Damped Trend Exponential Smoothing and Holt-Winters in Forecasting the Number of Airplane Passengers at Kualanamu Airport

Rustham Michael Binoto; Sudarwanto Sudarwanto; Vera Maya Santi

doi:10.30598/pijmathvol4iss1pp29-40

Rustham Michael Binoto Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Jakarta, Indonesia
Sudarwanto Sudarwanto Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Jakarta, Indonesia
Vera Maya Santi Universitas Negeri Jakarta

DOI: https://doi.org/10.30598/pijmathvol4iss1pp29-40

Keywords: Aircraft Passenger, Damped Trend, Forecasting, Holt-Winters, Kualanamu Airport

Abstract

Airplanes are one of the most frequently chosen modes of transportation by Indonesians today. Kualanamu Airport is one of the busiest airports in terms of the number of passengers. The number of airplane passengers often fluctuates, increasing and decreasing, so an analysis method is required to predict the number of passengers. This study uses the Double Exponential Smoothing Damped Trend and Multiplicative Holt-Winters models. The number of Kualanamu Airport domestic airplane passengers from January 2006 to December 2023 was used as research data. The best model is then used to forecast the number of Kualanamu Airport domestic airplane passengers for 12 periods from the last data used. The results showed that the Multiplicative Holt-Winters model with smoothing parameters and obtained smaller (Mean Absolute Error) MAE and (Mean Square Error) MSE values of 21415.556 and 961525264.508, compared to the Double Exponential Smoothing Damped Trend model with smoothing parameters,, and which obtained MAE and MSE values of 23612.461 and 1061042411.507 in predicting the number of domestic aircraft passengers at Kualanamu Airport. Forecasting accuracy for the next 12 periods using Holt-Winters Exponential Smoothing produces a MAPE value of 9.2%. It shows the accuracy of forecasting in the very good category.

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