Clusterization of Agroforestry Farmers using K-Means Cluster Algorithm and Elbow Method - Trio Santoso; Arief Darmawan; Novita Sari; Muhammad Ariq Fadhal Syadza; Edelweis Cikal Bunga Himawan; Wahyu Abdul Rahman (Jurnal Sylva Lestari, 2023)
Proper policy is crucial to support the development of forest areas. Therefore, good planning based on supporting data is crucial. All information considering farmers’ conditions and interests in Talang Mulya Village, situated around Wan Abdul Rachman Forest Park, is urgently needed. So far, policies and programs launched have only been general and inappropriate to implement for the whole farmers. The main objective of this research was to perform fast agroforestry farmers clustering with differences in the main characters to each other using the K-means clustering algorithm and Elbow method based on 10 variables of social and land cultivation conditions. Results showed that agroforestry farmers in Talang Mulya Village could be best divided into 4 clusters with the proportion of 30%, 40%, 23.3%, and 6,67% for clusters 1, 2, 3, and 4, respectively. Agroforestry farmers were dominated by farmers with the specific characteristics of the lowest number of families working on the land and the cultivated main plant species with a sufficient level of formal education, family dependents, farming experience, household members that help in the farm, size of land area, expenditure and income from land cultivation, and maintenance activities. The research results could be used as a consideration for determining specific and targeted activity programs to increase the cultivation capabilities and welfare of farmers in Talang Mulya Village. Keywords: Agroforestry, Elbow Method, K-means Clustering, Tahura Wan Abdul Rachman, Talang Mulya Village