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)
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.