyanta, Basunanda, P., Wulandari, R. A., Kastono, D., Widyawan, M. H., Nurmansyah, & Taryono. (2021). Rice cultivar selection in an agroforestry system through GGE-biplot and EBLUP. Biodiversitas Journal of Biological Diversity, 22(11), 4750–4757. https://doi.org/10.13057/BIODIV/D221106

Ansari, A., Pranesti, A., Telaumbanua, M., Alam, T., Taryono, Wulandari, R. A., Nugroho, B. D. A., & Supriyanta. (2023). Evaluating the effect of climate change on rice production in Indonesia using multimodelling approach. Heliyon, 9(9), e19639. https://doi.org/10.1016/J.HELIYON.2023.E19639

Ansari, A., Wuryandani, S., Pranesti, A., Telaumbanua, M., Ngadisih, N., Hardiansyah, M. Y., Alam, T., Supriyanta, N., Martini, T., & Taryono, N. (2023). Optimizing water-energy-food nexus: achieving economic prosperity and environmental sustainability in agriculture. Frontiers in Sustainable Food Systems, 7. https://doi.org/10.3389/fsufs.2023.1207197

Aparicio, J. D., Raimondo, E. E., Saez, J. M., Costa-Gutierrez, S. B., Álvarez, A., Benimeli, C. S., & Polti, M. A. (2022). The current approach to soil remediation: A review of physicochemical and biological technologies, and the potential of their strategic combination. Journal of Environmental Chemical Engineering, 10(2), 107141. https://doi.org/10.1016/J.JECE.2022.107141

Brust, G. E. (2019). Management strategies for organic vegetable fertility. Dalam Safety and practice for organic food (193–212). Academic Press. https://doi.org/10.1016/B978-0-12-812060-6.00009-X

Burak, S., & Margat, J. (2016). Water management in the Mediterranean region: Concepts and policies. Water Resources Management, 30(15), 5779–5797. https://doi.org/10.1007/S-11269-016-1389-4/TABLES/5

Chakravarty, K. H., Sadi, M., Chakravarty, H., Alsagri, A. S., Howard, T. J., & Arabkoohsar, A. (2022). A review on integration of renewable energy processes in vapor absorption chiller for sustainable cooling. Sustainable Energy Technologies and Assessments, 50, 101822. https://doi.org/10.1016/j.seta.2021.101822

Chu, G., Wang, Z., Zhang, H., Liu, L., Yang, J., & Zhang, J. (2015). Alternate wetting and moderate drying increases rice yield and reduces methane emission in paddy field with wheat straw residue incorporation. Food and Energy Security, 4(3), 238–254. https://doi.org/10.1002/FES-3.66

dos Santos Cordeiro, C. F., Rodrigues, D. R., da Silva, G. F., Echer, F. R., & Calonego, J. C. (2022). Soil organic carbon stock is improved by cover crops in a tropical sandy soil. Agronomy Journal, 114(2), 1546–1556. https://doi.org/10.1002/AGJ2.21019

Datta, A., Ullah, H., & Ferdous, Z. (2017). Water management in rice. Rice Production Worldwide, 255–277. https://doi.org/10.1007/978-3-319-47516-5_11/COVER

EPA. (2021). Inventory of U.S. greenhouse gas emissions and sinks. https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks

Fan, Y., Tian, Z., Wang, K., & Fan, D. (2021). Simulation of water saving and methane mitigation potential of paddy fields under alternate wetting and drying irrigation regime in China. Dalam 2021 9th international conference on agro-geoinformatics (AGRO-GEOINFORMATICS 2021). https://doi.org/10.1109/AGRO-GEOINFORMATICS50104.2021.9530342

FAOSTAT. (2023). Climate change: Agrifood systems emissions - Emissions totals. Food and Agriculture Organization of the United Nations. https://www.fao.org/faostat/en/#compare

Guo, Y., Zhang, G., Abdalla, M., Kuhnert, M., Bao, H., Xu, H., Ma, J., Begum, K., & Smith, P. (2023). Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models. Geoderma, 431. https://doi.org/10.1016/J.GEODERMA.2023.116364

