<![CDATA[Mikie Holiday Funland is one of the tourist destinations in North Sumatra that receives numerous visitor reviews through digital platforms such as Google Maps and TikTok. The large number of available reviews makes manual analysis less effective, creating the need for sentiment analysis to identify visitors' perceptions of the facilities and services provided. This study aims to classify visitor reviews of Mikie Holiday Funland into positive, negative, and neutral sentiment categories using the Naïve Bayes method. This research adopted the CRISP-DM framework, with data processing stages including text preprocessing, lexicon-based sentiment labeling, TF-IDF weighting, and classification using the Naïve Bayes algorithm. The data used in this study were collected from Google Maps reviews and TikTok comments from February 2025 to February 2026, totaling 4,876 reviews. Model evaluation was conducted using a confusion matrix and classification report. The results showed that the Naïve Bayes method achieved an accuracy of 73% in classifying review sentiments. Of the 4,876 reviews analyzed, 849 reviews (17.4%) were classified as positive, 1,466 reviews (30.1%) as negative, and 2,561 reviews (52.5%) as neutral. The dominance of neutral sentiment indicates that most reviews were informative and did not express strong opinions. Furthermore, the analysis results were successfully implemented in a Streamlit-based application to provide interactive sentiment visualizations. These findings are expected to serve as evaluation material for improving the quality of tourism facilities and services, as well as a source of information for prospective visitors in making decisions about visiting Mikie Holiday Funland.]]>
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