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Clustering and Forecasting of Covid-19 Data in Indonesia

Jurnal Matematika, Statistika dan Komputasi · Vol. 18 No. 3 (2022) · pp. 324–335

DOI
10.20956/j.v18i3.18882
ISSN
2614-8811, 1858-1382
Published
2022-05-15
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

Indonesia reported its first case of Covid-19 in March 2020, which was suspected to have been infected by a foreigner who visited Indonesia. The distribution of cases that occurred in Indonesia has an uneven frequency considering that Indonesia is an archipelagic country, in the analysis of Covid-19 cases in Indonesia, there are many provinces and some have the same pattern of case characteristics. time series so that forecasting analysis can be used. So that clustering analysis and forecasting of Covid-19 data can be used in Indonesia. The analysis was carried out with 2 stages of analysis, namely clusters using the clustering hierarchy method and forecasting using the ARIMA method. By using 288 data from January 1, 2021 – October 15, 2021, the results show that the daily Covid-19 cases by province in Indonesia can be grouped into 2 clusters, in the forecasting analysis only one province is taken from each cluster used in determining the model, cluster 1 used data from the province of Banten and cluster 2 used data from the province of West Java. By using R software, a model for each cluster is obtained, namely ARIMA(0,1,1) for cluster 1 and ARIMA(2,1,2) for cluster 2. From the forecasting results obtained data until October 30, 2021 shows the number of cases tends to be constant.

Keywords

Collaboration network of the authors

12 authors · 26 co-authorship links · 2 across different organisations

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

  • IPB University
  • Bandung Islamic University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Winalia AgwilAffiliation unknown2
Nurul HidayatiAffiliation unknown1
Bagus SartonoIPB University1
Eni MeylisahAffiliation unknown1
Dyah Setyo RiniAffiliation unknown1
Agus Mohamad SolehIPB University1
Khairil Anwar NotodiputroBandung Islamic University1
Erfiani ErfianiAffiliation 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://journal.unhas.ac.id/index.php/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Clustering and Forecasting of Covid-19 Data in Indonesia</dc:title>
	<dc:creator xml:lang="en">Astuti, Diyah </dc:creator>
	<dc:creator xml:lang="en">hartanti, Dyah Yunita </dc:creator>
	<dc:creator xml:lang="en">Nurhayanti, Susi Tri  </dc:creator>
	<dc:creator xml:lang="en">Fransiska, Herlin </dc:creator>
	<dc:subject xml:lang="en">Covid-19</dc:subject>
	<dc:subject xml:lang="en">Clustering</dc:subject>
	<dc:subject xml:lang="en">Forecasting</dc:subject>
	<dc:subject xml:lang="en">Provinsi</dc:subject>
	<dc:subject xml:lang="en">Indonesia</dc:subject>
	<dc:description xml:lang="en">Indonesia reported its first case of Covid-19 in March 2020, which was suspected to have been infected by a foreigner who visited Indonesia. The distribution of cases that occurred in Indonesia has an uneven frequency considering that Indonesia is an archipelagic country, in the analysis of Covid-19 cases in Indonesia, there are many provinces and some have the same pattern of case characteristics. time series so that forecasting analysis can be used. So that clustering analysis and forecasting of Covid-19 data can be used in Indonesia. The analysis was carried out with 2 stages of analysis, namely clusters using the clustering hierarchy method and forecasting using the ARIMA method. By using 288 data from January 1, 2021 – October 15, 2021, the results show that the daily Covid-19 cases by province in Indonesia can be grouped into 2 clusters, in the forecasting analysis only one province is taken from each cluster used in determining the model, cluster 1 used data from the province of Banten and cluster 2 used data from the province of West Java. By using R software, a model for each cluster is obtained, namely ARIMA(0,1,1) for cluster 1 and ARIMA(2,1,2) for cluster 2. From the forecasting results obtained data until October 30, 2021 shows the number of cases tends to be constant.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2022-05-15</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/18882</dc:identifier>
	<dc:identifier>10.20956/j.v18i3.18882</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 18 No. 3 (2022): MAY, 2022; 324-335</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/18882/8136</dc:relation>
	<dc:relation>10.20956/j.v18i3.18882.g8136</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2022 Author and publisher</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
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