Short-Term Forecasting of Air Travellers Outflows from Bali Using Web Search Data

Abstract

Air travelers have become one of the strategic indicators in the transportation sector. The official data-released by Statistics Indonesia (BPS) for thirty days-lag, makes the condition of this indicator can’t be known in real-time. By the utilization of web search data that has been briskly evolving in recent years, this study aims to explore the possibility of using web search data in performing short-term forecasting to know the general outlook of the indicator earlier. Based on this study, web search data and official statistics figures show a strong correlation and having similar movement patterns over time. The application of web search data as a predictor in time series modeling, especially on time series regression and autoregressive model (SARIMA and SARIMAX), turn out a predicted value that well-approach the actual value of the response variable. In addition, it is proven that the use of web search data can increase model accuracy. The analysis results using SARIMAX model shows that the number of air traveller’s outflows from Bali in September and October 2021 will generally be higher than the number in August 2021. The increasing number of air travelers is thought due to a decrease in Covid-19 cases which has triggered the public's confidence in travelling about to rise again.