Helmi, H., Zakaria, S., Efendi, Munawar, A. A., & Aulia, R. (2021). Effect of irrigation methods and testing some rice cultivars against growth, root development and yield on rainfed Ultisols of Aceh Besar. Dalam IOP conference series: Earth and environmental science (Vol. 922, Article 012044). IOP Publishing. https://doi.org/10.1088/1755-1315/922/1/012044

Heredia, M. C., Kant, J., Prodhan, M. A., Dixit, S., & Wissuwa, M. (2021). Breeding rice for a changing climate by improving adaptations to water saving technologies. Theoretical and Applied Genetics 2021 135:1, 135(1), 17–33. https://doi.org/10.1007/S00122-021-03899-8

Hussain, S., Huang, J., Huang, J., Ahmad, S., Nanda, S., Anwar, S., Shakoor, A., Zhu, C., Zhu, L., Cao, X., Jin, Q., & Zhang, J. (2020). Rice production under climate change: Adaptations and mitigating strategies. Dalam Environment, climate, plant and vegetation growth (659–686). Springer. https://doi.org/10.1007/978-3-030-49732-3_26/COVER

Ishfaq, M., Farooq, M., Zulfiqar, U., Hussain, S., Akbar, N., Nawaz, A., & Anjum, S. A. (2020). Alternate wetting and drying: A water-saving and ecofriendly rice production system. Agricultural Water Management, 241, 106363. https://doi.org/10.1016/J.AGWAT.2020.106363

Islam, S. M. M., Gaihre, Y. K., Islam, M. R., Ahmed, M. N., Akter, M., Singh, U., & Sander, B. O. (2022). Mitigating greenhouse gas emissions from irrigated rice cultivation through improved fertilizer and water management. Journal of Environmental Management, 307, 114520. https://doi.org/10.1016/J.JENVMAN.2022.114520

Jabran, K., & Chauhan, B. S. (2015). Weed management in aerobic rice systems. Crop Protection, 78, 151–163. https://doi.org/10.1016/J.CROPRO.2015.09.005

Javed, M. S., Ma, T., Jurasz, J., & Amin, M. Y. (2020). Solar and wind power generation systems with pumped hydro storage: Review and future perspectives. Renewable Energy, 148, 176–192. https://doi.org/10.1016/J.RENENE.2019.11.157

Jiang, M., Xu, P., Wu, L., Zhao, J., Wu, H., Lin, S., Yang, T., Tu, J., & Hu, R. (2022). Methane emission, methanogenic and methanotrophic communities during rice-growing seasons differ in diversified rice rotation systems. Science of The Total Environment, 842, 156781. https://doi.org/10.1016/J.SCITOTENV.2022.156781

Kumar, A., Basu, S., Ramegowda, V., & Pereira, A. (2016). Mechanisms of drought tolerance in rice . Dalam T. Sasaki (Ed.), Achieving sustainable cultivation of rice (Vol. 1, 153–186). Burleigh Dodds Science Publishing. https://doi.org/10.4324/9781351114189-9

Lampayan, R. M., Rejesus, R. M., Singleton, G. R., & Bouman, B. A. M. (2015). Adoption and economics of alternate wetting and drying water management for irrigated lowland rice. Field Crops Research, 170, 95–108. https://doi.org/10.1016/J.FCR.2014.10.013

Lan, X., Thoning, K. W., & Dlugokencky, E. J. (2022). Trends in globally averaged CH4, N2O, and SF6. NOAA Global Monitoring Laboratory. https://doi.org/10.15138/P8XG-AA10

Lin, Y.-P., Ansari, A., Ngoc-Dan Cao, T., Shiau, Y.-J., Lur, H.-S., Muzaffar, A., Wunderlich, R. F., & Mukhtar, H. (2022). Using inhibitors to trade greenhouse gas emission for ammonia losses in paddy soil: A zero-sum game. Environmental Technology & Innovation, 28, 102547. https://doi.org/10.1016/j.eti.2022.102547

Linquist, B. A., Anders, M. M., Adviento-Borbe, M. A. A., Chaney, R. L., Nalley, L. L., da Rosa, E. F. F., & van Kessel, C. (2015). Reducing greenhouse gas emissions, water use, and grain arsenic levels in rice systems. Global Change Biology, 21(1), 407–417. https://doi.org/10.1111/GCB.12701

