ENSEMBLE METHODS IN STATISTICAL DOWNSCALING WITH GAMMA-LASSO REGRESSION FOR RAINFALL PREDICTION IN WEST JAVA - Sativa, Oryza; Djuraidah, Anik; Notodiputro, Khairil Anwar (Jurusan Matematika FMIPA UNM, 2025)
Rainfall is a crucial factor in weather and climate studies, particularly in disaster mitigation efforts such as flood and landslide prevention. West Java, with its mountainous topography and high rainfall, requires accurate rainfall predictions as a basis for decision-making. One effective approach is the ensemble method, which provides valuable insights into prediction outcomes and captures uncertainty. This study analyzes rainfall data from six stations in West Java (Cibukamanah, Krangkeng, Kawali, Katulampa, Cibeureum, and Gunung Mas) over the period 1991–2020. The results indicate that applying the ensemble method in Statistical Downscaling modeling using Gamma-Lasso Regression improves rainfall prediction accuracy compared to single models.