Time Series Forecasting with Classical Decomposition Method: Jasmine Rice Exportation of Thailand

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Published: Apr 11, 2020
Keywords:
Forecasting, Time Series Analysis, Classical Decomposition, Export Value, Thai Jasmine Rice

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Nitinai Rungjindarat
Lecturer, Business Administration and General Education Office, Faculty of Hospitality Industry, Dusit Thani College
Sarun Thatsakaniwet
Bachelor’s Degree in Business Administration, Majoring in Culinary Arts and Kitchen Management, Faculty of Hospitality Industry, Dusit Thani College

Abstract

The aim of this paper is to study the trend, seasonal deviance and forecasting for the exportation value of jasmine rice in Thailand between year 2018 - 2019. The quarterly data is used for conducting the forecast model. The data are divided into two sets, first is the training data. Second is the testing data obtained from the Office of Agricultural Economics. Time Series Analysis is composed by classical decomposition method. The study found that the forecast model is extremely accurate since the Mean Absolute Percentage Error of the training data has resulted in 6.42% and Mean Absolute Percentage Error of the testing data is 3.09%. The exportation value of jasmine rice in Thailand has the tendency to decline together with the occurrence of seasonal deviance. The exportation value is highest in the fourth quarter (17.63% more than usual) and found to be lowest in the second quarter (10.66% less than usual)

Article Details

How to Cite
Rungjindarat, N. ., & Thatsakaniwet , S. . (2020). Time Series Forecasting with Classical Decomposition Method: Jasmine Rice Exportation of Thailand. Dusit Thani College Journal, 13(2), 283–293. Retrieved from https://so01.tci-thaijo.org/index.php/journaldtc/article/view/241072
Issue
Vol. 13 No. 2 (2019): Dusit Thani College Journal Vol.13 No.2 May - August 2019
Section
Research Article

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