Application of Generalized Space-Time Autoregressive (GSTAR) Model on Distribution of Death Case in 8 District of Central Jakarta

Rahmat Febriyanto; Yekti Widyaningsih; Siti Nurrohmah

Application of Generalized Space-Time Autoregressive (GSTAR) Model on Distribution of Death Case in 8 District of Central Jakarta

Rahmat Febriyanto, Yekti Widyaningsih, Siti Nurrohmah

Department of Mathematics

Research output: Contribution to conference › Paper › peer-review

Abstract

In this paper we apply Generalized Space-Time Model (GSTAR) model on Distribution of Death Case in 8 District of Central Jakarta. The GSTAR model is an extension of the STAR model. The main difference that exists between the GSTAR model and the STAR model is on assuming parameters. The parameters in the STAR model do not depend on the location, so this model is only suitable for locations with homogeneous characteristics. In the GSTAR model, the model parameters change for each location to form a diagonal matrix with parameters. The objective of this study is to model the data of death cases in Central Jakarta using GSTAR model. The data is provided by DINKES DKI (Public Health Office in Jakarta). The data describes the distribution of death cases in 8 districts of Central Jakarta in the period 2011-2017.

Original language	English
Publication status	Published - 2018
Event	The 8 th Annual Basic Science International Conference - ID, Malang, Indonesia Duration: 1 Jan 2018 → …

Conference

Conference	The 8 th Annual Basic Science International Conference
Country/Territory	Indonesia
City	Malang
Period	1/01/18 → …

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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http://basic.ub.ac.id/files/proceeding/BASIC%202018%20Proceedings%20Book_Revised5.pdfLicence: CC BY-NC

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title = "Application of Generalized Space-Time Autoregressive (GSTAR) Model on Distribution of Death Case in 8 District of Central Jakarta",

abstract = "In this paper we apply Generalized Space-Time Model (GSTAR) model on Distribution of Death Case in 8 District of Central Jakarta. The GSTAR model is an extension of the STAR model. The main difference that exists between the GSTAR model and the STAR model is on assuming parameters. The parameters in the STAR model do not depend on the location, so this model is only suitable for locations with homogeneous characteristics. In the GSTAR model, the model parameters change for each location to form a diagonal matrix with parameters. The objective of this study is to model the data of death cases in Central Jakarta using GSTAR model. The data is provided by DINKES DKI (Public Health Office in Jakarta). The data describes the distribution of death cases in 8 districts of Central Jakarta in the period 2011-2017.",

author = "Rahmat Febriyanto and Yekti Widyaningsih and Siti Nurrohmah",

year = "2018",

language = "English",

note = "The 8 th Annual Basic Science International Conference ; Conference date: 01-01-2018",

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Febriyanto, R, Widyaningsih, Y & Nurrohmah, S 2018, 'Application of Generalized Space-Time Autoregressive (GSTAR) Model on Distribution of Death Case in 8 District of Central Jakarta', Paper presented at The 8 th Annual Basic Science International Conference, Malang, Indonesia, 1/01/18. <http://basic.ub.ac.id/files/proceeding/BASIC%202018%20Proceedings%20Book_Revised5.pdf>

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T1 - Application of Generalized Space-Time Autoregressive (GSTAR) Model on Distribution of Death Case in 8 District of Central Jakarta

AU - Febriyanto, Rahmat

AU - Widyaningsih, Yekti

AU - Nurrohmah, Siti

PY - 2018

Y1 - 2018

N2 - In this paper we apply Generalized Space-Time Model (GSTAR) model on Distribution of Death Case in 8 District of Central Jakarta. The GSTAR model is an extension of the STAR model. The main difference that exists between the GSTAR model and the STAR model is on assuming parameters. The parameters in the STAR model do not depend on the location, so this model is only suitable for locations with homogeneous characteristics. In the GSTAR model, the model parameters change for each location to form a diagonal matrix with parameters. The objective of this study is to model the data of death cases in Central Jakarta using GSTAR model. The data is provided by DINKES DKI (Public Health Office in Jakarta). The data describes the distribution of death cases in 8 districts of Central Jakarta in the period 2011-2017.

AB - In this paper we apply Generalized Space-Time Model (GSTAR) model on Distribution of Death Case in 8 District of Central Jakarta. The GSTAR model is an extension of the STAR model. The main difference that exists between the GSTAR model and the STAR model is on assuming parameters. The parameters in the STAR model do not depend on the location, so this model is only suitable for locations with homogeneous characteristics. In the GSTAR model, the model parameters change for each location to form a diagonal matrix with parameters. The objective of this study is to model the data of death cases in Central Jakarta using GSTAR model. The data is provided by DINKES DKI (Public Health Office in Jakarta). The data describes the distribution of death cases in 8 districts of Central Jakarta in the period 2011-2017.

M3 - Paper

T2 - The 8 th Annual Basic Science International Conference

Y2 - 1 January 2018

ER -

Application of Generalized Space-Time Autoregressive (GSTAR) Model on Distribution of Death Case in 8 District of Central Jakarta

Abstract

Conference

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