The performance of GM (1,1) and ARIMA for forecasting of foreign tourists visit to Indonesia

Abstract

Forecasting can be used for helping the decision-makers to determine the next business strategy to improve the quality of Indonesia tourism such as the improvement of the accommodation facility like transportation and lodging, public services, and promotion to introduce Indonesia tourism objects. This research compared the forecasting performance between GM (1,1) and ARIMA models to determine the best method to forecast the number of foreign tourists visit to Indonesia by using limited data. The data used is the national data of foreign tourists arrival in the airport entrance obtained from the BPS Indonesia in the period of 2002 to 2014. From the result of the forecasting accuracy based on RMSE and MAPE showed that GM (1,1) is smaller than of the ARIMA. It indicates that the performance of GM (1,1) is better than ARIMA to forecast the number of foreign tourists visit. However, it can be concluded that both of the models are able to forecast properly because both of them produce MAPE less than 10%.