Penggunaan Metode Fuzzy C-Means untuk Pengelompokan Kabupaten/Kota Berdasarkan Jumlah Tenaga Kesehatan - Syam, Surya Cahyadi; Tinungki, Georgina Maria; Kalondeng, Anisa (ESTIMASI: Journal of Statistics and Its Application, 2026)
Clustering is the process of partitioning data into a number of clusters, which in the cluster have similar characteristics to one another and have differences with other clusters. In this study, clustering is used to group district/cities based on the number of health workers in South Sulawesi using fuzzy c-means. To get the results of grouping, there are 11 health worker variables used. In determining the optimum number of clusters, the Pseudo F-Statistic is used. In the first test, the optimum cluster was obtained in 5 groups and the second test was in 6 groups without makassar and bone. From the clustering analysis in the first test, it was found that groups 2 and 3 only have one member. In the second test, group 1 had 4 members, groups 2 and 6 had 3 members, group 3 had 2 members, and groups 4 and 5 had 5 members.