Prediction Model for Chilli Productivity Based on Climate and Productivity Data

The global trade increases the competition in agricultural product export all around the world. The Indonesian Agricultural Industry needs to improve their competitiveness by fulfilling the requirements and restrictions imposed by some countries with regards to trace ability information features of the products, such as location of farming field cultivation method, chemical contaminants and supply chain information. Some European countries require the implementation of E-GAP (European Good Agricultural Practices) in order to secure food safety. Food safety provides the control and monitoring during, pre-, and post-harvest stages of agricultural products. This paper describes a prediction model based on the climate and productivity data on Indonesian agricultural products. The prediction model with an iteration of the climate and their possible increase or decrease in productivity. The model relies on historical data and an analytical algorithm. The decision support and early warning system provides the farmer some advice to reduce the crop failure risks due to climate change.