Pengelompokan Daerah Rawan Kriminalitas di Sulawesi Selatan Menggunakan Metode K-means Clustering - Irwan, Irwan; Sanusi, Wahidah; Saman, Febriyanto (Jurusan Matematika FMIPA UNM, 2022)
This research is an applied research that emphasizes how to carry out cluster analysis mathematically, knowing how to apply k-means clustering, and the characteristics of each group of crime-prone areas. The simulation data used in this study is data obtained from the Central Statistics Agency (BPS) of South Sulawesi Province. The data was then analyzed by the K-means clustering method. The results of the study show that there are four characteristics of each group of crime-prone areas in South Sulawesi. Group 1 is categorized as a crime-safe area, Group 2 is categorized as a crime-prone area, group 3 is categorized as a crime-safe area, and group 4 is categorized as an area that is quite prone to crime.