Forecasting the number of domestic airplane passenger arrivals using the ARIMA model

Abstract

As travel opportunities have increased, the air transport sector has expanded considerably in recent decades. Many techniques and operations management applications are utilized in the air transportation industry. These include demand forecasting, which predicts future passenger numbers and helps with planning capacity and resources. This research aims to forecast the number of domestic airplane passenger arrivals using the ARIMA model with Minitab 22 and explore the implications on the decision-making of operational management strategies in aviation industries in Indonesia. The data was collected from the Central Bureau of Statistics (Badan Pusat Statistik-BPS) database on airline domestic passenger arrivals in Indonesia. The results show that the best ARIMA model is 1,0,1. The forecasting results show the upper and lower numbers of passengers for five years. The significant increase in air passengers necessitates that airlines focus on fleet capacity, flight availability, and service quality improvements while maintaining competitive ticket prices to maintain passenger numbers. Implementing effective forecasting and dynamic pricing strategies can optimize operational efficiency and ensure sustainable growth in the aviation industry.