FALAAH, ICHLASUL (2021) ANALISIS SENTIMEN OPINI PUBLIK TERHADAP KEBIJAKAN PEMBELAJARAN DARING SELAMA PANDEMI COVID-19 PADA TWITTER MENGGUNAKAN METODE NAÏVE BAYES. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
ANALYSIS OF PUBLIC OPINION SENTIMENT ON ONLINE LECTURE POLICY DURING THE COVID-19 PANDEMIC ON TWITTER USING NAÏVE BAYES METHOD ICHLASUL FALAAH Department of Informatics, Faculty of Science & Technology University of Technology Yogyakarta North Ringroad St., Jombor Sleman Yogyakarta E-mail: ichlasulfalah@gmail.com ABSTRACT Indonesia is one of the countries affected by the Covid-19 pandemic. The Covid-19 pandemic has caused Indonesia to also issue several appeals to the public, such as calls for online learning carried out by all educational institutions in Indonesia. Online learning is a new method and is not yet commonly used in Indonesian universities, taken from a student's perspective. Of course, every student has their views, opinions, or aspirations regarding online learning that is currently being held. Social media is a suitable place to share one's opinions or aspirations, which an example of social media as a place to share one's opinion is Twitter. This study aims to create a system that can analyze sentiments regarding online learning policies during the Covid-19 pandemic on Twitter in Indonesia using the Naive Bayes method. A series of stages were carried out in this study, namely data collection from Twitter, preprocessing, the classification process using the Naive Bayes method, and performance evaluation. From the test results with a confusion matrix, an accuracy value of 84% is obtained with the details of precision 0.84, recall 0.84, and F1 Score 0.83 with a dataset of 10000 tweets divided into training and testing data with a division ratio of 80:20. From this research, it can be concluded that the Naïve Bayes method can be applied to analyze sentiment towards online learning policies on Twitter Indonesia. Keywords: Sentiment Analysis, Online Learning, Naïve Bayes, Twitter.
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 29 Oct 2021 01:22 |
| Last Modified: | 29 Oct 2021 01:22 |
| URI: | http://eprints.uty.ac.id/id/eprint/8597 |
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