Forecasting Indonesia’s Corn and Rice Production Using Box-Jenkins Approach: Implications for National Food Security
Abstract
Ensuring reliable the production of staple food is precondition to achieve food security, especially on the challenge of climate change and voaltile demands. Forecasting the production of food crops is essential for fabricating effective policies to maintain national food security in Indonesia. This study aims to forecast corn and rice productions using the Box-Jenkins methodology as additional information for supporting the decision tools for food security planning. Competing models were evaluated using information criteria and forecast accuracy measures such as Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). The model specification used were: Corn production ARMA (2.0), while Rice production used SARIMA (0.1.4 )(0.1.1)12. This model generate the forecast of both commodities from late 2025 to 2027. The result of this study can be a consideration for policymakers in making policy on food security in Indonesia.
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