Forecasting of Factory Pineapple Prices with Box-Jenkins Method
Abstract
The objective of this study was to construct the appropriate forecasting model of factory pineapple price with Box-Jenkins method. Data was gathered 106 values from the Office of Agricultural Economics during January, 2007 to October, 2015 and then divided to 2 sets. The first set contained 100 values since January, 2007 to April, 2015 for constructing the forecasting models. The second set consisted of 6 values since May to October, 2015 for comparing accuracy of the forecasting values with the 3 criterions; the root mean squared error, mean absolute error and mean absolute percent error. The study findings indicated the most accurate forecasting model was ARIMA(0,1,1)(0,1,1)12 Key words : factory pineapple price, Box-Jenkins methodReferences
Department of Agriculture. (2015). Is - not pineapple. Retrieved November 5, 2015, from http://www.doa.go.th/ pibai/pibai/n15/v_7-aug/ceaksong.html
Office of Agricultural Economics. (2015). Pineapple plant prices. Retrieved October 2, 2015, from http://www.oae.
go.th/main.php?filename=monthlyprice
Bowerman, B. L. & O’Connell, R. T. (1993). Forecasting and Time Series: An Applied Approach. 3rd¬¬ ed.
California, Duxbury Press.
H.Brian Hwarng, H.T.Ang. (2001). A simple neural network for ARIMA (p.q) time series. Omega, 29, 319-333.
Office of Agricultural Economics. (2015). Pineapple plant prices. Retrieved October 2, 2015, from http://www.oae.
go.th/main.php?filename=monthlyprice
Bowerman, B. L. & O’Connell, R. T. (1993). Forecasting and Time Series: An Applied Approach. 3rd¬¬ ed.
California, Duxbury Press.
H.Brian Hwarng, H.T.Ang. (2001). A simple neural network for ARIMA (p.q) time series. Omega, 29, 319-333.
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Published
2016-04-07
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Research Article