Pengelompokan Produktivitas Cabai Besar di Jawa Barat Menggunakan Algoritma K-Means

Abstract

Chili is a horticultural plant that falls under the vegetable category and has significant potential for commodity development. The consumption of chili in Indonesia continues to increase every year. As one of the highest chili-producing provinces in Indonesia, West Java needs to be clustered to identify areas with varying productivity potential, from low to high, so that it can be optimized. This study aims to cluster the productivity of big chili in West Java using clustering techniques in data mining through the k-means algorithm. The data used includes harvested area, production, and productivity of big chili in West Java from 2021 to 2024, obtained from opendata.jabarprov.go.id. The methodology applied is KDD (Knowledge Discovery in Database). The determination of the best cluster value is conducted using the elbow method. The clustering results yield two clusters: cluster 0 (areas with low big chili productivity) and cluster 1 (areas with high big chili productivity). The evaluation of the clustering results using the silhouette coefficient shows a value of 0.86, indicating that the resulting structure falls into the strong structure category