Prediksi Curah Hujan Bulanan Di Wilayah Lombok Barat Menggunakan Principal Component Regression (PCR)

Abstract

Rainfall is a significant climate parameter in various sectoral of human activities. Despite that, precise rainfall prediction is necessary. One factor which can affect the rainfall is Sea Surface Temperature. We used Sea Surface Temperature data in Indonesia limited by 14° LS - 10° LU and 90° BT - 142° BT to predict monthly rainfall in West Lombok. The method used in this study is Principal Component Regression. Regression is calculated using 1998-2013 data, with Principal Component Analysis result of Indonesian Sea Surface Temperature as the predictor. Validation using contingency table for 2014-2018 rainfall characteristic data in West Lombok showed that rainfall prediction is appropriate with the rainfall pattern observation data.