Sentiment Analysis System Of Bali Tourism Using Naive Bayes Algorithm And Web Framework
Keywords:
sentiment analysis, tourist, Bali, Naive Bayes, web frameworkAbstract
To obtain trends and impacts that may occur in the Bali tourism industry after the pandemic requires tourism actors to maintain the existence of the tourist beauty and culture they have. This research aims to develop a sentiment analysis system in the Bali tourism sector using the Naive Bayes algorithm and the Web Framework. This research stages carried out include Data Collection (Scraping), Data Cleaning, Feature Extraction, Modeling, and Web Platform Development. The data used was 2779 review data. The results show that most of the visitor reviews are in the "Very Positive" category, namely 1244. Next, 776 reviews are in the "Positive" category, 328 "Neutral”. The words that appeared most frequently included “place”, “walk”, “beautiful”, “nice”. The evaluation results show that the Bayes algorithm shows an accuracy value of 71%, which means Naive Bayes produces sufficient accuracy for sentiment analysis. In this research, we succeeded in developing a website with a web framework to predict the sentiment of a review in real time and it is hoped that it can help related parties understand and respond to reviews more effectively, improve the tourist experience, and advance the tourism sector in Bali.
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References
Ginantra, N. L. W. S. R., Yanti, C. P., Prasetya, G. D., Sarasvananda, I. B. G., & Wiguna, I. K. A. G. (2022). Analisis Sentimen Ulasan Villa di Ubud Menggunakan Metode Naive Bayes, Decision Tree, dan K-NN. Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI), 11(3), 205–215. https://doi.org/10.23887/janapati.v11i3.49450
I. W. B. Suryawan, N. W. Utami, and K. Q. Fredlina, “Analisis Sentimen Review Wisatawan pada Objek Wisata Ubud Menggunakan Algoritma Support Vector Machine,” J. Inform. Teknol. dan Sains, vol. 5, no. 1, pp. 133–140, 2023.
Irvandi, Irawan, B., & Nurdiawan, O. (2023). Naive Bayes Dan Wordcloud Untuk Analisis Sentimen Wisata Halal Pulau Lombok. INFOTECH Journal, 9(1), 236–242. https://doi.org/10.31949/infotech.v9i1.5322
Putu, N. L. P. M., Ahmad Zuli Amrullah, & Ismarmiaty. (2021). Analisis Sentimen dan Pemodelan Topik Pariwisata Lombok Menggunakan Algoritma Naive Bayes dan Latent Dirichlet Allocation. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 5(1), 123–131. https://doi.org/10.29207/resti.v5i1.2587
Sari, R., & Hayuningtyas, R. Y. (2019). Penerapan Algoritma Naive Bayes Untuk Analisis Sentimen Pada Wisata TMII Berbasis Website. Indonesian Journal on Software Engineering (IJSE), 5(2), 51–60. https://doi.org/10.31294/ijse.v5i2.6957
Singgalen, Y. A. (2021). Analisis Sentimen dan Pemodelan Topik dalam Optimalisasi Pemasaran Destinasi Pariwisata Prioritas di Indonesia. Journal of Information Systems and Informatics, 3(3), 459–470. https://doi.org/10.51519/journalisi.v3i3.171
Suryawan, I. W. B., Utami, N. W., & Fredlina, K. Q. (2023). Analisis Sentimen Review Wisatawan pada Objek Wisata Ubud Menggunakan Algoritma Support Vector Machine. Jurnal Informatika Teknologi Dan Sains, 5(1), 133–140.
Widyarto, E. B., Informatika, F., Telkom, U., Informatika, F., Telkom, U., Lhaksmana, K. M., Informatika, F., Telkom, U., & Belakang, A. L. (2023). Implementasi Metode Naïve Bayes Classifier Terhadap Analisis Sentimen Tempat Wisata di Nusa Tenggara Barat. 10(5), 4934–4941.
W. Khofifah, D. N. Rahayu, and A. M. Yusuf, “Analisis Sentimen Menggunakan Naive Bayes Untuk Melihat Review Masyarakat Terhadap Tempat Wisata Pantai Di Kabupaten Karawang Pada Ulasan Google Maps,” J. Interkom J. Publ. Ilm. Bid. Teknol. Inf. dan Komun., vol. 16, no. 4, pp. 28–38, 2022, doi: 10.35969/interkom.v16i4.192.
