Application of K-Means Clustering for Grouping Plantation Production in West Pasaman Regency in 2024 - Dini Andita Putri; Fitri Mudia Sari; Chairini Wirdiastuti (UNP Journal of Statistics and Data Science, 2025)
The plantation sector plays a strategic role in supporting the economy of West Pasaman Regency, with major commodities including oil palm, coconut, rubber, cocoa, and patchouli. However, disparities in production across subdistricts require further analysis to identify regions with similar characteristics. This study applies the K-Means Clustering method, with the optimal number of clusters determined using the Elbow Method. The results show three clusters: the first with relatively balanced production, the second dominated by rubber and cocoa, and the third represented by Kinali District with high dominance of oil palm, coconut, and patchouli. These findings indicate that K-Means Clustering can effectively map regional plantation potentials and provide a useful basis for formulating targeted development strategies to optimize resource allocation and support sustainable agricultural planning in West Pasaman Regency.