Sentiment Analysis Of Public Opinions On The Effectiveness Of Online Learning Using Naïve Bayes Algorithm

  • Ratna Pinka Baptis Dakhi Universitas Nusa Mandiri
  • Achmad Maezar Bayu Aji Universitas Nusa Mandiri

Abstract

Covid-19 was declared a global pandemic by the World Health Organization (World Health Organization) on March 11, 2020. This has resulted in the government urging the public not to carry out activities outside the home which is an effort to break the chain of spreading Covid-19. Activities that were suddenly stopped had a negative impact on the community. Starting from the decline in economic growth to the lagging  of students  in  studying.  The Covid-19  pandemic has  had  an  impact  on various perspectives of human life today, especially in the field of education. So that the teaching and learning process continues. All students are required to study at home online or online. However, online learning raises pros and cons among the public,  so  research  needs  to  be  done  to  analyze  public  sentiment  about  online learning and find out the effectiveness of online learning during the Covid-19 pandemic by utilizing Twitter as a source of data to be researched. Based on the results of the analysis of public opinion sentiment about online learning using the Naïve Bayes Classifier  algorithm with Rapidminer as the software used in data processing, the accuracy value is 60.00% with 65.67% precision and 53.30% recall

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Author Biographies

Ratna Pinka Baptis Dakhi, Universitas Nusa Mandiri

Faculty of Information Technology

Achmad Maezar Bayu Aji, Universitas Nusa Mandiri

Faculty of Information Technology

References

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Published
2022-06-17
How to Cite
DAKHI, Ratna Pinka Baptis; BAYU AJI, Achmad Maezar. Sentiment Analysis Of Public Opinions On The Effectiveness Of Online Learning Using Naïve Bayes Algorithm. JISICOM (Journal of Information System, Informatics and Computing), [S.l.], v. 6, n. 1, p. 273-279, june 2022. ISSN 2597-3673. Available at: <https://journal.stmikjayakarta.ac.id/index.php/jisicom/article/view/822>. Date accessed: 29 mar. 2024. doi: https://doi.org/10.52362/jisicom.v6i1.822.