This study aims to analyze the sentiment of visitor comments on the Tjong A Fie Mansion tourist attraction in Medan City using the Naïve Bayes Classifier method. A total of 100 comments were manually collected from Google Maps and underwent preprocessing stages, including case folding, tokenization, stopword removal, and stemming. Feature extraction was then performed using the TF-IDF method, followed by classification using the Multinomial Naïve Bayes algorithm. Model performance was evaluated using a confusion matrix. The test results showed that a data split of 80% for training and 20% for testing yielded the highest accuracy, reaching 80%, with a sentiment classification result of 100% positive. These findings indicate that the Naïve Bayes method can effectively and efficiently classify text-based comments. The sentiment analysis results are expected to provide input for tourism managers to improve service quality and serve as a reference for the development of user opinion-based decision support systems.
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