Comparison of SARIMA and BES for Forecasting Red Chili Production
Abstract
The goal of this study is to compare the performance of Seasonal Autoregressive Integrated Moving Average (SARIMA) and Bagging Exponential Smoothing (BES) models for forecasting red chili production. The secondary data used in this study came from BPS-Statistics Indonesia and the Ministry of Agriculture. The data include monthly national-level red chili production from January 2013 to December 2021. Data is analyzed using time series approaches such as SARIMA and BES. The performance of both systems was compared, and production forecasts were created using the best model. According to the research findings, for this dataset, the SARIMA (1,1,1)(0,1,1)12 technique outperforms the BES method since it has lower MAPE and RMSE values, 7.06 and 95,473, respectively. The best model was then applied to anticipate red chili production from January to December 2022, resulting in a highly accurate MAPE of 5.39.
Keywords: Bagging Exponential Smoothing, red chili production, SARIMA
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