Forecasting of Air Passengers using Singular Spectrum Analysis

Volume 8, Issue 2, April 2023     |     PP. 51-61      |     PDF (1356 K)    |     Pub. Date: May 4, 2023
DOI: 10.54647/mathematics110393    85 Downloads     18139 Views  

Author(s)

Sisti Nadia Amalia, Department of Mathematics, State University of Medan, Indonesia
Zul Amry, Department of Mathematics, State University of Medan, Indonesia

Abstract
Air transportation is the most appropriate option for extremely vast distances, such as those between cities, provinces, and countries. While unpredictability, high volatility, and seasonality sometimes result in complex behavior in air passenger time series, this research applies the Singular Spectrum Analysis technique for air passengers data and uses the linear recurrent type for forecasting. Trends, seasonality, cyclists, and noise can all be found and extracted using Singular Spectrum Analysis. Singular Spectrum Analysis has the potential to be a highly effective forecasting method.

Keywords
Singular Spectrum Analysis, Linear Reccurent Forecasting, Air Passenger

Cite this paper
Sisti Nadia Amalia, Zul Amry, Forecasting of Air Passengers using Singular Spectrum Analysis , SCIREA Journal of Mathematics. Volume 8, Issue 2, April 2023 | PP. 51-61. 10.54647/mathematics110393

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