Penduga Model Arima Untuk Peramalan Harga Tbs Kelapa Sawit Di Propinsi Riau

Sigit Sugiarto

Abstract


This article discusses forecasting methods using the Autoregressive Integrated Moving Average (ARIMA) model. This method of forecasting is used to predict the price of Fresh Fruit Bunches (FFB) in Riau Province by 2017. Using the R language, this research yields FIVE models: ARIMA (1,1,0), ARIMA (0,1,1 ), ARIMA (2,1,0), ARIMA (1,1,1) and ARIMA (0,1,2) Model Based on the decision criteria selected one of five combinations of the model which has the smallest MSE value, ie: ARIMA ( 0.1,2) , with the best value of MSE 3905 selected by the criterion of the squared value of the mean square error error. Consequently, model (1) is the best model.

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