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Modeling Simulation of COVID-19 in Indonesia based on Early Endemic Data

Communication in Biomathematical Sciences · Vol. 3 No. 1 (2020) · pp. 1–8

DOI
10.5614/cbms.2020.3.1.1
ISSN
2549-2896
Published
2020-04-17
Publisher
The Indonesian Bio-Mathematical Society
Language
eng

Abstract

The COVID-19 pandemic has recently caused so much anxiety and speculation around the world. This phenomenon was mainly driven by the drastic increase in the number of infected people with the COVID-19 virus worldwide. Here we propose a simple model to predict the endemic in Indonesia. The model is based on the Richard's Curve that represents a modified logistic equation. Based on the similar trends of initial data between Indonesia and South Korea, we use parameter values that are obtained through parameter estimation of the model to the data in South Korea. Further, we use a strict assumption that the implemented strategy in Indonesia is as effective as in South Korea. The results show that endemic will end in April 2020 with the total number of cases more than 8000.

Keywords

Collaboration network of the authors

40 authors · 117 co-authorship links · 2 across different organisations · showing the 40 most connected

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  • Bandung Institute of Technology
  • National Research and Innovation Agency
  • Institut Teknologi Kalimantan
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Muhammad FakhruddinAffiliation unknown5
Edy SoewonoAffiliation unknown3
Hadi SusantoNational Research and Innovation Agency3
Roberd SaragihBandung Institute of Technology2
Dewi HandayaniBandung Institute of Technology2
Dewi SuhikaBandung Institute of Technology2
Retno Wahyu DewantiInstitut Teknologi Kalimantan2
Wisnu Prasojo WidiantoAffiliation unknown2
Mia Siti KhumaerohAffiliation unknown1
Karunia Putra WijayaAffiliation unknown1
Ilham Saiful FauziAffiliation unknown1
Yenie SyukriyahAffiliation unknown1
Rudy KusdiantaraAffiliation unknown1
Vania Mene RisrianiAffiliation unknown1
Tjandra AnggraeniAffiliation unknown1
Anita TriskaAffiliation unknown1
Mona ZevikaAffiliation unknown1
Glenn Lahodny Jr.Affiliation unknown1
. FaridaAffiliation unknown1
Hilda FahlenaAffiliation unknown1
Widya OktavianaAffiliation unknown1
. SudirmanAffiliation unknown1
DILA PUSPITAAffiliation unknown1
Agus HasanAffiliation unknown1
Yuki NasutionAffiliation unknown1
Endah PutriAffiliation unknown1
Venansius TjahjonoAffiliation unknown1
Kamal SukandarAffiliation unknown1
WidyastutiAffiliation unknown1
NadiaAffiliation unknown1
Chai Jian TayAffiliation unknown1
Afdol ZikriAffiliation unknown1
Sila RizqinaAffiliation unknown1
Kamal Khairudin SukandarAffiliation unknown1
SeprianusAffiliation unknown1
Suhadi Wido SaputroAffiliation unknown1
Stefanus Raynaldo SeptyawanAffiliation 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) http://journals.itb.ac.id/index.php/cbms/oai, first harvested 8 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Modeling Simulation of COVID-19 in Indonesia based on Early Endemic Data</dc:title>
	<dc:creator>Nuraini, Nuning</dc:creator>
	<dc:creator>Khairudin, Kamal</dc:creator>
	<dc:creator>Apri, Mochamad</dc:creator>
	<dc:subject xml:lang="en-US">mathematical model</dc:subject>
	<dc:subject xml:lang="en-US">COVID-19</dc:subject>
	<dc:subject xml:lang="en-US">Richard’s curve</dc:subject>
	<dc:subject xml:lang="en-US">Indonesia.</dc:subject>
	<dc:description xml:lang="en-US">The COVID-19 pandemic has recently caused so much anxiety and speculation around the world. This phenomenon was mainly driven by the drastic increase in the number of infected people with the COVID-19 virus worldwide. Here we propose a simple model to predict the endemic in Indonesia. The model is based on the Richard's Curve that represents a modified logistic equation. Based on the similar trends of initial data between Indonesia and South Korea, we use parameter values that are obtained through parameter estimation of the model to the data in South Korea. Further, we use a strict assumption that the implemented strategy in Indonesia is as effective as in South Korea. The results show that endemic will end in April 2020 with the total number of cases more than 8000.</dc:description>
	<dc:publisher xml:lang="en-US">The Indonesian Bio-Mathematical Society</dc:publisher>
	<dc:date>2020-04-17</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">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/cbms/article/view/13395</dc:identifier>
	<dc:identifier>10.5614/cbms.2020.3.1.1</dc:identifier>
	<dc:source xml:lang="en-US">Communication in Biomathematical Sciences; Vol. 3 No. 1 (2020); 1-8</dc:source>
	<dc:source>2549-2896</dc:source>
	<dc:source>10.5614/cbms.2020.3.1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/cbms/article/view/13395/4641</dc:relation>
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