The Effect of The COVID-19 Pandemic and Google Trends on the Forecasting of International Tourist Arrivals in Indonesia

Abstract

The tourism sector is a strategic industrial pillar that contributes to a country’s economy. In future tourism development efforts, accurate tourism forecasting is needed. Despite its importance, tourism is also one of the most vulnerable industries. Since COVID-19 was declared a pandemic by WHO, social distancing has significantly impacted tourism development. It can be explored more deeply by including the COVID-19 pandemic in the forecast. In addition, it is necessary to include Google Trends, which is a product of the largest search engine in the world and is proven to improve forecasting accuracy. This study aimed to analyze the effect of the COVID-19 pandemic and search query data on the forecasting of foreign tourists to Indonesia. The methods used are ARIMAX and SARIMAX with the endogenous variables of foreign tourist visits to Indonesia. Meanwhile, the exogenous variables are Google Trends search query data and the COVID-19 pandemic. The performance of the two methods is then compared with the ARIMA and SARIMA methods, which do not use exogenous variables in forecasting. This study indicates that the exogenous variables increase the forecasting accuracy. Forecasting with the best accuracy is obtained by the SARIMAX method with the exogenous variable Google Trends. This method outperformed the other methods with MAPE = 5.4556, RMSE = 11041.0510 and MAE = 8479.6116. In addition, in this study, a framework was created to build a composite search index for Google Trends to improve forecasting accuracy.