Penerapan Metode K-Means Clustering Untuk Analisis Potensi Lahan Pangan Pada Provinsi Kalimantan Selatan

Harjono, Rhaka Pradena
Pakereng, Magdalena A. Ineke

J-SAKTI (Jurnal Sains Komputer dan Informatika)
Vol 7, No 1 (2023): EDISI MARET

National food needs are increasing along with the current population of 237 million people with growth that continues to increase every year, so it needs to be balanced with the provision of sufficient agricultural land resources. The application of the K-Means in the grouping of potential agricultural land in South Kalimantan Province, with the aim of obtaining groups of potential land data. By using the K-means clustering algorithm, the data is divided into 3 clusters, namely cluster 0 with a low potential of 6 districts, cluster 1 with a medium potential of 5 districts, and cluster 2 with a high potential of 2 districts.