Sentiment Analysis of the COVID-19 Booster Vaccine with the Naïve Bayes Algorithm
Analisis Sentimen Vaksin Booster COVID-19 dengan Algoritme Naïve Bayes
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(1) * Dyah Retno Utari
Universitas Budi Luhur Jakarta
Indonesia
(*) Corresponding Author
Abstract
In early 2020, a new deadly virus was discovered that can spread quickly, called SARS-CoV-2 or Coronavirus Disease 2019 (COVID-19). Indonesia is a country with a relatively high number of survivors of COVID-19. The success of the Indonesian government in providing massive COVID-19 vaccinations can minimize the risk of death. The World Health Organization (WHO) stated it would revoke the Public Health Emergency of International Concern (PHEIC) status for COVID-19 in May 2023. However, many positive cases of Covid-19 were still found in Indonesia. Most of them are survivors who have not carried out complete vaccinations until they get a booster vaccine. This study analyzes public sentiment about booster vaccines in Indonesia using the Naïve Bayes classification algorithm. The results showed that the classification modeling accuracy had an excellent value of 97.51%. In contrast, based on the analysis results, the number of words that frequently appeared in the twelve highest word cloud visualization results found tokens that had positive sentiment values.
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References
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Copyright (c) 2023 Dyah Retno Utari
This work is licensed under a Creative Commons Attribution 4.0 International License.
