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SUSCEPTIBLE VACCINATED INFECTED RECOVERED SUSCEPTIBLE MODEL: EQUILIBRIA POINTS AND APPLICATION ON COVID-19 CASE DATA IN INDONESIA

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 18 No. 3 (2024) · pp. 1607–1614

DOI
10.30598/barekengvol18iss3pp1607-1614
ISSN
2615-3017, 1978-7227
Published
2024-08-02
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Severe Respiratory Syndrome Coronavirus-2 is the infectious agent that causes COVID-19. A vaccine program is an effort to stop the spread of COVID-19 infections in Indonesia. The susceptible vaccinated infected recovered susceptible (SVIRS) model can be used to represent the spread of infectious diseases. This study aims to construct the SVIRS model, identify the equilibria points thus apply it to COVID-19 case data in Indonesia, and determine transmission patterns, model accuracy, and interpretation. Literature and applications are the research methodologies employed. First-order nonlinear differential equations form the obtained SVIRS model. The model has two equilibrium points: a disease-free equilibrium point, and the other is endemic equilibrium point. The SVIRS model on the spread of COVID-19 in Indonesia was obtained using daily secondary data from January 11 to November 30, 2022. The model is solved by the fourth-order Runge-Kutta method. The model’s accuracy is accurate enough to explain the spread of COVID-19 in Indonesia with a mean average percentage error (MAPE) value of 43%. According to the transmission pattern, the number of COVID-19 cases in Indonesia peaked on July 27, 2022, then decreased to zero, obtaining an equilibrium point when no more cases of the disease were present.

Collaboration network of the authors

20 authors · 39 co-authorship links

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  • Universitas Sulawesi Tenggara
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Dewi Retno Sari SaputroAffiliation unknown6
Vika Yugi KurniawanAffiliation unknown2
Sutanto SutantoAffiliation unknown2
Arifah Mufidah LestariAffiliation unknown1
Andjani Ayu Cahaya TanjungAffiliation unknown1
Siti Roqhilu YumarohAffiliation unknown1
Putri WulandariUniversitas Sulawesi Tenggara1
Sela Putri IndriatiAffiliation unknown1
Ghufron Musta'inAffiliation unknown1
Fahri Aimar KusumoAffiliation unknown1
Nabiella Zahra RizkitaAffiliation unknown1
Bayu PurboutomoAffiliation unknown1
Nicolas Ray Amarco TambunanAffiliation unknown1
Yogi Pasca PratamaAffiliation unknown1
Muhammad Bagus SistriatmajaAffiliation unknown1
Beny Trias OktoraAffiliation unknown1
Salju Indara Zeith GeisthAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">SUSCEPTIBLE VACCINATED INFECTED RECOVERED SUSCEPTIBLE MODEL: EQUILIBRIA POINTS AND APPLICATION ON COVID-19 CASE DATA IN INDONESIA</dc:title>
	<dc:creator>Widyaningsih, Purnami</dc:creator>
	<dc:creator>Ivanni, Anas</dc:creator>
	<dc:creator>Kurdhi, Nughthoh Arfawi</dc:creator>
	<dc:description xml:lang="en-US">Severe Respiratory Syndrome Coronavirus-2 is the infectious agent that causes COVID-19. A vaccine program is an effort to stop the spread of COVID-19 infections in Indonesia. The susceptible vaccinated infected recovered susceptible (SVIRS) model can be used to represent the spread of infectious diseases. This study aims to construct the SVIRS model, identify the equilibria points thus apply it to COVID-19 case data in Indonesia, and determine transmission patterns, model accuracy, and interpretation. Literature and applications are the research methodologies employed. First-order nonlinear differential equations form the obtained SVIRS model. The model has two equilibrium points: a disease-free equilibrium point, and the other is endemic equilibrium point. The SVIRS model on the spread of COVID-19 in Indonesia was obtained using daily secondary data from January 11 to November 30, 2022. The model is solved by the fourth-order Runge-Kutta method. The model’s accuracy is accurate enough to explain the spread of COVID-19 in Indonesia with a mean average percentage error (MAPE) value of 43%. According to the transmission pattern, the number of COVID-19 cases in Indonesia peaked on July 27, 2022, then decreased to zero, obtaining an equilibrium point when no more cases of the disease were present.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2024-08-02</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12001</dc:identifier>
	<dc:identifier>10.30598/barekengvol18iss3pp1607-1614</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application; 1607-1614</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol18iss3year2024</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12001/8613</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Purnami Widyaningsih, Anas Ivanni, Nughthoh Arfawi Kurdhi</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>