The Application of the K-Means Clustering Method in Grouping the Number of Poor People per Regency/City in Papua Province in 2023
Priskilla Sahaduta Simbolon, Enita Dewi Tarigan, Tulus Joseph Herianto · Journal of Mathematics Technology and Education. · 2025
Poverty is a serious problem faced by many developing countries and is still a major challenge in remote areas of Indonesia, especially in Papua Province. The high poverty rate in Papua Province makes this area the poorest province with the highest percentage of poor people in Indonesia in 2023. This study aims to classify Regencies/Cities in Papua Province based on the socio-economic conditions of the community using the K-Means Clustering. The data was obtained from the official source of the Central Statistics Agency of Papua Province using four main indicators, namely the percentage of the poor population, total population, the Human Development Index (IPM), and the Life Expectancy Rate (AHH). The analysis process was carried out iteratively until stability was achieved in the third iteration. The final results showed 3 clusters: Cluster 1 consists of 13 districts/cities with a moderate poverty level, cluster 2 consists of 7 districts/cities with a high poverty level, and cluster 3 consists of 9 districts/cities with a low poverty level. The high poverty levels in cluster 2 include: Jayawijaya Regency, Paniai Regency, Puncak Jaya Regency, Yahukimo Regency, Tolikara Regency, Lanny Jaya Regency, and Puncak Regency. Keyword: Clustering, K-Means, Poverty