Clustering of Sub-districts in Cilacap Regency Based on the Number of Health Facilities, Active KB Participants, and Population Growth Rate Using K-Means Cluster Analysis

Abstract

This research examines clustering of sub-districts in Cilacap Regency based on the number of healthcare facilities, active family planning (FP) participants, and population growth rate using K-Means Cluster analysis. The study was conducted at the Cilacap Regency Statistics Bureau using 2023 data. The purpose of this research is to identify differences in each subdistrict’s characteristics to support precise policy formulation. The analysis uses R 4.4.1 software and involves Euclidean distance measurement techniques and standard deviation to determine data similarity between sub-districts. Based on the results, five clusters with unique characteristics were identified. Clusters 1 and 2 have moderate levels of healthcare facilities and FP participants, while Cluster 3 represents sub-districts with the highest number of healthcare facilities and FP participants. Cluster 4 has a low population growth rate, while Cluster 5 includes sub-districts with the highest growth rate. This clustering provides critical information for the allocation of health resources and effective implementation of FP programs. Recommendations for further research include adding related factors to refine clustering results and provide deeper insights for decision-making in the regional health sector.