Forecast of Farmers' Exchange Rate in Jambi Province Using the Arima Method (Autoregressive Integrated Moving Average)
DOI:
https://doi.org/10.32493/sm.v8i1.59309Keywords:
Farmer Exchange Rate, Forecasting, ARIMA, Time Series, Jambi ProvinceAbstract
Changes in the NTP over time indicate the variations in agricultural product prices and the costs of production that farmers deal with. This research intends to predict the Farmer Exchange Rate for Jambi Province using the ARIMA technique. The data utilized consists of time series information on the NTP of Jambi Province stretching from January 2021 to May 2025. The analysis process involves checking for data stationarity via the ADF test, performing Box-Cox transformation, differencing, identifying models using ACF and PACF charts, estimating parameters, and conducting model diagnostics. The optimal model was determined based on the MAPE evaluation. The findings indicated that the ARIMA (0,2,1) model was the most effective, exhibiting a lower MAPE value than other models, indicating strong forecasting accuracy. This model was subsequently employed to predict the NTP for Jambi Province for the period from June to October 2025. The results from these predictions reveal a rising trend in NTP values, suggesting a possibility for enhanced farmer welfare in Jambi Province. It is anticipated that this study will provide useful insights for the government and relevant stakeholders.
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