Forecasting with Triple Exponential Smoothing on Data of the Number of Passengers Departing Domestic Flights at Sultan Hasanuddin International Airport

Abstract

Transportation facilities and means have developed very rapidly and become the basic needs of the community from time to time. This development ultimately requires the availability of capable and adequate transportation facilities and infrastructure in the form of the availability of good facilities. In general, the movement of the number of flight passengers at Sultan Hasanudin Airport tends not to be stationary on average because in certain times the movement forms an uptrend pattern. In addition, the number of flight passengers at Sultan Hasanudin Airport has an irregular pattern with varying increases and decreases. To forecast fluctuations in the number of flight passengers at Sultan Hasanudin Airport in the coming period, it can be done by time series analysis. The Triple Exponential Smoothing method or commonly referred to as Winter Exponential Smoothing is one of the Time Series methods that is suitable for handling seasonal data such as the number of domestic passengers at Sultan Hasanuddin Airport Makassar. The analysis step of the Triple Exponential Smoothing method is model identification, parameter estimation by trial and error, then is the calculation of the initial value of data smoothing, trends, and seasonality with a length of one season L = 12 and the last is to calculate the error value using MAPE and RMSE. The best model is obtained from a combination of parameters α = 0.9; β = 0,1; and γ=0.1 which results in the smallest forecasting error using RMSE with a value of 56,674.56 and MAPE with a value of 56,674.56. Using a forecasting model:
 So the forecasting results are obtained that look close and not too far from the previous year's data so that it can be used as a reference for the management of the aircraft company to make the right decisions and anticipate a surge in the number of passengers.