A Prediction Study about the Pandemic Era based on Machine Learning Methods

dc.authorscopusid57213371849
dc.authorscopusid58178788900
dc.authorscopusid58179020200
dc.authorscopusid58178988900
dc.contributor.authorEryılmaz, Meltem
dc.contributor.authorKara, Erdi
dc.contributor.authorErtan,Ö.
dc.contributor.authorKara,E.
dc.contributor.otherMathematics
dc.contributor.otherComputer Engineering
dc.date.accessioned2024-07-05T15:46:00Z
dc.date.available2024-07-05T15:46:00Z
dc.date.issued2021
dc.departmentAtılım Universityen_US
dc.department-tempEryılmaz M., Atılım University, Ankara, Turkey; Yalçınkaya F., Atılım University, Ankara, Turkey; Ertan Ö., Atılım University, Ankara, Turkey; Kara E., Atılım University, Ankara, Turkeyen_US
dc.description.abstractCoronavirus pandemic has been going on since late 2019, millions of people died worldwide, vaccination has recently started in many countries and new strategies are sought by countries since they are still struggling to defeat the virus. So, this research is made to predict the possible ending time of the coronavirus pandemic in Turkey using data mining and statistical studies. Data mining is a computer science study that processes large amounts of data and produces new useful information. It is especially used to support decision making in companies today. So, this project could support the decision making of authorities in developing an effective strategy against the on-going pandemic. During the research we have practiced on Turkey’s coronavirus and vaccination data between 13 January 2021 and 28 May 2021. We used Rapidminer and the Random Forest method for data mining. After all the simulations we have applied and observed during our research, it was clearly seen that vaccination parameters were decreasing the new cases. Also, the stringency index did not affect the new cases. As a conclusion of our research and observations, we think that the government should vaccinate as many people as it can in order to relax restrictions for the last time. © 2021 Authors. All rights reserved.en_US
dc.identifier.citation0
dc.identifier.doi10.17762/ijritcc.v9i12.5492
dc.identifier.endpage7en_US
dc.identifier.issn2321-8169
dc.identifier.issue12en_US
dc.identifier.scopus2-s2.0-85152204470
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.17762/ijritcc.v9i12.5492
dc.identifier.urihttps://hdl.handle.net/20.500.14411/4000
dc.identifier.volume9en_US
dc.language.isoenen_US
dc.publisherAuricle Global Society of Education and Researchen_US
dc.relation.ispartofInternational Journal on Recent and Innovation Trends in Computing and Communicationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCovid-19en_US
dc.subjectdata miningen_US
dc.subjectrandom foresten_US
dc.subjectrapid mineren_US
dc.titleA Prediction Study about the Pandemic Era based on Machine Learning Methodsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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