Perbandingan Kinerja Algoritma K-Means dan K-Medoids Pada Pengelompokan Usaha Pertanian Perorangan Tanaman Pangan di Provinsi Kalimantan Barat - Margareta, Tiara; Satyahadewi, Neva; Pertiwi, Retno (Badan Pusat Statistik Provinsi Kalimantan Barat, 2025)
Kalimantan Barat province as the third largest province in Indonesia, has diverse and promising potential, especially in agriculture. It is known based on the result of the 2023 Agricultural Census, 354.503 people in Kalimantan Barat are food crop subsector agricultural business (contributing 48,58 percent of the total individual agricultural holdings). It is necessary to classify the commodity of food crop to identify the potential commodities in each regencies/cities. The method used in this analysis are the K-Means and K-Medoids algorithms. The use of both methods aims to compare and determine the most suitable algorithm for this analysis. The data used is sourced from the result of the complete enumeration of the 2023 agricultural census with the variable is the number of individual agricultural holdings of food crop commodities (rice and secondary food crops). The purpose of this study is to classify the number of food crop agricultural holdings in Kalimantan Barat Province by regency/municipality. The analysis results showed that K-Means was the best algorithm used for this data, with a DBI of 0,637. Smaller than the K-Medoids algorithm, which had a DBI of 0,683. The result of the K-Means analysis identified four clusters of food crop commodity areas. The first cluster consist of five regencies/municipalities, the second cluster contains one, the third cluster includes six, the fourth cluster comprise two regencies/municipalities.