PENERAPAN METODE BAYESIAN VECTOR AUTOREGRESSION DALAM PERAMALAN JUMLAH KUNJUNGAN WISATAWAN CINA KE BALI

Abstract

Bali is one of the regions in Indonesia which has a very rapid development in the tourism sector. This is indicated by the number of foreign tourist visits to Bali. Since 2017, China has shifted Australia's position as the country with the most number of foreign tourist visits to Bali. This study aims to forecast the number of Chinese tourist visits to Bali, Indonesia’s inflation rate, and the CNY to IDR exchange rate for the period June 2019-March 2020 as well as the dynamic relationship between the three variables. This study used the Bayesian Vector Autoregression (BVAR) method with the Normal-Wishart Prior and compared several lag orders to get the best forecasting results based on the MAPE forecasting criterion. Based on the MAPE forecasting criterion, this study shows the BVAR model with lag 4 produces a very accurate forecasting for the CNY to IDR exchange rate and a good forecasting of the number of Chinese tourist visits to Bali and Indonesia’s inflation rate. The forecast of the number of Chinese tourist visits to Bali, Indonesia’s inflation rate, and the CNY to IDR exchange rate show a stable figure. The impulse response function shows there were shocks in the beginning of the period before finally reaching a stable condition.