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Forecasting Models for Total Crude Palm Oil Productions in Thailand
Author(s)
Banditvilai, Somsri
Date Issued
December 2, 2024
Type
Conference Paper
Abstract
This research aims to find a suitable forecasting model for Thailand's total crude palm oil production. The monthly total crude palm oil production in Thailand was gathered from the Office of Agricultural Economics, Ministry of Agriculture, and cooperatives from January 2010 to December 2022. The data were divided into two sets. The first set, from January 2010 to December 2021, was used for constructing and selecting the forecasting models. The second one, from January 2022 to December 2022, was used to compute the accuracy of the forecasting model. Since the total crude palm oil production has trend and seasonal variation, the research used the Holt-Winters method with different initial settings for trend and seasonal influence, the Bagging Holt-Winters method, and the Box-Jenkins method to construct the forecasting models. The minimum mean square error (MSE) and residuals have normal distributions used to select the appropriate forecasting model, and the mean absolute percentage error (MAPE) was used to compute the efficiency of the forecasting model.According to the three forecasting methods results, the Box-Jenkins method was suitable for forecasting Thailand's total crude palm oil production. The ARIMA(2,1,2)(0,1,1)12 model was the best model for predicting Thailand's total crude palm oil production and yielded the MAPE =13.49%
Citation
ACM International Conference Proceeding Series, 107-113, 2024