Published: 2026-04-01

Perbandingan Metode Naïve Bayes dan Support Vector Machine untuk Klasifikasi Sentimen Ulasan Wisatawan: Studi Kasus Mulia Resort Nusa Dua Bali

DOI: 10.35870/jtik.v10i2.5416

Kiki Setiawan, Humam Mu'asyir
  • Kiki Setiawan: Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
  • Humam Mu'asyir: Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
Cover JTIK VOLUME 10 NO 2 APRIL 2026

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Abstract

The tourism industry requires systems that efficiently capture tourist perceptions. Online reviews on platforms like TripAdvisor provide valuable insights but are challenging to analyze manually due to their volume and diversity. This study develops a sentiment classification model for tourist reviews by comparing Naïve Bayes and Support Vector Machine (SVM). The dataset comprises public reviews of Mulia Resort Nusa Dua Bali, categorized as positive or negative. Text preprocessing includes tokenization, stopword removal, and TF-IDF transformation. Model performance is evaluated using accuracy, precision, recall, and F1-score. The study delivers a ready-to-use sentiment classification model and comparative performance analysis of both algorithms. Findings are expected to identify the more effective method for sentiment analysis of tourist reviews and provide a reference for building recommendation systems and strategic decision-making in the tourism sector.

Keywords

Mulia Resort Hotel ; Naïve Bayes ; Sentiment Analysis ; Support Vector Machine ; TripAdvisor

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How to Cite

Setiawan, K., & Mu'asyir, H. (2026). Perbandingan Metode Naïve Bayes dan Support Vector Machine untuk Klasifikasi Sentimen Ulasan Wisatawan: Studi Kasus Mulia Resort Nusa Dua Bali. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 10(2), 520-529. https://doi.org/10.35870/jtik.v10i2.5416
Article Information

This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.

  • Issue: Vol. 10 No. 2 (2026)

  • Section: Computer & Communication Science

  • Published: %750 %e, %2026

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Author Biographies
Kiki Setiawan
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Fakultas Teknik, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.

Humam Mu'asyir
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Fakultas Teknik, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.

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