Sentiment Analysis Of The Clash Of Champions Event By Ruangguru With The Naïve Bayes Method - Yuniar Farida; Rofina Muti’atun Khasanah Khasanah (JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING, 2026)
The rapid development of information technology has encouraged people to actively express their opinions through social media platforms, including X (formerly Twitter). One topic that has attracted considerable public attention is Clash of Champions, an academic competition organized by Ruangguru. This study aims to analyze X users’ sentiments toward the Clash of Champions event and evaluate the performance of the Naïve Bayes method in classifying these sentiments. The dataset consisted of 5,121 tweets collected through a crawling process using Google Colab from June to November 2024. The data were subjected to preprocessing and represented using Term Frequency–Inverse Document Frequency (TF-IDF) weighting before being classified into positive and negative sentiment categories using the Naïve Bayes algorithm. The results indicate that most tweets expressed positive sentiment, suggesting that Clash of Champions received favorable public responses. The classification model achieved an accuracy of 89.74%, a precision of 91.94%, a recall of 86.91%, and an F1-score of 89.34%. These findings demonstrate that the Naïve Bayes method is effective for analyzing public sentiment on social media. This study contributes empirical evidence regarding public perceptions of educational competition programs and supports the application of Naïve Bayes for sentiment classification in Indonesian social media data.