Peramalan Banyaknya Penumpang Bandar Udara Internasional Sam Ratulangi Manado Dengan Metode Winter's Exponential Smoothing dan Seasonal ARIMA

Abstract

The Winter's Exponential Smoothing method is used to overcome seasonal patterns in data. This method is divided into two models, namely additive and multiplicative models. While the Seasonal ARIMA method is an ARIMA method used to solve seasonal time series. The data used is secondary data from PT. Angkasa Pura I (Persero) Sam Ratulangi International Airport Manado for the period January 2015 to December 2022. The purpose of this research is to determine the model for forecasting the number of passengers at PT.Angkasa Pura I (Persero) Sam Ratulangi International Airport Manado, as well as to compare the Winter's method Exponential Smoothing and Seasonal ARIMA based on the smallest MSD value. The results of the comparison of the two methods with the smallest MSD value are the Winter's Exponential Smoothing method with the multiplicative model equation. The results of the analysis on arriving passengers, namely the exponential smoothing of the original data (α) is 0.9, the smoothing of the trend pattern (β) is 0.1, and the smoothing of the seasonal pattern (γ) is 0.1. With the results of the 2023 forecast, namely: January 95,046, February 87,154, March 98,462, April 97,391, May 110,061, June 103,098, July 130,360, August 118,165, September 108,790, October 115,673, November 112,114, and December 136.40. The results of the analysis on domestic passenger departures are α = 0.9, β = 0.1, and γ = 0.2. With the results of forecasting the number of departures in 2023, namely January 108.900, February 88.588, March 100.646, April 98.066, May 111.638, June 112.963, July 126.684, August 111.471, September 111.872, October 116.211, November 111.990, and December 117.431.