<![CDATA[This research employs the CRISP-DM framework to analyze digital engagement through travel vlog content, explicitly focusing on vlogs about Gili Trawangan. The study systematically follows the CRISP-DM phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Utilizing the VADER sentiment analysis model and the SVM algorithm with SMOTE, the research achieves a high level of accuracy in sentiment classification, with the SVM model demonstrating an accuracy of 88.57% +/- 5.11% and a precision of 90.95% +/- 5.09%. Analysis of 442 cleaned and labeled data points reveals a strong dominance of positive sentiments, with 62.61% in the first video and 84.25% in the second video. These findings underscore the effectiveness of travel vlogs in engaging viewers and generating positive interactions as powerful tools for tourism marketing. The study concludes that the CRISP-DM framework is highly effective in facilitating comprehensive sentiment analysis and enhancing strategic tourism marketing initiatives.]]>
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