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Forecasting Jumlah Penumpang Pesawat Yogyakarta International Airport dengan Big Data Google Trends dan Variabel Makroekonomi untuk Mendukung Official Statistics Chisan, Innas Khoirun; Wijayanto, Arie Wahyu
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2123

Abstract

Aviation is an important element to support human connectivity and mobility so it is important to carry out an analysis of the number of airplane passengers. BPS releases data on the number of airplane passengers with a lag of around thirty days. In addition, the use of search engines is increasingly being used nowadays. This research aims to predict the number of Yogyakarta International Airport (YIA) airplane passengers in 2024 using Google Trends and macroeconomic data. To carry out this forecast, the SARIMA and SARIMAX models will be compared with several combinations of external variables. The research results show that the use of Google Trends Index variables and macroeconomics can increase forecasting accuracy. The best model selected was SARIMAX with external variables Google Trends Index and macroeconomics. The forecast results for the number of airplane passengers in January 2024 are 332 thousand passengers and in February 2024 there are 292 thousand passengers. Accurate predictions can help flight planning so that this research can play a role in improving the quality of official statistics in the field of air transportation.