{"id":23233,"date":"2025-05-25T13:30:08","date_gmt":"2025-05-25T06:30:08","guid":{"rendered":"https:\/\/samawa-university.ac.id\/?p=23233"},"modified":"2025-05-28T10:24:23","modified_gmt":"2025-05-28T03:24:23","slug":"dosen-universitas-samawa-memenangkan-hibah-kompetitif-nasional-program-penelitian-kementerian-pendidikan-tinggi-sains-dan-teknologi-tahun-2025-skema-pdp-4","status":"publish","type":"post","link":"https:\/\/samawa-university.ac.id\/?p=23233","title":{"rendered":"Dosen Universitas samawa Memenangkan Hibah Kompetitif Nasional, Program Penelitian Kementerian Pendidikan Tinggi, Sains, dan Teknologi Tahun 2025, Skema PDP. Dengan Judul Pemodelan Prediksi Curah Hujan Menggunakan Deep Learning Berbasis Data Satelit untuk Mitigasi Bencana Banjir dan Kekeringan di Kabupaten Sumbawa"},"content":{"rendered":"

\"\"<\/p>\n

UNSANEWS, Sumbawa Besar – Tim yang diketuai oleh Romi Aprianto, M.Sc. dengan anggota Dr. Armansyah Putera,M.Pd. meneliti terkait Pemodelan Prediksi Curah Hujan Menggunakan Deep Learning<\/em> Berbasis Data Satelit untuk Mitigasi Bencana Banjir dan Kekeringan di Kabupaten Sumbawa.<\/p>\n

Wilayah Sumbawa merupakan daerah yang sering mengalami bencana hidrometeorologi, khususnya banjir dan kekeringan. Sistem prediksi curah hujan yang ada masih mengandalkan metode konvensional dengan akurasi terbatas,<\/p>\n

sehingga kurang efektif untuk mitigasi bencana banjir dan kekeringan. Di sisi lain, data satelit (CHIRPS, NOAA OISST) belum dimanfaatkan secara optimal. Penelitian ini menjawab kebutuhan tersebut dalam bentuk pemodelan prediksi menggunakan Deep Learning dengan mengintegrasikan Long Short-Term<\/em> Memory (LSTM) <\/em>dan data satelit untuk meningkatkan akurasi prediksi. Hal ini sejalan dengan prioritas Kemdiktisaintek 2025 dalam penguatan riset AI dan teknologi informasi, serta RPJMN 2025-2029 tentang ketahanan iklim. Tujuan dari penelitian ini adalah mengembangkan model prediksi curah hujan berbasis LSTM dengan input data satelit dan merumuskan rekomendasi kebijakan dalam mitigasi bencana banjir dan kekeringan di Kabupaten Sumbawa.<\/p>\n

Metode yang digunakan dalam penelitian ini meliputi (1) pengumpulan data curah hujan bulanan 30 tahun 1994-2024) dari satelit CHIRPS, suhu permukaan laut (SST) dari NOAA OISST, dan Southern Oscillation Index (SOI) dari Bureau of Meteorology Australia.<\/p>\n","protected":false},"excerpt":{"rendered":"

UNSANEWS, Sumbawa Besar – Tim yang diketuai oleh Romi Aprianto, M.Sc. dengan anggota Dr. Armansyah Putera,M.Pd. meneliti terkait Pemodelan Prediksi Curah Hujan Menggunakan Deep Learning … <\/p>\n","protected":false},"author":4,"featured_media":23202,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[128],"tags":[],"class_list":["post-23233","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-128"],"yoast_head":"\nDosen Universitas samawa Memenangkan Hibah Kompetitif Nasional, Program Penelitian Kementerian Pendidikan Tinggi, Sains, dan Teknologi Tahun 2025, Skema PDP. 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