Luo, D., Yu, H., Li, Y., Yu, Y., Chapman, S. J., & Yao, H. (2023). A joint role of iron oxide and temperature for methane production and methanogenic community in paddy soils. Geoderma, 433, 116462. https://doi.org/10.1016/J.GEODERMA.2023.116462

Maharjan, G. R., Prescher, A. K., Nendel, C., Ewert, F., Mboh, C. M., Gaiser, T., & Seidel, S. J. (2018). Approaches to model the impact of tillage implements on soil physical and nutrient properties in different agro-ecosystem models. Soil and Tillage Research, 180, 210–221. https://doi.org/10.1016/J.STILL.2018.03.009

Maneepitak, S., Ullah, H., Datta, A., Shrestha, R. P., Shrestha, S., & Kachenchart, B. (2019). Effects of water and rice straw management practices on water savings and greenhouse gas emissions from a double-rice paddy field in the Central Plain of Thailand. European Journal of Agronomy, 107, 18–29. https://doi.org/10.1016/J.EJA.2019.04.002

Maneepitak, S., Ullah, H., Paothong, K., Kachenchart, B., Datta, A., & Shrestha, R. P. (2019). Effect of water and rice straw management practices on yield and water productivity of irrigated lowland rice in the Central Plain of Thailand. Agricultural Water Management, 211, 89–97. https://doi.org/10.1016/J.AGWAT.2018.09.041

Marpaung, I. S., Sipahutar, T., Siagian, D. R., & P., T. (2021). Teknologi tanaman padi sistem tanam benih langsung dengan hambur di dataran tinggi Sumatera Utara (studi kasus di Kabupaten Humbang Hasundutan). Proceedings Series on Physical & Formal Sciences, 2, 344–351. https://doi.org/10.30595/PSPFS.V2I.209

Matthews, R. B., Wassmann, R., & Arah, J. (2000). Using a crop/soil simulation model and GIS techniques to assess methane emissions from rice fields in asia. I. Model development. Nutrient Cycling in Agroecosystems, 58(1–3), 141–159. https://doi.org/10.1023/A:1009894619446/METRICS

Mehra, P., Baker, J., Sojka, R. E., Bolan, N., Desbiolles, J., Kirkham, M. B., Ross, C., & Gupta, R. (2018). A review of tillage practices and their potential to impact the soil carbon dynamics. Advances in Agronomy, 150, 185–230. https://doi.org/10.1016/BS.AGRON.2018.03.002

Mukhtar, H., Wunderlich, R. F., Muzaffar, A., Ansari, A., Shipin, O. V., Cao, T. N.-D., & Lin, Y.-P. (2023). Soil microbiome feedback to climate change and options for mitigation. Science of The Total Environment, 882, 163412. https://doi.org/10.1016/j.scitotenv.2023.163412

Mulyani, A., Nursyamsi, D., & Syakir, M. (2017). Strategi pemanfaatan sumberdaya lahan untuk pencapaian swasembada beras berkelanjutan. Jurnal Sumberdaya Lahan, 11(1), 223337. https://doi.org/10.2018/JSDL.V11I1.8187

Netafim. (2023). Increase rice yield using drip irrigation. https://www.netafimindia.com/crop-knowledge/rice/

Nugroho, K., Slamet, S., & Lestari, P. (2017). Keragaman genetik 24 varietas padi sawah dan padi gogo (Oryza sativa L.) Indonesia berdasarkan marka SSR. Scripta Biologica, 4(1), 5–10. https://doi.org/10.20884/1.SB.2017.4.1.350

Pandey, V., & Shukla, A. (2015). Acclimation and tolerance strategies of rice under drought stress. Rice Science, 22(4), 147–161. https://doi.org/10.1016/J.RSCI.2015.04.001

Panuju, D. R., Mizuno, K., & Trisasongko, B. H. (2013). The dynamics of rice production in Indonesia 1961–2009. Journal of the Saudi Society of Agricultural Sciences, 12(1), 27–37. https://doi.org/10.1016/J.JSSAS.2012.05.002

Peyron, M., Bertora, C., Pelissetti, S., Said-Pullicino, D., Celi, L., Miniotti, E., Romani, M., & Sacco, D. (2016). Greenhouse gas emissions as affected by different water management practices in temperate rice paddies. Agriculture, Ecosystems & Environment, 232, 17–28. https://doi.org/10.1016/J.AGEE.2016.07.021

