KLASIFIKASI KOMENTAR NETIZEN X TENTANG PEMECATAN SHIN TAE YONG DARI PSSI DENGAN ALGORITMA NAIVE BAYES
DOI:
https://doi.org/10.36080/skanika.v9i1.3605Keywords:
confusion matrix, multinomial naive bayes, sentiment analysis, text mining, xAbstract
The dismissal of the Indonesian National Football Team head coach, Shin Tae-yong, generated diverse public reactions on the social media platform X. The large volume and variability of netizen comments require a systematic analysis to objectively understand public opinion. This study aims to analyze the sentiment of netizen comments regarding the dismissal of Shin Tae-yong using a text mining approach and the Multinomial Naive Bayes algorithm. The data were collected from social media X through a crawling process and subsequently processed through preprocessing stages and TF-IDF weighting. The classification results demonstrate that the proposed model achieved good performance, with an accuracy of 91.3%, precision of 94.94%, recall of 79.43%, and an F1-score of 85.4%. The prediction results were dominated by negative sentiments (275 instances), followed by positive (40 instances) and neutral sentiments (30 instances). These findings indicate that public opinion tends to be predominantly negative toward the decision, while the classification model effectively categorizes sentiments. This study is expected to serve as a reference for understanding public opinion in national sports issues and to support data-driven decision-making.
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