Forecasting Strategic Food Commodity Prices for 2026 Using ARIMA: Policy Implications for Price Stability in Indonesia
DOI:
https://doi.org/10.47776/mizania.v6i2.2187Keywords:
ARIMA, Food Comodity Prices, Forecasting, Price Volality, Price Stabilization PolicyAbstract
Food price volatility remains a major challenge for economic stability and inflation control in Indonesia, particularly for strategic food commodities that dominate household consumption. Commodities such as garlic, chicken eggs, chicken meat, cooking oil, and sugar contribute significantly to national inflation and require effective price stabilization policies. This study aims to forecast the prices of five strategic food commodities for 2026 using the Autoregressive Integrated Moving Average (ARIMA) model. The analysis employs daily price data from 2023 to 2025 obtained from official government sources. The forecasting procedure follows the Box–Jenkins methodology, including stationarity testing, model identification, parameter estimation, diagnostic checking, and forecasting. Model performance is evaluated using Mean Absolute Error (MAE), Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). The results show that the ARIMA model effectively captures short-term price dynamics and produces reliable forecasts for all examined commodities. Overall, the forecasting results indicate a general upward trend in food prices throughout 2026, with varying degrees of volatility across commodities. These findings provide important insights for policymakers in designing anticipatory food price stabilization and inflation control strategies.
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