Piepho, H. P., Nazir, M. F., Qamar, M., Rattu, A. U. R., Riaz-Ud-Din, Hussain, M., Ahmad, G., Fazal-E-Subhan, Ahmad, J., Abdullah, Laghari, K. B., Vistro, I. A., Sharif Kakar, M., Sial, M. A., & Imtiaz, M. (2016). Stability analysis for a countrywide series of wheat trials in Pakistan. Crop Science, 56(5), 2465–2475. https://doi.org/10.2135/CROPSCI2015.12.0743

Pratiwi, E. P. A., & Shinogi, Y. (2016). Rice husk biochar application to paddy soil and its effects on soil physical properties, plant growth, and methane emission. Paddy and Water Environment, 14(4), 521–532. https://doi.org/10.1007/S-10333-015-0521-Z/FIGURES/9

Pratiwi, E., Akhdiya, A., Purwani, J., Husnain, & Syakir, M. (2021). Impact of methane-utilizing bacteria on rice yield, inorganic fertilizers efficiency and methane emissions. Dalam IOP conference series: Earth and environmental science (Vol. 924, Article 012017). IOP Publishing. https://doi.org/10.1088/1755-1315/648/1/012137.

PuslitbangKPT. (2020, 27 Januari). Teknologi irigasi tetes (irigasi hemat air) [Video]. YouTube. https://www.youtube.com/watch?v=6iied70eK4c

Putranto, A. W. (2012). Optimasi potensi hasil berbagai varietas padi (Oryza sativa L.) melalui pengaturan populasi dan pemupukan nitrogen pada dua kondisi pengairan [Tesis]. Universitas Gadjah Mada. https://etd.repository.ugm.ac.id/penelitian/detail/56491

Ramachandran, V., Ramalakshmi, R., Kavin, B. P., Hussain, I., Almaliki, A. H., Almaliki, A. A., Elnaggar, A. Y., Hussein, E. E., Li, Z., Fan, Y., Augusto, C., Santos, G., Jin, J., Ramachandran, V., Ramalakshmi, R., Kavin, B. P., Hussain, I., Almaliki, A. H., Almaliki, A. A., … Hussein, E. E. (2022). Exploiting IoT and its enabled technologies for irrigation needs in agriculture. Water, 14(5), 719. https://doi.org/10.3390/W14050719

Ritung, S., Suryani, E., Subardja, D., Sukarman, Nugroho, K., Suparto, Hikmatullah, Mulyani, A., Tafakresnanto, C., Sulaeman, Y., Subandiono, R. E., Wahyunto, Ponidi, Prasodjo, N., Suryana, U., Hidayat, H., Priyono, A., & Supriatna, W. (2015). Sumber daya lahan pertanian Indonesia: Luas, penyebaran, dan potensi ketersediaan (E. Husen, F. Agus, & D. Nursyamsi, Ed.). IAARD Press. https://repository.pertanian.go.id/handle/123456789/20044

Sandhu, N., & Kumar, A. (2017). Bridging the rice yield gaps under drought: QTLs, genes, and their use in breeding programs. Agronomy, 7(2), 27. https://doi.org/10.3390/AGRONOMY7020027

Sapkota, A., Haghverdi, A., Avila, C. C. E., & Ying, S. C. (2020). Irrigation and greenhouse gas emissions: A review of field-based studies. Soil Systems, 4(2), 20. https://doi.org/10.3390/SOILSYSTEMS4020020

Setyanto, P., Pramono, A., Adriany, T. A., Susilawati, H. L., Tokida, T., Padre, A. T., & Minamikawa, K. (2018). Alternate wetting and drying reduces methane emission from a rice paddy in Central Java, Indonesia without yield loss. Soil Science and Plant Nutrition, 64(1), 23–30. https://doi.org/10.1080/00380768.2017.1409600

Sharma, S. K., Singh, Y. V., Tyagi, S., & Bhatia, A. (2016). Influence of rice varieties, nitrogen management and planting methods on methane emission and water productivity. Paddy and Water Environment, 14(2), 325–333. https://doi.org/10.1007/S-10333-015-0502-2/TABLES/4

