Abstract
Indonesia is currently one of the largest coffee producers in the world, and involved in exporting coffee countries. The financial series data such export value of coffee is highly volatile in both mean and variance. Thereby, the model of ARIMA with order p,d,q is one way to deal with this error. The aim of this study is to determine the best-fitted ARIMA(p,d,q) model to forecast the monthly series of export of coffee from January 2005 to April 2020. The findings suggest that ARIMA(1,3,1) is the best-selected model due to its very significant p-value (less than 0.0001), which showed that the model is applicable for forecasting. The model is then used to establish the prediction of ExCof monthly data for the next 12 months.
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