Estimating and Forecasting Covid-19 Cases in Sulawesi Island Using Generalized Space-Time Autoregressive Integrated Moving Average Model

Sukarna, Sukarna and Syahrul, Nurul Fadilah and Sanusi, Wahidah and Aswi, Aswi and Abdy, Muhammad and Irwan, Irwan (2023) Estimating and Forecasting Covid-19 Cases in Sulawesi Island Using Generalized Space-Time Autoregressive Integrated Moving Average Model. Media Statistika, 15 (2). pp. 186-197. ISSN 1979 – 3693

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Official URL: https://ejournal.undip.ac.id/index.php/media_stati...

Abstract

A range of spatio-temporal models has been used to model Covid-19 cases. However, there is only a small amount of literature on the analysis of estimating and forecasting Covid19 cases using the Generalized Space-Time Autoregressive Integrated Moving Average (GSTARIMA) model. This model is a development of the GSTARMA model which has nonstationary data. This paper aims to estimate and forecast the daily number of Covid-19 cases in Sulawesi Island using GSTARIMA models. We compared two models namely GSTARI and GSTIMA considering the root mean square error (RMSE). Data on a daily number of Covid-19 cases (from April 10, 2020, to May 07, 2021) were used. The location weight used is the inverse distance weight based on the distance between airports in the capital cities of each province. The appropriate models obtained based on the data are the GSTARIMA (1;0;1;1) model and the GSTARIMA (1;1;1;0) model. The results showed that the forecast for the number of new Covid-19 cases is accurate and reliable only for the short term.

Item Type:	Article
Subjects:	KARYA ILMIAH DOSEN Universitas Negeri Makassar > KARYA ILMIAH DOSEN
Divisions:	FAKULTAS MIPA
Depositing User:	Zainatun
Date Deposited:	23 Jun 2023 04:54
Last Modified:	23 Jun 2023 04:54
URI:	http://eprints.unm.ac.id/id/eprint/31245

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