Singh, S. (2021). Energy crisis and climate change. Dalam Energy: Crises, challenges and solutions (1–17). John Wiley & Sons, Ltd. https://doi.org/10.1002/9781119741503.CH1

Subrata, B. A. G., Yudono, P., Waluyo, S., & Putra, E. T. S. (2016). Pengaruh proporsi populasi padi gogo dan kacang hijau dalam tumpangsari terhadap hasil dan komposisi gulma di lahan pasir pantai [Tesis]. Universitas Gadjah Mada. https://etd.repository.ugm.ac.id/penelitian/detail/103173

Surendran, U., Raja, P., Jayakumar, M., & Subramoniam, S. R. (2021). Use of efficient water saving techniques for production of rice in India under climate change scenario: A critical review. Journal of Cleaner Production, 309, 127272. https://doi.org/10.1016/J.JCLEPRO.2021.127272

Suryanto, P., Kurniasih, B., Faridah, E., Nurjanto, H. H., Rogomulyo, R., Handayani, S., Kastono, D., Muttaqien, A. S., & Alam, T. (2020). Influence of furrow with organic material and Chromolaena odorata compost on upland rice productivity in an agroforestry system with Melaleuca cajuputi. Biodiversitas Journal of Biological Diversity, 21(2), 780–791. https://doi.org/10.13057/BIODIV/D210246

Susilawati, H. L., Setyanto, P., Kartikawati, R., & Sutriadi, M. T. (2019). The opportunity of direct seeding to mitigate greenhouse gas emission from paddy rice field. Dalam IOP conference series: Earth and environmental science (Vol. 393, Artikel 012042). IOP Publishing. https://doi.org/10.1088/1755-1315/393/1/012042.

Tao, Y., Zhang, Y., Jin, X., Saiz, G., Jing, R., Guo, L., Liu, M., Shi, J., Zuo, Q., Tao, H., Butterbach-Bahl, K., Dittert, K., & Lin, S. (2015). More rice with less water – evaluation of yield and resource use efficiency in ground cover rice production system with transplanting. European Journal of Agronomy, 68, 13–21. https://doi.org/10.1016/J.EJA.2015.04.002

Toorn, S. a. D., Worrell, E., & Van Den Broek, M. (2021). How much can combinations of measures reduce methane and nitrous oxide emissions from European livestock husbandry and feed cultivation? Journal of Cleaner Production, 304, 127138. https://doi.org/10.1016/j.jclepro.2021.127138

Ullah, H., & Datta, A. (2018). Root system response of selected lowland Thai rice varieties as affected by cultivation method and potassium rate under alternate wetting and drying irrigation. Archives of Agronomy and Soil Science, 64(14), 2045–2059. https://doi.org/10.1080/03650340.2018.1476756

Verma, H., Borah, J. L., & Sarma, R. N. (2019). Variability assessment for root and drought tolerance traits and genetic diversity analysis of rice germplasm using SSR Markers. Scientific Reports, 9(1), 1–19. https://doi.org/10.1038/s41598-019-52884-1

Viandari, N. A., Adriany, T. A., & Pramono, A. (2020). Alternate wetting and drying system (AWD) combined with farmyard manure to increase rice yield and reduce methane emission and water use. Dalam IOP conference series: Materials science and engineering (Vol. 980, Artikel 012066). IOP Publishing. https://doi.org/10.1088/1757-899x/980/1/012066

Vishwakarma, P., & Dubey, S. K. (2020). Diversity of endophytic bacterial community inhabiting in tropical aerobic rice under aerobic and flooded condition. Archives of Microbiology, 202(1), 17–29. https://doi.org/10.1007/S00203-019-01715-Y/FIGURES/6

Wang, H., Zhang, Y., Zhang, Y., McDaniel, M. D., Sun, L., Su, W., Fan, X., Liu, S., & Xiao, X. (2020). Water-saving irrigation is a ‘win-win’ management strategy in rice paddies – With both reduced greenhouse gas emissions and enhanced water use efficiency. Agricultural Water Management, 228, 105889. https://doi.org/10.1016/J.AGWAT.2019.105889

