<![CDATA[Oil is the most important commodity in everyday life, because oil is one of the main sources of energy that is needed for other people. Changes in crude oil prices greatly affect the economic conditions of a country. Therefore, the aim of this study is develop an appropriate model for forecasting crude oil price based on the ARIMA and its ensembles. In this study, ensemble method uses some ARIMA models to create ensemble members which are then combined with averaging and stacking techniques. The data used are the price of world crude oil period 2003-2017. The results showed that ARIMA (1,1,0) model produces the smallest RMSE values for forecasting the next thirty six months. Keywords: Ensemble, ARIMA, Averaging, Stacking, Crude Oil Price]]>
Copyrights © 2018
