Klasterisasi Daerah Rawan Kriminalitas di Sulawesi Tenggara Menggunakan Metode K-Means Clustering

Abstract

Crime is anything that relates to unlawful behavior. In every society, the presence of crime affects social dynamics, levels of security, and general well-being. Southeast Sulawesi in the midst of its diversity is facing a significant increase in crime, this is evident from the 3,000 cases that have been reported. The purpose of this research is to categorize crime-prone areas in Southeast Sulawesi using the K-Means Clustering method. K-Means is a research data analysis method or a data mining method that will carry out modeling without supervision (unsupervised). The data from this research was taken from the sultra.bps.go.id web page. The data taken in the form of data on the number of crimes and the percentage of crime victims in the regions of Southeast Sulawesi. The results of this study obtained 3 clusters of crime-prone areas in Southeast Sulawesi. The clustering evaluation results if calculated by the Daviees Bouilden Index method is as much as 0.5904 index.