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SVEAuAdIR model of COVID-19 Transmission

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 17 No. 1 (2023) · pp. 1–10

DOI
10.22146/ijccs.73334
ISSN
2460-7258, 1978-1520
Published
2023-02-23
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The COVID-19 pandemic that has occurred has received worldwide attention due to the rapid rate of transmission of the outbreak and the large number of deaths that occurred. The aim of this study is to build the SVEAuAdIR model, determine the transmission of COVID-19 in Indonesia by forecast the spread of the disease, and determine the effect of vaccination by looking at the basic reproduction number of SVEAuAdIR model. The results obtained from MAPE on the model are 12%. So it can be said that the SVEAuAdIR model is good for prediction models for the spread of COVID-19. The situation where there are no more individuals infected with COVID-19 is called COVID-19 disease free, thus it is predicted that Indonesia will be free of COVID-19 on October 7, 2021. The target of the Indonesian Ministry of Health is that by the end of 2021 the spread of COVID-19 can be stopped. However, on October 7, 2021, judging from the actual data during this research, there were still new cases of COVID-19. On that day there were 1393 new cases infected with COVID-19. Thus, showing that Indonesia's target of being free of COVID-19 disease by the end of 2021 has not been achieved. The number of the SVEAuAdIR model is in the range of values, which means that the spread of disease is close to disease-free. Based on the results of the value of the SVEAuAdIR model, this study concluded that vaccination could reduce the spread of COVID-19 compared to those who did not vaccinate

Keywords

Collaboration network of the authors

27 authors · 34 co-authorship links · 4 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Gadjah Mada
  • Universitas Teknokrat Indonesia
  • 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
Sigit PriyantaUniversitas Gadjah Mada2
Anifudin AzisUniversitas Gadjah Mada1
Praretno WibowoAffiliation unknown1
Juwita MaharantiAffiliation unknown1
Iqnatius Dimas NugrohoUniversitas Gadjah Mada1
Amelia NursantiUniversitas Gadjah Mada1
Tri Kuntoro PriyambodoUniversitas Gadjah Mada1
Zaied ShouranUniversitas Gadjah Mada1
Nur Azizul HaqimiUniversitas Gadjah Mada1
Friska Ayu ListyaUniversitas Gadjah Mada1
Wahyono WahyonoUniversitas Gadjah Mada1
Riska Amalia PraptiwiUniversitas Gadjah Mada1
Dayan Ramly RamadhanUniversitas Gadjah Mada1
Hendri Kurniawan PrakosaUniversitas Gadjah Mada1
Raymond LuisUniversitas Gadjah Mada1
Sarah Rosdiana TambunanUniversitas Gadjah Mada1
Luthfia Nurma HapsariUniversitas Gadjah Mada1
Reka AlamsyahUniversitas Gadjah Mada1
Debby AlitaUniversitas Teknokrat Indonesia1
Muslikhah MuslikhahAffiliation unknown1
Elih SudiapermanaAffiliation unknown1
Moh Edi WibowoUniversitas Gadjah Mada1
Agus SihabudinAffiliation unknown1
Lukman HeryawanUniversitas Gadjah Mada1
Ahmad RiyadiUniversitas Sulawesi Tenggara1

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://journal.ugm.ac.id/ijccs/oai, first harvested 26 Oct 2026, last seen 1 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">SVEAuAdIR model of COVID-19 Transmission</dc:title>
	<dc:creator>Nisitasari, Anindhita</dc:creator>
	<dc:creator>Rokhman, Nur</dc:creator>
	<dc:subject xml:lang="en-US">Data Science</dc:subject>
	<dc:subject xml:lang="en-US">COVID-19; SVEAuAdIR; Forecasting</dc:subject>
	<dc:description xml:lang="en-US">The COVID-19 pandemic that has occurred has received worldwide attention due to the rapid rate of transmission of the outbreak and the large number of deaths that occurred. The aim of this study is to build the SVEAuAdIR model , determine the transmission of COVID-19 in Indonesia by forecast the spread of the disease, and determine the effect of vaccination by looking at the basic reproduction number  of SVEAuAdIR model. The results obtained from MAPE on the model are 12%. So it can be said that the SVEAuAdIR model is good for prediction models for the spread of COVID-19. The situation where there are no more individuals infected with COVID-19 is called COVID-19 disease free, thus it is predicted that Indonesia will be free of COVID-19 on October 7, 2021. The target of the Indonesian Ministry of Health is that by the end of 2021 the spread of COVID-19 can be stopped . However, on October 7, 2021, judging from the actual data during this research, there were still new cases of COVID-19. On that day there were 1393 new cases infected with COVID-19. Thus, showing that Indonesia's target of being free of COVID-19 disease by the end of 2021 has not been achieved. The  number of the SVEAuAdIR model is in the range of values , which means that the spread of disease is close to disease-free. Based on the results of the  value of the SVEAuAdIR model, this study concluded that vaccination could reduce the spread of COVID-19 compared to those who did not vaccinate</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US">Master Program of Computer Science, Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta</dc:contributor>
	<dc:date>2023-02-23</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/73334</dc:identifier>
	<dc:identifier>10.22146/ijccs.73334</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 17, No 1 (2023): January; 1-10</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/73334/35774</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>