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All Journal Formosa Journal of Science and Technology (FJST)
Arif Pramudwiatmoko
Department of Enginering, Faculty of Science & Technology, Universitas Teknologi Yogyakarta
Humanities Computer Science & IT Education Industrial & Manufacturing Engineering Social Sciences

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Sentiment Monitoring of Google Maps Reviews Using Naive Bayes and Support Vector Machine at Aveta Hotel Malioboro Rinaldi Hamzah; Arif Pramudwiatmoko
Formosa Journal of Science and Technology Vol. 5 No. 6 (2026): June 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjst.v5i6.95

Abstract

Manual monitoring of hotel customer reviews on Google Maps is increasingly inefficient due to growing review volumes, particularly in detecting negative sentiment. This study proposes a web-based sentiment monitoring system integrated with Naive Bayes and Support Vector Machine (SVM) for automated sentiment classification of Google Maps reviews at Aveta Hotel Malioboro. A dataset of 2,449 historical reviews was collected via DOM scraping and processed through text preprocessing and TF-IDF feature extraction. SVM with minority-class oversampling achieved the highest performance: accuracy 0.9540, precision 0.9514, recall 0.9540, and F1 Score 0.9522. The implemented system retrieves reviews periodically via SerpAPI, classifies sentiment automatically, and delivers real-time Telegram notifications, enabling structured and data-driven hotel review monitoring
Co-Authors Rinaldi Hamzah