Wijaya, S. (2019). Indonesian food culture mapping: A starter contribution to promote Indonesian culinary tourism. Journal of Ethnic Foods, 6(1), 1–10. https://doi.org/10.1186/S42779-019-0009-3/TABLES/1

Xu, Y., Ge, J., Tian, S., Li, S., Nguy-Robertson, A. L., Zhan, M., & Cao, C. (2015). Effects of water-saving irrigation practices and drought resistant rice variety on greenhouse gas emissions from a no-till paddy in the central lowlands of China. Science of The Total Environment, 505, 1043–1052. https://doi.org/10.1016/J.SCITOTENV.2014.10.073

Yang, Y., Jin, Z., Mueller, N. D., Driscoll, A. W., Hernandez, R. R., Grodsky, S. M., Sloat, L. L., Chester, M. V., Zhu, Y. G., & Lobell, D. B. (2023). Sustainable irrigation and climate feedbacks. Nature Food, 4(8), 654–663. https://doi.org/10.1038/s43016-023-00821-x

Zhuang, Y., Zhang, L., Li, S., Liu, H., Zhai, L., Zhou, F., Ye, Y., Ruan, S., & Wen, W. (2019). Effects and potential of water-saving irrigation for rice production in China. Agricultural Water Management, 217, 374–382. https://doi.org/10.1016/J.AGWAT.2019.03.010

Apriyana, Y., Aldrian, E., & Koesmaryono, Y. (2019, November). The dynamics of rice cropping calendar and its relation with the ENSO (El Niño-Southern Oscillation) and IOD (Indian Ocean Dipole) in Monsoon and Equatorial Regions of Indonesia. Dalam IOP conference series: Earth and environmental science (Vol. 363, No. 1, Artikel 012013). IOP Publishing.

Boer, R., & Surmaini, E. (2020). Economic benefits of ENSO information in crop management decisions: case study of rice farming in West Java, Indonesia. Theoretical and Applied Climatology, 139(4), 1435–1446. https://doi.org/10.1007/s00704-019-03055-9

Cai, W., Santoso, A., Collins, M., Dewitte, B., Karamperidou, C., Kug, J.-S., Lengaigne, M., McPhaden, M. J., Stuecker, M. F., Taschetto, A. S., Timmermann, A., Wu, L., Yeh, S.-W., Wang, G., Ng, B., Jia, F., Yang, Y., Ying, J., Zheng, X.-T., Bayr, T. ... Zhong, W. (2021). Changing El Niño–Southern oscillation in a warming climate. Nature Reviews Earth & Environment, 2(9), 628–644.

Cao, J., Zhang, Z., Tao, F., Chen, Y., Luo, X., & Xie, J. (2023). Forecasting global crop yields based on El Niño Southern Oscillation early signals. Agricultural Systems, 205, 103564.

Change, I. C. (2013). The Physical Science Basis.

Iizumi, T., Luo, J. J., Challinor, A. J., Sakurai, G., Yokozawa, M., Sakuma, H., Brown, M. E., & Yamagata, T. (2014). Impacts of El Niño Southern Oscillation on the global yields of major crops. Nature communications, 5(1), 3712.

Lesk, C., Rowhani, P., & Ramankutty, N. (2016). Influence of extreme weather disasters on global crop production. Nature, 529, 84–87 https://doi.org/10.1038/nature16467.

Malau, L. R. E., Ulya, N. A., Anjani, R., & Rahmat, M. (2021, October). Study of ENSO impact on agricultural food crops price as basic knowledge to improve community resilience in climate change. Dalam IOP conference series: Earth and environmental science (Vol. 874, No. 1, Artikel 012008). IOP Publishing.

FAO. (2021). The impact of disasters and crises on agriculture and food security: 2021. https://doi.org/10.4060/cb3673en

Sekhar, C. S. C. (2018). Climate change and rice economy in Asia: Implications for trade policy. Dalam The state of agricultural commodity markets (SOCO) (Vol. 2018). FAO.

Wilhelmsen, H., Ladstädter, F., Scherllin-Pirscher, B., & Steiner, A. K. (2018). Atmospheric QBO and ENSO indices with high vertical resolution from GNSS radio occultation temperature measurements. Atmospheric Measurement Techniques, 11(3), 1333–1346.

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