<![CDATA[Ensuring food security is a key part of sustainable development in Indonesia, especially since rice remains the country's staple crop. In regions like West Nusa Tenggara (NTB) Province, where rice harvest areas can vary significantly, having accurate forecasts is essential for effective planning. This study explores historical data on rice harvest areas in NTB to forecast future trends, uncover seasonal patterns, and assess long-term changes. To do this, we apply and compare three forecasting methods: Simple Moving Average (SMA), Weighted Moving Average (WMA), and Exponential Moving Average (EMA). Their performance is evaluated using accuracy measures such as Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE), with results also presented visually to support data-driven decision-making. Among the methods tested, EMA with a 3-period window (EMA-3) produced the most accurate forecasts. This is reflected in its lower RMSE and MAPE values compared to the other methods. Based on the MAPE results, EMA-3 proves to be a reliable method for forecasting rice harvest areas in NTB.]]>
Copyrights © 2025
