Forecasting the Number of Domestic Aircraft Passengers at Sultan Aji Muhammad Sulaiman Sepinggan Balikpapan Airport with Holt-Winters Exponential Smoothing

Abstrak

Forecasting the number of domestic air passengers plays an important role in supporting operational efficiency and strategic planning at airports. This study aims to forecast the number of domestic air passengers at Sultan Aji Muhammad Sulaiman Sepinggan Balikpapan Airport using the Holt-Winters Exponential Smoothing method and the ensembel averaging approach. The data used are monthly data on the number of domestic passengers from January 2018 to September 2023. Four Holt-Winters models with variations in smoothing parameters were built to obtain the best model based on the Mean Absolute Percentage Error (MAPE) value. The results showed that Model 1 provided the best accuracy with a MAPE value of 6.17%. Furthermore, forecasting was carried out using the ensembel averaging approach from the four models, which produced higher accuracy with a MAPE of 5.64%. These findings indicate that the ensembel method can improve forecasting accuracy compared to using a single model. Thus, this approach can be an effective alternative to support operational planning in the air transportation sector.