Forecasting Passengers Arriving and Departing at Sentani International Airport Terminal Using the ARIMA Method - Jemi Victor Palpialy; Rifqi Raza Bunahri; Musri Kona; Dhian Supardam; Hadi Prayitno (Dinasti Publisher, 2023)
The airport terminal is one of the impacts of Covid-19 which can still be felt with a decrease in the number of arriving passengers and the number of departing passengers. The sentani international airport terminal adjusts airport activities along with normalization after covid-19. The purpose of this study was to determine the number of arriving passengers and the number of departing passengers at the Sentani International Airport terminal by forecasting using the ARIMA forecasting method. This research method uses the ARIMA method. The results show that the best model for forecasting the number of incoming passengers is the ARIMA (1.1.1) model with an RMSE value of 31433.34, MAE of 23993.72, and MAPE of 5207.000, and the number of departing passengers with the ARIMA (1.1.1) model with RMSE of 25220.27, MAE of 18720.95, and MAPE of 11690.43. The ARIMA model can provide accurate forecasts if conducted over a short or brief time frame.