Diversification of Agricultural Areas in Indonesia using Dynamic Copula Modeling and K-Means Clustering

Agriculture is one of the main pillars economic growth in Indonesia. Failure this sector can result faltering stability country. Thus, to minimize these failures, mapping areas with particular commodity potential needed. One factors affecting crops rainfall. Therefore, paper aims model distribution based on rainfall precipitation using dynamic copula. The modeling results are then used as a basis for grouping food crop commodities determination group was carried out k-means clustering method. We expect that provide an overview farmers or government make policies related optimization Indonesia's agricultural sector. This will enable offer facilities losses, such superior seeds resistant weather changes and provision training enhancing farming skills. In addition, it also suggested diversify farm reduce failures due dependence single product.