Penggunaan Indeks Google Trends dalam Nowcasting Jumlah Penumpang Pesawat Terbang pada Keberangkatan Domestik dan Internasional di Bandara Soekarno-Hatta - Arini, Rechtiana Putri; Wijayanto, Arie Wahyu (Seminar Nasional Official Statistics, 2025)
Soekarno-Hatta International Airport, as Indonesia’s busiest air transit hub, requires swift, data-driven decision-making to implement responsive policies that enhance passenger services. The number of airline passengers serves as a critical indicator for managing passenger traffic flow, demanding timely data insights. However, official statistics often suffer from a 1–2 month reporting lag. To address this, the study applies nowcasting techniques to estimate passenger volumes using Google Trends indices from January 2016 to January 2024. By integrating GT indicators into SARIMAX and Time Series Regression models, airport authorities can access early signals of passenger traffic volumes. Among the models tested, SARIMA(0,1,1)(1,0,0) 12 demonstrated the best performance, achieving a MAPE of 15.15%. This approach offers valuable, near-real-time insights to support operational planning and policy response in a fast-paced transport environment.