<![CDATA[This study analyzes the sentiment of Sriwijaya FC supporters toward the club's management through comments on Instagram. Data was collected from 6,601 comments on the official @SriwijayaFC account and processed through text preprocessing stages with an 80:20 split for training and testing data. The analysis was conducted using four machine learning algorithms: SVM, Random Forest, Naïve Bayes, and KNN. The results indicate that neutral sentiment dominates (50.92%), followed by positive (25.07%) and negative (24.01%) sentiment, suggesting that most comments are informative or impartial, although there are both supporting and opposing opinions. Model performance evaluation using a confusion matrix and accuracy, precision, recall, and F1-score metrics shows that SVM achieved the highest accuracy (89%), followed by Random Forest (82%), Naïve Bayes (74%), and KNN (65%). These findings demonstrate that machine learning is effective in classifying social media sentiment. Future research may explore deep learning algorithms and expand data sources to other platforms for a more comprehensive analysis.]]>
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