Big Data Analytics Based Model for Red Chili Agriculture in Indonesia

Horticulture chili plants are a food crop with significant role in the Indonesian macroeconomy. Chili production increases in certain months, which is followed by domestic demand for chili. As production centers for chili plants are concentrated in several provinces, production sometimes is unable to meet consumption demands. This results in a severe increase in chili prices in certain months. The disparity in chili prices in some areas can impact farmers. The purpose of this paper is to develop a model that can be used for the implementation of big data analytics (BDA) in the red chili horticultural agro-industry. Big Data Analytics techniques are applied to develop a predictive model. The research method used a qualitative content analysis approach. The results of this study is a proposed model based on BDA that is applicable to agribusiness of red chili plants in Indonesia. Thus, it could be used in making decisions for farmers to plan optimal chili production schedule and plan logistics and distribution chains to several regions so that farmers can reduce the production cost and increase profit for the farmer.