<![CDATA[This research was carried out by using ARIMA (Autoregressive Integrate Moving Avarage ) with VAR method (Vector Autoregressive) to see which one more effective in forecasting. From the results of the study may indicate that the ARIMA method is more effective than VARmethod in predicting demand for credit in Indonesia . ARIMA ( 1,1,0 ) is the best model for forecasting the level of the average forecasting error is quite low with a value of 8.70 (RMSE) compared with VAR models . Additionally VAR models using multiple stages to performforecasting models such as VAR , Impulse Response , Variance Decomposition to be done to project the demand for credit . From the research that has been done quantitatively that the ARIMA method is more effective and efficient in making predictions , the stage or the method used is quite simple with accurate results with relatively low error rates with 8.70 (RMSE) . While the VAR method for forecasting the need to use multiple stages in predicting demand for credit , but no measure of the level of error in the method of the VAR model is best for forecasting the ARIMA model .Keywords : Credit, Credit Demand, Forecasting]]>
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