DOI: 10.36347/sjebm.2019.v06i02.004

Pages: 104-116

Forecasting is attempted to predict future circumstances and events through testing the situation in the past. The purpose of this study was to analyze the best model to forecast Indonesia’s shrimp export to Japan. Data of Indonesia’s Shrimp exports are time series during 1989-2017. Moving Averages, Single Exponential Smoothing, Least Squares Trend, Quadratic Trend, and Box-Jenkins (ARIMA) models were used to predict the Indonesia’s shrimp export to Japan during 1989-2017 and to forecast export in 2018. Then, the forecast error analysis was analyzed by MAPE (Mean Absolute Percentage Error), MAD (Mean Absolute Deviation), and MSE (Mean Square Error. Minitab 17 application and Microsoft Excel were used for data analysis. As a result, ARIMA was selected as the best model as forecasting model because it has the smallest forecasting errors evaluated by MAPE, MAD, and MSE and is able to predict more accurately than other forecasting models.