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All Journal Indonesian Journal of Statistics and Its Applications
Manaf, Silmi Annisa Rizki
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Computer Science & IT Mathematics Other

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Sentiment Analysis of Twitter Users’ Opinion Towards Face-to-Face Learning: Analisis Sentimen Tanggapan Masyarakat Pengguna Twitter terhadap Pembelajaran Tatap Muka Manaf, Silmi Annisa Rizki; Alamudi, Aam; Fitrianto, Anwar
Indonesian Journal of Statistics and Applications Vol 7 No 1 (2023)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i1p15-31

Abstract

In early 2022, the government allowed face-to-face learning again after approximately one year of online learning. When face-to-face learning will be held again in several areas, the number of Covid-19 has increased and the government has imposed the enforcement of restrictions on community activities. The pros and cons of face-to-face learning also occur on social media, one of them is on Twitter. This study used twitter data for January 30th – February 7th 2022. Opinions on twitter regarding face-to-face learning were studied by sentiment analysis using the binary logistic regression method with sentiment classes being positive and negative. Labeling uses based on the final score of the difference between the number of positive and negative words. The purpose of this study is to determine the public’s perception of the policy of implementing face-to-face learning in the era of the Covid-19 on social media especially Twitter. From this study, public’s perception tends to be in a negative direction which indicates that they have not agreed enough with the existence of face-to-face learning in the period of February 2022 with the accuracy was 85%, sensitivity was 77%, specificity was 88%, and AUC was 91%.
Co-Authors Aam Alamudi Fitrianto, Anwar