Pengelompokan Data Penduduk Di Desa Penembang Menggunakan Algoritma K-Means Clustering Untuk Program Bantuan Sosial - Artha Dwika Santosa; Herlina Latipa Sari; Prahasti Prahasti (Jurnal Media Infotama, 2026)
Population data clustering in Penembang Village using K-Means Clustering Algorithm-Means Clustering can help manage population data in Penembang Village, particularly in relation to social assistance. It can provide information on the results of population data grouping, which has been divided into two clusters, namely Cluster C1 (in dire need of assistance) and Cluster C2 (not in need of assistance). It can also help Penembang Village Office in determining the priority of residents who are in dire need of assistance so that social assistance programs are targeted appropriately. The desktop-based population data clustering application uses the Visual Basic.Net programming language with SQL Server database. Based on tests conducted using data from 12.5% of the total 241 households in 2024, namely 30 households, the results show that the group in dire need of assistance (Cluster C1) consists of 12 households with a percentage of 40%, and the group that does not need assistance (Cluster C2) consists of 18 households with a percentage of 60%. Based on testing of the program demo in Penembang Village Office, it is found that the population data grouping application is very easy to operate and very helpful in obtaining population data clustering information, thereby supporting the decision-making process in determining social assistance recipients in Penembang Village Office.