Penerapan Metode Clustering Dalam Pengelompokkan Data Curah Hujan Dengan Algoritma K-Means

Abstract

High rainfall can cause natural disasters such as floods, landslides and flash floods. This phenomenon has become more frequent and more severe in recent years, and Indonesia as a tropical country is very vulnerable to natural disasters caused by extreme weather. The Meteorology, Climatology and Geophysics Agency (BMKG) notes that the high number of hydrometeorological disasters cannot be separated from climate change. The BMKG Climate Variability Analysis Coordinator said that BMKG monitoring results in the last 40 years indicated that extreme rainfall in Indonesia had an increasing trend, both in terms of frequency and intensity. The causes of disasters due to rainfall are climate change, population growth and urbanization which increase the risk of natural disasters. Climate change causes rainfall to become more irregular and intense. Population growth causes an increase in settlements in areas that are vulnerable to disasters, so that the risk of disasters becomes higher. Urbanization also causes a reduction in the area of natural areas that can absorb rainwater, resulting in floods and landslides. According to data obtained from the Indonesian Disaster Information Data site (https://dibi.bnpb.go.id/) there were 2690 floods, 2228 landslides and 272 droughts that occurred in Indonesia in the period 2017 to 2018, and landslides is the most common disaster, in 2020 there were 3,232 landslides recorded in West Java.

 Keywords: Calstering, Algorithm, Rainfall, Kemeans