Rahayu, Anggelia Dwi (2025) SENTIMENT ANALYSIS OF PUBLIC PERCEPTION OF BINUS SERPONG STUDENT BULLYING CASE USING NAÏVE BAYES METHOD. Tugas Akhir thesis, Informatics.
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Abstract
Public sentiment analysis of the bullying case at SMA Binus Serpong was conducted using the Naïve Bayes method, a widely recognized technique in text classification. Bullying in schools is a serious issue that significantly impacts the psychological well-being and academic development of victims. This study explores the emotional patterns of netizens in response to the case through interactions on social media, particularly YouTube, which is a popular platform for sharing opinions and comments. The objective of this study is to determine whether netizens’ responses to the bullying case are predominantly positive, negative, or neutral, as well as to evaluate the effectiveness of the Naïve Bayes algorithm in sentiment classification. The analysis process in this study consists of several stages, including data crawling, data preprocessing, and data classification. Data were collected from 2,259 YouTube comments related to the bullying case at SMA Binus Serpong. Preprocessing involved text cleaning and normalization to prepare the data for analysis. The processed comments were then classified using Complement Naïve Bayes and Multinomial Naïve Bayes, which were integrated with TF-IDF in the classification pipeline. The results of the analysis showed that the classification model used achieved an accuracy of 80.47%. Negative sentiment dominates with 72.2%, followed by positive sentiment (20.7%) and neutral sentiment (0.7%). The evaluation also shows that negative sentiment has a precision of 0.81, a recall of 0.93 and an f1-score of 0.87. Positive sentiment has a precision of 0.67, recall of 0.40, and f1-score of 0.50, while neutral sentiment has a precision of 0.70, recall of 0.43, and f1-score of 0.53. Keywords: Sentiment analysis, bullying, public perception, Naïve Bayes, YouTube
| 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: | 06 May 2025 04:15 |
| Last Modified: | 06 May 2025 04:15 |
| URI: | http://eprints.uty.ac.id/id/eprint/17823 |
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