NTP forecasting is crucial for supporting appropriate policy-making. Therefore, this study aims to address the problem of selecting the most accurate forecasting method for predicting the Farmers’ Terms of Trade Index (FTTI). Specifically, the objective is to compare the accuracy of two time series forecasting methods, namely Decomposition and Single Exponential Smoothing (SES), in forecasting the price index received by food crop farmers for the period 2020 to 2024. Both methods were evaluated using Root Mean Square Error (RMSE) as a measure of forecasting accuracy. The results show that the Decomposition method provides better forecasting accuracy, as indicated by lower RMSE values (RMSE = 1.846) than the SES method, both with α = 0.1 (RMSE = 7.37) and α = 0.6 (RMSE = 3.23). This finding suggests that the Decomposition method is better at capturing seasonal patterns and trends in the FTTI data than the SES method, which tends to produce larger errors.
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