Forecasting of Fresh Cassava Prices via the Use of Box-Jenkins Method
Keywords:
fresh cassava, Box-Jenkins method, mean absolute percentage error root mean square errorAbstract
The objective of this study was to construct and select an appropriate forecasting model for fresh cassava prices via the use of Box-Jenkins method. 277 data points gathered from the website of the Office of Agricultural Economics during January 1997 to January 2020 were used and divided into 2 sets. The first set, consisting of 264 data points and from the period of January 1997 to December 2018, were used to construct the forecasting models. The second set, consisting of 13 data points and from the period of January 2019 to January 2020, were used to compare the accuracy of the forecasting models; the lowest mean absolute percentage error and root mean square error were used as the comparison criteria. The result show that the most accurate model is SARIMA(1, 2, 1)(1, 1, 0)12 with no constant; the forecasting model can be written as the equation:
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