Agricultural Strategic Commodity Price Forecasting Using Artificial Neural Network

Abstract

Agricultural commodities, especially perishable one such as chili and onion have sharp and irregular price fluctuation. Decreasing supply of the commodities to the marketplace produces its price soars. On the contrary, the price falls below the normal price when its supply increase abundantly. Where the price stability on the commodities is desired, government are trying to maintain its supply rigorously. This paper aims to forecast chili price as a perishable commodities to help the decision maker in maintaining its supply. The method used in this study was artificial neural network using the input variable i.e. consumer’s price, chili production, and chili consumption. The artificial neural network model has been produced using the available data. It has MAPE value 16.19% and considered as sufficient accuracy.