Analysis of Tourist Sentiment towards Tourist Attractions in the Mandalika Special Economic Zone Using the Naïve Bayes Method
Abstract
The Mandalika Special Economic Zone has become one of the most popular destinations for both domestic and international tourists. This popularity highlights the importance of understanding the views and feelings of the tourists. Therefore, this study aims to analyze tourist sentiment towards the attractions in the Mandalika Special Economic Zone. The data analyzed was obtained from 1,144 reviews on the TripAdvisor platform. The research stages included data collection, data labeling, data preprocessing, data transformation, data classification, as well as data analysis and visualization. The results of this study indicate that the majority of tourists have a positive sentiment towards the attractions in the Mandalika Special Economic Zone. Furthermore, testing with the Naïve Bayes algorithm successfully classified tourist sentiments accurately, with consistent accuracy rates obtained from each fold: fold 1: 89.08%, fold 2: 89.96%, fold 3: 88.21%, fold 4: 87.34%, and fold 5: 90.79%.
References
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[2] H. Purba and I. Irwansyah, “User Generated Content dan Pemanfaatan Media Sosial Dalam Perkembangan Industri Pariwisata: Literature Review,” Prof. J. Komun. dan Adm. Publik, vol. 9, no. 2, pp. 229–238–229–238, 2022, [Online]. Available: https://jurnal.unived.ac.id/index.php/prof/article/view/3065
[3] N. Donthu, S. Kumar, N. Pandey, N. Pandey, and A. Mishra, “Mapping the electronic word-of-mouth (eWOM) research: A systematic review and bibliometric analysis,” J. Bus. Res., vol. 135, no. July, pp. 758–773, 2021, doi: 10.1016/j.jbusres.2021.07.015.
[4] R. Filieri, F. Acikgoz, V. Ndou, and Y. Dwivedi, “Is TripAdvisor still relevant? The influence of review credibility, review usefulness, and ease of use on consumers’ continuance intention,” Int. J. Contemp. Hosp. Manag., vol. 33, no. 1, pp. 199–223, 2021, doi: 10.1108/IJCHM-05-2020-0402.
[5] 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.
[6] Q. Jiang, C. S. Chan, S. Eichelberger, H. Ma, and B. Pikkemaat, “Sentiment analysis of online destination image of Hong Kong held by mainland Chinese tourists,” Curr. Issues Tour., vol. 24, no. 17, pp. 2501–2522, 2021, doi: 10.1080/13683500.2021.1874312.
[7] Y. I. Mahendra, “Dampak Pembangunan Kawasan Ekonomi Khusus Mandalika (KEK) Terhadap Pengembangan Usaha Mikro Kecil Dan Menengah Di Kuta Lombok Tengah Di Tinjau Dalam Perspektif Ekonomi Islam,” Econetica, vol. 2, no. 2, pp. 12–20, 2020.
[8] S. Damyanti and I. Indriani, “Dampak Pembangunan Sirkuit Kuta Mandalika Terhadap Pengembangan Usaha Mikro Kecil dan Menengah di Tinjau Dalam Perspektif Ekonomi Islam,” J. Sharia Econ. Islam. Tour., vol. 1, no. 3, pp. 20–27, 2021, [Online]. Available: http://journal.ummat.ac.id/index.php/jseit
[9] Y. . Wahyudin, A. M. Munir, and K. Rizki, “Pemberdayaan Masyarakat di Kawasan Ekonomi Khusus (KEK) Mandalika Provinsi Nusa Tenggara Barat Melalui Indikator Pembangunan Manusia,” Pros. Semnaskom - Unram, vol. 4, no. 1, pp. 226–234, 2022.
[10] B. R. T. Yunarni and A. Haris, “Pemberdayaan Perekonomian Masyarakat Melalui Pemberdayaan Usaha Mikro Kecil Dan Menengah (UMKM) Di Kawasan Ekonomi Khusus (KEK) Mandalika Lombok.,” JISIP (Jurnal Ilmu Sos. dan Pendidikan), vol. 4, no. 3, pp. 333–342, 2020, doi: 10.58258/jisip.v4i3.1224.
