Forecasting on the crude palm oil and kernel palm production: Seasonal ARIMA approach

Author

Ahmad, Sabri ; Latif, Humaira´ Abdul

Author_Institution

Dept. of Math., Univ. Malaysia Terengganu, Kuala Terengganu, Malaysia

fYear

2011

fDate

5-6 Dec. 2011

Firstpage

939

Lastpage

944

Abstract

The purpose of this study is to develop crude palm oil and kernel palm production using SARIMA (Seasonal Autoregressive Integrated Moving Average). The data set used in this study is production of crude palm oil and kernel palm from June 2001 until May 2011. The accuracy of the forecasts was then measured by the MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error), RMSE (Root Mean Squared Error) and MSE (Mean Square Error). In conclusion, the model SARIMA(0,1,2)(1,1,3)₁₂ was choose to forecast the crude palm oil production while the model SARIMA(1,1,1)(1,1,0)₁₂ was choose to forecast kernel palm production. The results showed that the production for crude palm oil and kernel palm are increase than the previous year.

Keywords

autoregressive moving average processes; crude oil; forecasting theory; mean square error methods; production management; Kernel palm production; MAE; MAPE; MSE; RMSE; crude palm oil; mean absolute error; mean absolute percentage error; mean square error; root mean squared error; seasonal ARIMA approach; seasonal autoregressive integrated moving average; Autoregressive processes; Correlation; Kernel; Mathematical model; Predictive models; Production; Time series analysis; Crude Palm Oil and Kernel Palm Production; MAE (Mean Absolute Error); MAPE (Mean Absolute Percentage Error); MSE (Mean Square Error); RMSE (Root Mean Squared Error); SARIMA (Seasonal Autoregressive Integrated Moving Average);

fLanguage

English

Publisher

ieee

Conference_Titel

Humanities, Science and Engineering (CHUSER), 2011 IEEE Colloquium on

Conference_Location

Penang

Print_ISBN

978-1-4673-0021-6

Type

conf

DOI

10.1109/CHUSER.2011.6163876

Filename

6163876