Analisis Sentimen Pada Pembelajaran Daring Di Indonesia Melalui Twitter Menggunakan Naïve Bayes Classifier

Authors

  • Ida Bagus Gede Sarasvananda Institut Bisnis dan Teknologi Indonesia
  • Diana Selivan Institute Bisnis dan Teknologi Indonesia
  • Made Leo Radhitya Institute Bisnis dan Teknologi Indonesia
  • I Nyoman Tri Anindia Putra Institute Bisnis dan Teknologi Indonesia

DOI:

https://doi.org/10.31598/sintechjournal.v5i2.1241

Keywords:

sentiment analysis, twitter, naïve bayes classifier

Abstract

Education is one of the areas most affected by the covid-19 pandemic. Education during the pandemic must continue. To reduce the spread of covid-19 and learning activities can run as usual, the government, in this case the Ministry of Education and Culture, has implemented a distance education system in Indonesia. In addition, the response from the community is very important for an evaluation of the applied online learning. With the implementation of the policy regarding online learning in Indonesia, it is necessary to conduct a sentiment analysis to find out how the responses, opinions, or comments from the public and online learning actors related to online learning are currently being implemented. So the author conducted a research entitled Sentiment Analysis on Online Learning in Indonesia Through Twitter Using the Naïve Bayes Classifier Method to measure student responses regarding online learning during the covid -19 pandemic in Indonesia. The results of the accuracy of this study is 99.8% and the classification error is 0.12%. Of the total data entered, 83 tweets or 20% were included in the positive class, the negative class was 317 tweets or 80%.

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Published

2022-10-28

Issue

Vol. 5 No. 2 (2022): SINTECH Journal Edition Oktober 2022

Section

Articles

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Copyright (c) 2022 Ida Bagus Gede Sarasvananda, Diana Selivan, Made Leo Radhitya, I Nyoman Tri Anindia Putra

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