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Winda Triyani
Department of Mathematics, Jenderal Soedirman University
Mathematics

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KAJIAN PEMODELAN DERET WAKTU: METODE VARIASI KALENDER YANG DIPENGARUHI OLEH EFEK VARIASI LIBURAN Winda Triyani; Rina Reorita
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 4 No 1 (2012): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2012.4.1.2948

Abstract

Calendar variation method is a technique that combines ARIMA modeling and regression modeling. Calendar variation is a cyclical pattern with varying periods due to the different calendar date position for each year. There are two types of calendar variation, trading day variation and holiday variation. In this research, modeling of time series with holiday variation was studied and modification of the modeling was developed for the case of holiday effect due to Eid’s day occur. The case study was conducted to the data of train passenger number at DAOP V Purwokerto. It was found that the last model for the underlying data was the regression model with the residual following seasonal ARIMA (1,1,1)(0,0,1)12 without constant parameter.
KAJIAN PEMODELAN DERET WAKTU: METODE VARIASI KALENDER YANG DIPENGARUHI OLEH EFEK VARIASI LIBURAN Winda Triyani; Rina Reorita
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 4 No 1 (2012): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2012.4.1.2948

Abstract

Calendar variation method is a technique that combines ARIMA modeling and regression modeling. Calendar variation is a cyclical pattern with varying periods due to the different calendar date position for each year. There are two types of calendar variation, trading day variation and holiday variation. In this research, modeling of time series with holiday variation was studied and modification of the modeling was developed for the case of holiday effect due to Eid’s day occur. The case study was conducted to the data of train passenger number at DAOP V Purwokerto. It was found that the last model for the underlying data was the regression model with the residual following seasonal ARIMA (1,1,1)(0,0,1)12 without constant parameter.
Co-Authors Rina Reorita