Penerapan Metode K-Means Untuk Clustering Desa Rawan Bencana Berdasarkan Data Kejadian Terjadinya Bencana Alam

Located in the Southeast Asian region, country of Indonesia is one areas prone to disasters related demographic, geological and geographical conditions that trigger both caused by natural factors, non-natural factors human factors. Purbalingga an area Central Java Province which has potential for occur when weather are uncertain. The K-Means clustering method used make it easier analyze group data identify several disaster-prone area. In this research, processing uses rapidminer tools. Based on processing, there were 5 clusters Regency with a very high level vulnerability, medium low vulnerability vulnerability. With existence groups have been determined, hoped anticipation made may arise can continue be carried out appropriately so as minimize effects community.