Advances and Applications in Statistics
Volume 52, Issue 4, Pages 251 - 265
(April 2018) http://dx.doi.org/10.17654/AS052040251 |
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THE ELECTION OF THE BEST AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODEL TO FORECASTING RICE PRODUCTION IN INDONESIA
Georgina Maria Tinungki
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Abstract: The objective of this research is to identify the best autoregressive integrated moving average (ARIMA) model for forecasting rice production in Indonesia. Rice crops are the most important agricultural commodity in Indonesia, because rice is the staple food of Indonesians. Therefore, the ability to forecast rice production is crucial. We used autoregressive integrated moving average (ARIMA) model to predict rice production in Indonesia. The data analyzed is the data of rice production in Indonesia from 1993 to 2012. The data of 2013 to 2015 got used to validate the forecasting results. The results show that the ARIMA model (2, 2, 0) is the best model for forecasting rice production in Indonesia. |
Keywords and phrases: agriculture, ARIMA model, rice production, time series model. |
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