Sentiment Analysis of Tweets About Allowing Outdoor Mask Wear Using Naïve Bayes and TextBlob

Authors

  • Ilham Firman Ashari Institut Teknologi Sumatera
  • Fadhillah A Institut Teknologi Sumatera
  • M. Daffa Institut Teknologi Sumatera
  • Sekar A Institut Teknologi Sumatera

DOI:

https://doi.org/10.33022/ijcs.v12i3.3238

Keywords:

Covid-19, Naive Bayes, Sentiment Analysis, Text Mining

Abstract

Covid-19, a virus that attacks the respiratory tract and has a fairly high mortality rate, has spread throughout the country. On March 11, 2020, WHO declared Covid-19 a global pandemic. The government is trying various efforts to reduce the number of sufferers of this virus. Starting from the implementation of the lockdown, PPKM, to making Government Regulations related to the use of masks and so on for personal protection. In June 2021, there was a spike in Covid-19 cases in Indonesia and Covid-19 patients increased drastically. Conditions at that time were very chaotic, and left trauma for some people. On May 17, 2022, the government made concessions in the use of masks in open spaces while maintaining social distance. Even though masks play an important role in preventing the spread of the virus. With this, a research related to "Analysis of Sentiment on Tweets regarding Allowance for the Use of Masks in Outdoors using Naive Bayes was carried out" to find out public opinion. The research was conducted using Text Mining through Twitter sentiment and Naive Bayes for classification. Based on research, the majority of twitter users give a neutral response. This is indicated by the number of neutral sentiments of 75.76% or about 757 tweets. The data used in this study, namely 1000 Indonesian tweets with the keyword 'jokowi mask'. Testing data of 20% resulted in a more accurate model, which resulted in an accuracy of about 85%, while the model using testing data of 30% only produced an accuracy of about 83%.

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Published

30-06-2023