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All Journal Journal of Information System Exploration and Research
Auliya Rahman Isnain Isnain
Departmentof Engineering and Computer Science, Universitas Teknokrat Indonesia, Indonesia

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Analysis of the Sentiment of Tourist Reviews on Google Maps Towards Tourist Villages in Lampung Province Using the Naïve Bayes Method Achmad Jundi Al Falah; Auliya Rahman Isnain Isnain
Journal of Information System Exploration and Research Vol. 4 No. 3: July 2026
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v4i3.101

Abstract

Background: Tourist reviews provide information for evaluating visitor experiences and tourism village development. Objective: This study analyzes tourist sentiment toward tourism villages in Lampung Province using Google Maps reviews and Naive Bayes classification. Methods: A total of 2,847 reviews were collected from nine developed tourism villages registered in the Tourism Village Network. Data were preprocessed, transformed into textual features, and classified using Naive Bayes with 80% training and 20% testing data. Results: Positive sentiment accounted for 73.38% of reviews, neutral 17.98%, and negative 8.64%. The Naive Bayes model achieved 81.56% accuracy with good precision, recall, and F1-score, particularly for the positive class. Tourist satisfaction factors included natural beauty (28.46%), community friendliness (22.38%), affordable prices (18.92%), cleanliness (15.67%), and adequate facilities (14.57%). Dissatisfaction concerned accessibility and road conditions (31.71%), inadequate facilities (26.83%), site cleanliness (19.51%), and entrance ticket prices (14.23%). Conclusion: Text-mining-based sentiment analysis effectively captures tourist perceptions and identifies priorities for tourism village improvement, particularly infrastructure, facilities, cleanliness, and community service training for satisfying and sustainable tourism experiences.
Co-Authors Achmad Jundi Al Falah