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Elis Khatizah
Mathematics Study Program, School of Data Science, Mathematics and Informatics, IPB University, West Java, 16680, Indonesia
Computer Science & IT Control & Systems Engineering Mathematics

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The Similarity of COVID-19-Related Profiles and Pandemic Conditions in ASEAN Countries Elis Khatizah
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol. 22 No. 2 (2025): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Program Studi Ilmu Komputer, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v22i2.35

Abstract

Abstract Abstract This paper examines the potential relationship between countries’ profiles and COVID-19conditions in 10 ASEAN countries, focusing on new confirmed cases and deaths. We initially clusteredthe countries based on demographic profiles and then observed the pandemic situation within each cluster.The samples of genome sequence, particularly the Omicron variant collected from each country, are alsoclustered to investigate the spread of the virus. Furthermore, we created a simple algorithm to identifycountries with profiles similar to ASEAN nations. Our findings show that countries with similardemographic profiles and geographically proximate are more likely to experience similar pandemicconditions even though they have no identical genome sequence of the virus. Five of the 10 ASEANcountries have similar demographic profiles to countries within the ASEAN region and as assumed,experienced similar COVID-19 situations. Conversely, the remaining ASEAN countries, which shareprofiles with countries outside the region, demonstrate fairly different COVID-19 conditions, particularlywith regard to the timing of the spread of the virus. With comparable resources at hand, insights fromcountries with similar profiles provide valuable information for effective pandemic management effortsin the future.Keywords: ASEAN profiles; clustering; COVID-19; demographic; pandemic management
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