An Integrated Model for Time Series Regression with Islamic Calendar Variation and COVID 19 to Forecast Number of Train Passangers Mega Silfiani(a,b,*), Farida Nur Hayati (a)
a)Department of Statistics, Institut Teknologi Kalimantan
Jalan Soekarno Hatta KM. 15, Karang Joang, Balikpapan, Indonesia
b)Department of Economics, Gdansk University
Armii Krajowej Street, 114-116, Sopot, Poland
*) megasilfiani[at]lecturer.itk.ac.id
Abstract
The purpose of this paper is to examine a forecasting model for the number of train passengers using an integrated time series regression with Islamic Calendar Variation and Covid 19 Effects. This study uses the number of train passengers in Jabodetabek, Jawa (Non Jabodetabek), and Sumatra from January 2006 to October 2022 as its data source. Integrated time series regression with Islamic Calendar Variation and Covid 19 Effects for Jabodetabek, Jawa (Non Jabodetabek), and Sumatra has RMSE values for each variable of 5433.681, 2788.881, and 185.207. In Jabodetabek and Jawa (non-Jabodetabek), variations in the Islamic calendar have no substantial impact on the number of train passengers. Meanwhile, Ied Fitr has a huge impact on the amount of train passengers in Sumatra. In general, the Covid 19 impact influences the number of railway passengers for each variable significantly.
Keywords: Forecasting- Regression- Time Series- Train Passangers
