Production forecasting is a crucial instrument in supporting planning and policy-making in the agricultural sector, particularly for strategic commodities such as corn. This study aims to forecast corn production in West Sumatra Province and evaluate the most accurate forecasting method to serve as a basis for agricultural development policy formulation. Time series data on corn production from 2000 to 2024 were analyzed using three forecasting methods: Average Forecast, Naïve Forecasting, and Moving Average. The results show that the Naïve Forecasting method produced the most accurate projections, with a MAE of 56,546.39 and an RMSE of 83,788. These findings suggest that even simple forecasting models can be effective tools for short-term projections. Accurate production forecasting is therefore essential to anticipate harvest fluctuations, maintain supply stability, and design more responsive and data-driven policy interventions in West Sumatra.Keywords: Forecasting, Corn Production, Naive Forecasting, West Sumatera.
Suryani et al. (Mon,) studied this question.