Segmentasi Wilayah Indonesia Yang Berpotensi Budidaya Cabai Dengan Hierarki Clustering

Abstract

Chili is one of the most widely consumed and highly price-volatile horticultural vegetables in Indonesia. In terms of consumption, it is a staple ingredient in the daily diet of most Indonesians. When chili prices surge, it not only affects the purchasing power of the population but also disrupts economic stability. Daily chili price data from the Department of Trade for the period of January 2010 to December 2015 demonstrates significant price fluctuations, primarily influenced by seasonal variations driven by weather conditions. Policy recommendations include promoting off-season chili cultivation, regulating production, and fostering farmer-industry partnerships. In pursuit of these objectives, mapping chili production regions in Indonesia using big data and data mining techniques, particularly hierarchical clustering, emerges as a valuable approach. This methodology allows the creation of models identifying optimal areas for chili cultivation, taking into account soil conditions conducive to optimal growth.The hierarchical clustering process employs average linkage and cosine distance to group regions based on climatic and environmental characteristics. The analysis reveals that Cluster C4, encompassing various provinces across Indonesia, exhibits the most favorable conditions for chili cultivation. This conclusion offers valuable guidance to farmers and researchers in determining the optimal locations for chili cultivation. Furthermore, the approach holds potential for application to other agricultural commodities, contributing to increased domestic production and price stability in the market.