Clustering Village Development in West Java Province on the Condition of Developing Village Strata Using K-Means Algorithm

Abstract

Villages are important units in the socio-economic structure of a country, and an in-depth understanding of the factors that influence village growth and welfare is essential. To facilitate the local government in handling the equitable distribution of village needs, it is necessary to cluster or group villages. The purpose of this research is to assist the government in clustering certain villages into several clusters, making it easier to monitor and procure village needs within the West Java Provincial government. Clustering is done using the K-Means algorithm. The application of the K-Means Algorithm by determining the Cluster value is 96. The results showed that each cluster has its own membership number. Cluster 0 consists of 8 villages, Cluster 1 consists of 12 villages, and Cluster 2 consists of 8 villages. Furthermore, in testing the performance of the K-Means algorithm by dividing into 96 clusters, the Davies Bouldin Index value is -0.996. From the results of data processing and analysis, it is necessary to provide assistance and procurement of village needs for villages with low clusters by the West Java provincial government