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  5. Analysis of public sentiment on Covid-19 vaccination policy based on text mining with the Naïve Bayes Classifier approach
 
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Analysis of public sentiment on Covid-19 vaccination policy based on text mining with the Naïve Bayes Classifier approach

Journal
Applied Mathematics and Computational Intelligence (AMCI)
Date Issued
2021-12
Author(s)
Rita Susanti
Universitas Airlangga
Alvito Aryo Pangestu
Universitas Airlangga
Haydar Arsy Firdaus
Universitas Airlangga
M. Fariz Fadillah Mardianto
Universitas Airlangga
Handle (URI)
https://amci.unimap.edu.my/
https://ejournal.unimap.edu.my/index.php/amci/article/view/172/138
https://hdl.handle.net/20.500.14170/2975
Abstract
One of the goals in the SDGs, which is to ensure a healthy life and promote the welfare of all people of all ages, has become difficult to maintain since the emergence of Covid-19 in Indonesia. Thus, the Indonesian government has issueda policy regarding the procurement of vaccines and the implementation of vaccinations through Presidential Regulation Number 99 of 2020. Meanwhile, the public's perception of the Covid-19 vaccine that appears are variesandwill affect the Covid-19 vaccination process in Indonesia, so a sentiment analysis needs to be carried out to free Indonesia from the Covid-19 pandemic. By using the text mining method, the primary data collected is in the form of public opinions from Twitter. With the Naïve Bayes Classifier approach, it is concluded that the model is consistent and good enough to be used to classify public sentiment regarding the Covid-19 vaccination policy.
Subjects
  • Naïve Bayes Classifie...

  • Sentiment

  • Twitter

  • Text mining

File(s)
Analysis of Public Sentiment on Covid-19 Vaccination Policy Based.pdf (384.36 KB)
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Mar 5, 2026
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Acquisition Date
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