Guest Sentiment Analysis Based on Online Reviews to Optimize Guest Satisfaction at Hotel X
DOI:
https://doi.org/10.55606/bijmt.v5i2.4442Keywords:
Sentiment Analysis, TripAdvisor, Guest Satisfaction, Naïve Bayes, Hotel ManajementAbstract
Tourism has become one of the largest and fastest-growing industries globally. Advances in technology and communication have brought significant changes in various aspects, especially in the hospitality industry. Using a dataset from November 2024 to January 2025, this sentiment analysis was conducted using the Naive Bayes classification method (Gaussian, Multinomial, and Bernoulli). The results show that 72.99% of reviews are positive, while 19.08% are negative and 7.93% are neutral. The Naive Bayes model demonstrates high accuracy in classifying positive sentiment but exhibits differences in classification accuracy for the negative and neutral categories due to class imbalance. Occupancy data reveals a peak in 2023 and a significant decline in 2024. This study reveals the importance of ongoing sentiment analysis to establish management strategies, address service gaps, and improve guest satisfaction, which aims to improve guest satisfaction in the competitive hospitality market.
References
1. Alnsour, Y. (2018). The effect of social media marketing on consumers’ satisfaction. International Journal of Business and Management Invention, 7(3), 44–51.
2. Antara, M., & Sumarniasih, M. S. (2017). Role of tourism in economy of Bali and Indonesia. Journal of Tourism and Hospitality Management, 5(2). https://doi.org/10.15640/jthm.v5n2a4
3. Ariansyah, R. (2025). Pengaruh ulasan online terhadap keputusan pembelian wisatawan. Jurnal Ekonomi Digital, 4(1), 15–22.
4. Azzahra, S. A., & Wibowo, A. (2020). Analisis sentimen multi-aspek berbasis konversi ikon emosi dengan algoritme Naïve Bayes untuk ulasan wisata kuliner pada web TripAdvisor. Jurnal Teknologi Informasi dan Ilmu Komputer, 7(4), 737. https://doi.org/10.25126/jtiik.2020731907
5. Chandradev, V., Suarjaya, I. M. A. D., & Bayupati, I. P. A. (2023). Analisis sentimen review hotel menggunakan metode deep learning BERT. Jurnal Buana Informatika, 14(2), 107–116.
6. Fahira, F., & Prianto, C. (2023). Prediksi pola kedatangan turis mancanegara dan menganalisis ulasan TripAdvisor dengan LSTM dan LDA. Jurnal Tekno Insentif, 17(2), 69–83. https://doi.org/10.36787/jti.v17i2.1096
7. Hu, M., & Liu, B. (2004). Mining and summarizing customer reviews. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 168–177). https://doi.org/10.1145/1014052.1014073
8. Kelly, R. (2020). Measuring customer satisfaction: Concepts and methods. International Journal of Marketing Science, 12(1), 11–21.
9. Khotimah, A. K. (2024). Analisis sentimen terhadap kualitas pelayanan. JATI (Jurnal Mahasiswa Teknik Informatika), 8(3), 3044–3048. https://doi.org/10.36040/jati.v8i3.9520
10. LEVYTSKA, I. (2019). Revenue management in hotel business. Economy. Finances. Management: Topical Issues of Science and Practical Activity, 5(45), 108–117. https://doi.org/10.37128/2411-4413-2019-5-12
11. Mabrur, R., Indrasari, D., & Nuryanti, M. (2022). Determinants of customer satisfaction in the hospitality industry. Journal of Business and Tourism Research, 8(1), 34–46.
12. Maulidiah, L., Hasanah, U., & Fathurrochman, I. (2023). Customer satisfaction in digital hotel booking: A literature review. Jurnal Manajemen dan Bisnis Digital, 3(2), 25–33.
13. Sarudin, R., Ismail, A., & Dewi, D. (2021). Analisis online review TripAdvisor.com terhadap minat pembelian produk jasa akomodasi di Hotel Manhattan. Jurnal Ilmu Sosial dan Ekonomi, 7(4), 33–43. https://doi.org/10.30813/.v7i1.2634
14. Supriyanto, A., Wijayanti, R., & Nursidik, R. (2023). Penerapan analisis sentimen dalam pengelolaan ulasan pelanggan hotel berbasis teks. Jurnal Teknologi dan Informasi, 9(2), 54–61.
15. Wiastuti, R. D., & Kurnia, J. R. (2021). Atribut luxury hotel di Jakarta berdasarkan ulasan digital pada TripAdvisor. Pringgitan, 2(1). https://doi.org/10.47256/pringgitan.v2i01.161
16. Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 58, 51–65. https://doi.org/10.1016/j.tourman.2016.10.001
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