Malaysia tourism demand forecasting using box-jenkins approach

Tourism industry in Malaysia is crucial and has contributes a huge part in Malaysia’s economic growth. The capability of forecasting field in tourism industry can assist people who work in tourism-related-business to make a correct judgment and plan future strategy by providing the accurate forecast values of the future tourism demand. Therefore, this research paper was focusing on tourism demand forecasting by applying Box-Jenkins approach on tourists arrival data in Malaysia from 1998 until 2017. This research paper also was aiming to produce the accurate forecast values. In order to achieve that, the error of forecast for each model from Box-Jenkins approach was measured and compared by using Akaike Information Criterion (AIC), Mean Absolute Deviation (MAD), Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE). Model that produced the lowest error was chosen to forecast Malaysia tourism demand data. Several candidate models have been proposed during analysis but the final model selected was SARIMA (1,1,1)(1,1,4)12. It is hoped that this research will be useful in forecasting field and tourism industry