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

Abstract

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