The Forecasting Techniques Comparison of Field Crops in Thailand
DOI: 10.14416/j.ind.tech.2021.12.008
Keywords:
Field crops, Time-series forecasting technique, Mean absolute percentage error, Tracking signalAbstract
The essential agricultural production of field crops in Thailand was forecasted in this study. Time-series approaches were used to forecast six field crops, including Thai white rice 15%, Thai jasmine rice 105, sugar cane, cassava, peanuts, and corn, and the results were compared to the mean absolute percentage error and tracking signal. For forecasting, there were two datasets: a training dataset and a testing dataset. The first set of data is developed a forecasting model, and it contains 240 monthly price data from 2000 to 2019, which uses historical monthly pricing data ranging from 3 to 20 years. The second set of data has tested the model with actual price data to develop a forecast model and validate the model with current price data, consisting of 12 monthly price data in 2020. The Box-Jenkins forecasting technique was found to be suitable for forecasting the prices of Thai white rice 15%, Thai jasmine rice 105, sugar cane, cassava, and corn, while the Double Exponential Smoothing technique was shown to be suitable for forecasting peanut prices with MAPE ranging from 1.22% to 8.13%. The MAPE of field crops for the testing dataset varies from 2.00% to 11.94%, which is an accurate estimate.
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