Analisis Curah Hujan di Indonesia untuk Memetakan Daerah Potensi Banjir dan Tanah Longsor dengan Metode Cluster Fuzzy C-Means dan Singular Value Decompotition (SVD) - Dedi Setiawan (Engineering, MAthematics and Computer Science (EMACS) Journal, 2021)
One of the climate changes impact is extreme rainfall. Extreme rainfall can cause some hydrometeorological disasters, especially floods and landslides. In 2016, BNPB recorded that there were 2,342 disaster events in Indonesia, 92% of which were disasters dominated by floods, landslides, and cyclones. There were 766 floods, 612 landslides, and 74 combinations of both. In this case, clustering is one of the important method to identify groups of areas with similar characteristics of high or low rainfall. Another analysis that can be applied is the identification of the extreme rainfall and the determination of dominant rainfall pattern using Singular Value Decomposition (SVD) for each region in Indonesia. The data was taken from Indonesia’s rainfall data in January 1998 - March 2017, obtained from the Tropical Rainfall Measuring Mission (TRMM) meteorological satellite, with 12,834 observation units. The highest average rainfall in Indonesia in December is 290,26 mm/month. Rainy season is predicted from November to April because they have the highest average rainfall. The SVD analysis formed four dominant rainfall patterns in Indonesia with a variance of 25.59%, where Papua and West Papua are the regions with the highest rainfall. The area around the Indian Ocean is the area with the most extreme rainfall events compared to other regions. Using Fuzzy C-means, three clusters can be formed, with criteria for areas of high, medium, and low rainfall. Based on the results of the analysis, the area has the potential for flooding and landslides due to high rainfall, so that preventive and mitigation efforts against the risk of flooding and landslides can be treated better.