<![CDATA[Digital tourism applications have become an essential component of contemporary travel experiences, influencing how tourists search for information, make reservations, and evaluate services. Although various theoretical studies emphasize the role of digital platforms in enhancing tourist satisfaction, there remains a gap between these theoretical expectations and empirical evidence derived from large-scale user-generated content, particularly in the context of tourism applications in developing countries. This study aims to analyze user satisfaction with the Traveloka application by examining online reviews through sentiment analysis in order to bridge this gap between theory and actual user experiences. The research employed a quantitative descriptive approach combined with sentiment analysis techniques. Data were collected from user reviews on the Google Play Store, where an initial dataset of 2,500 reviews was filtered to obtain 516 tourism-related reviews for analysis. The instruments used in this study included text preprocessing procedures, a sentiment classification model, frequency-based keyword analysis, and statistical tests to examine the relationship between user sentiment and rating levels. The results show that positive sentiment dominates user reviews, accounting for 71.23% of the data, followed by negative sentiment at 26.03% and neutral sentiment at 2.74%, supported by an average rating of 3.89 and a median rating of 5. Dominant positive expressions highlight ease of use, fast service, affordable prices, and convenience in booking, while negative sentiment is mainly associated with refund issues, payment systems, account access, and booking cancellations. The chi-square test confirms a significant relationship between sentiment and user ratings (χ² = 1022.00; p < 0.001). In conclusion, while Traveloka is generally perceived as a reliable and user-friendly tourism application, improving service quality in transaction handling and post-purchase processes is crucial to enhancing overall user satisfaction.]]>
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