[11] E. Sopian, R. H. Sayuti, and A. Evendi, “Model Pemberdayaan Masyarakat di Kawasan Ekonomi Khusus Mandalika Kabupaten Lombok Tengah,” Proceeding Semin. Nas. Mhs. Sosiol., vol. 1, no. 1, pp. 171–180, 2023.
[12] M. A. Satrio, “Upaya Pemerintah Indonesia dalam Meningkatkan Pariwisata Mandalika Melalui Kerangka Branding ‘Wonderful Indonesia,’” Indones. Perspect., vol. 6, no. 1, pp. 65–85, 2021, doi: 10.14710/ip.v6i1.37513.
[13] Z. A. Ramdani, “Peran Pemerintah Dalam Pengembangan Kawasan Ekonomi Khusus Mandalika Provinsi Nusa Tenggara Barat,” J. Planoearth, vol. 5, no. 1, p. 1, 2020, doi: 10.31764/jpe.v5i1.1639.
[14] A. Sentimen et al., “Analisis Sentimen Objek Wisata Bali Di Google Maps Menggunakan Algoritma Naive Bayes,” J. Sains Komput. Inform. (J-SAKTI, vol. 6, no. 1, pp. 418–427, 2022.
[15] Y. A. Singgalen, “Analisis Sentimen Wisatawan Melalui Data Ulasan Candi Borobudur di Tripadvisor Menggunakan Algoritma Naïve Bayes Classifier,” Build. Informatics, Technol. Sci., vol. 4, no. 3, 2022, doi: 10.47065/bits.v4i3.2486.
[16] N. L. W. S. R. Ginantra, C. P. Yanti, G. D. Prasetya, I. B. G. Sarasvananda, and I. K. A. G. Wiguna, “Analisis Sentimen Ulasan Villa di Ubud Menggunakan Metode Naive Bayes, Decision Tree, dan K-NN,” J. Nas. Pendidik. Tek. Inform., vol. 11, no. 3, pp. 205–215, 2022, doi: 10.23887/janapati.v11i3.49450.
[17] A. R. Ismail and Raden Bagus Fajriya Hakim, “Implementasi Lexicon Based Untuk Analisis Sentimen Dalam Menentukan Rekomendasi Pantai Di DI Yogyakarta Berdasarkan Data Twitter,” Emerg. Stat. Data Sci. J., vol. 1, no. 1, pp. 37–46, 2023, doi: 10.20885/esds.vol1.iss.1.art5.
[18] M. U. Albab, Y. Karuniawati P, and M. N. Fawaiq, “Optimization of the Stemming Technique on Text preprocessing President 3 Periods Topic,” J. Transform., vol. 20, no. 2, pp. 1–10, 2023, [Online]. Available: https://journals.usm.ac.id/index.php/transformatika/■page1
[19] N. L. P. M. Putu, Ahmad Zuli Amrullah, and Ismarmiaty, “Analisis Sentimen dan Pemodelan Topik Pariwisata Lombok Menggunakan Algoritma Naive Bayes dan Latent Dirichlet Allocation,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 5, no. 1, pp. 123–131, 2021, doi: 10.29207/resti.v5i1.2587.
[20] Pande Made Risky Cahya Dinatha and Nur Aini Rakhmawati, “Komparasi Term Weighting dan Word Embedding pada Klasifikasi Tweet Pemerintah Daerah,” J. Nas. Tek. Elektro dan Teknol. Inf., vol. 9, no. 2, pp. 155–161, 2020, doi: 10.22146/jnteti.v9i2.90.
Published
2024-08-07
How to Cite
Pribadi, T., Fahry, F., Muharis, M., & Marswandi, E. (2024). Analysis of Tourist Sentiment towards Tourist Attractions in the Mandalika Special Economic Zone Using the Naïve Bayes Method. Jurnal Bumigora Information Technology (BITe), 6(1), 105-114. https://doi.org/https://doi.org/10.30812/bite.v6i1.4081
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