Chili consumption in Indonesia continues to increase along with population growth, however chili prices often experience fluctuations which are influenced by various factors, such as rainfall, market demand and production costs. These unpredictable price fluctuations can make it difficult for farmers and market players to plan chili production and distribution. This research aims to predict chili prices using the neural network method, by utilizing historical data on chili prices and other supporting factors such as weather conditions, market demand and production costs. The neural network model is expected to be able to produce chili price predictions that are more accurate and reliable compared to conventional methods. With accurate price predictions, it is hoped that it can provide a stronger basis for farmers and market players in making decisions regarding the production, distribution and marketing strategies of chilies, as well as creating price stability in the market.
Copyrights © 2024