Implementasi Data Mining Clustering Dalam Mengelompokan Kasus Perceraian Yang Terjadi Di Provinsi Jawa Barat Menggunakan Algoritma K-Means - Ihsan Ahmad Fauzi; Raditya Danar Dana (Maeswara : Jurnal Riset Ilmu Manajemen dan Kewirausahaan, 2023)
Divorce cases in West Java Province have increased every year. The profile map of divorce cases that occurred in each region is not yet known, so efforts to provide guidance to minimize divorce cases are not optimal. Divorce case data is also not equipped with a visualization feature that makes it easier for authorized officials to easily understand and analyze data. This study analyzes divorce cases in regencies/cities in West Java Province, using the K-Means Algorithm Clustering data mining method. The clustering method is grouping data based on the same characteristics. In determining the number of clusters, that is by using the value of the Davies Bouldin Index. The results of this study obtained the best cluster of grouping divorce cases, there were 2 clusters, namely cluster 0, there were 5 regencies and 9 cities, while in cluster 1 there were 13 regencies, with a Davies Bouldin index value of 0.168 and an avg.within centroid distance value of 5,870. Cluster 0 is the city/district with the lowest divorce cases and cluster 1 is the city/district with the highest divorce cases.