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All Journal Proceedings of KNASTIK AGRIEKONOMIKA Transformasi: Jurnal Pengabdian Masyarakat Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Teaching and Learning in Elementary Education Indonesian Journal of Primary Education QARDHUL HASAN: MEDIA PENGABDIAN KEPADA MASYARAKAT JIMFE (Jurnal Ilmiah Manajemen Fakultas Ekonomi) Multitek Indonesia : Jurnal Ilmiah Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pedagonal : Jurnal Ilmiah Pendidikan EKOLOGIA : Jurnal Ilmiah Ilmu Dasar dan Lingkungan Hidup Operations Research: International Conference Series Jurnal PkM (Pengabdian kepada Masyarakat) Teknologika Jurnal Aplikasi Bisnis dan Komputer Indonesian Journal of Primary Education
Aries Maesya
Universitas Pakuan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Public Health Social Sciences Other

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Journal : Proceedings of KNASTIK

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PEMODELAN DOWNSCALING LUARAN GCM DAN ANOMALI SST NINO 3.4 MENGGUNAKAN SUPPORT VECTOR REGRESSION (Studi Kasus Curah Hujan Bulanan Indramayu) Maesya, Aries; Buono, Agus; Mushthofa, Mushthofa
Proceedings of KNASTIK 2012
Publisher : Duta Wacana Christian University

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Abstract

anomaly Nino 3.4 as input in the training to predict a rainfall monthly in Indramayu.The techniques of a downscaling is used for a phenomenon indicators of El Nino andSouthern Oscillation (ENSO) climate anomaly such as a Global Circulation Model(GCM) and Sea Surface Temperature (SST) nino 3.4 are commonly used as a primarystudy learn and understand the climate system. This research propose a method fordeveloping a downscaling model GCM output and SST anomaly Nino 3.4 by usingSupport Vector Regression (SVR). The research result showed that GCM output andSST anomaly Nino 3.4 can be approach the average value of monthly rainfall. The bestresult of prediction is Bondan station which has average correlation that is 0.700.
Co-Authors 'ala, Faridatul Ade Muchlis Maulana Anwar Agus Buono Ahmad Izzuddin Awiria, Awiria Cantika Zaddana E Mulyati Effendi, E Mulyati Eka Suhardi Elinda Puspita Elly Sukmanasa Eneng Tita Tosida Evi Sopiani Faridatul’al, Faridatul’al Fredi Andria Halimah Tus Sadiah Lina Novita Lina Novita Lina Novita, Lina Lita Karlitasari Luthfiyana Nur Alifa Muhamad Saad Nurul Ishlah Prawira, Asrori Yudha Prihastuti Harsani Ramdhani, Muhammad Imam RR. Ella Evrita Hestiandari S. Rusdiana Selo Aji Supardi Rusdiana Tomi Herdiawan, Tomi Victor Ilyas Sugara Yuli Wahyuni