Pengelompokan Provinsi di Indonesia Berdasarkan Hasil Panen Padi Menggunakan Metode Fuzzy C-Means

Abstract

The agricultural sector, particularly rice as a commodity, plays an important role in supporting national food security. Rice production in Indonesia has declined in recent years due to climate change, land
conversion, and uneven distribution of assistance. This study aims to classify provinces in Indonesia based on rice yields using the Fuzzy C-Means (FCM) method. Secondary data from BPS for the 2019–
2023 period were employed with five main variables, namely yield, harvested area, productivity, rainfall, and seeds. The research stages included data standardization, followed by clustering using the Fuzzy
C-Means method, which was carried out iteratively until the cluster centers and membership values reached stability. The optimal number of clusters was determined through validity testing with the Partition Coefficient. The results indicate the formation of three clusters: high, medium, and low. These findings can serve as a basis for formulating more targeted and effective agricultural policies.