Sentiment Analysis of Visitor Reviews on Star Hotels in Manado City
DOI:
https://doi.org/10.25126/jitecs.202381403Abstract
Sentiment analysis is a technique of extracting the text data to analyze the opinions and evaluate to obtain the information. Sentiment analysis is performed by internet users on social media or online applications or websites to provide assessments or personal opinions. Tourism in North Sulawesi has grown by 600% in the past four years, and the rise of tourism has sent tourists flocking to the city of Manado. These travelers need a hotel that satisfies their desires, so they need to read about the hotel in the reviews on the hotel reservation service website. This takes a lot of time. To overcome existing problems, sentiment analysis applications were developed to make it easier for potential hotel users to find previous user responses. Additionally, data mining classification techniques are used to help hotel managers determine the satisfaction of previous hotel users using a Naive Bayes algorithm. The five tests performed gave the best result, 76.20% accuracy, with an average of 70.55%. While the average precision is 70.57% and 99.85% for the recall.
References
F. Wullur, "Berita Manado," 23 April 2019. [Online]. Available: https://beritamanado.com/sulut-dinobatkan-the-rising-star-sektor-pariwisata/. [Accessed December 2021].
J. Han, M. Kamber and J. Pei., Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems), Burlington: Elsevier, 2012.
Abdilah, E. Mardiyani and M. Safudin, "Integrasi Algoritma Genetika Dan Information Gaint Untuk Menganalisis Sentimen Review Hotel Menggunakan Algoritma Naive Bayes," Jurnal Teknik Komputer AMIK BSI, vol. 4, no. 1, p. 186–193, 2018.
E. M. Sipayung, H. Maharani and I. Zefanya, "Perancangan Ssitem Analisis Sentimen Komentar Pelanggan Menggunakan Metode Naive Bayes Classifier," JSI: Jurnal Sistem Informasi, vol. 8, no. 1, pp. 958–965,, 2016.
5. F. M. Suarka, A. S. Sulistyawati and N. P. R. Sari, "Pengembangan ”Leisure And Recreation For Later Life” (Wisatawan Lanjut Usia) Di Kawasan Wisata Sanur-Bali," Jurnal Analisis Pariwisata, vol. 17, no. 2, pp. 109-115, 2017.
Angdresey, M. A. Lamongi and R. Munir, "Information Retrieval System in the Bible," CogITo Smart Journal, vol. 7, no. 1, pp. 111-120, 2021.
Liu, Sentiment Analysis and Opinion Mining, Morgan & Claypool Publishers, 2012.
S. Gusriani, K. D. K. Wardhani and M. I. Zul, "Analisis Sentimen Terhadap Toko Online di Sosial Media Menggunakan Metode Klasifikasi Naïve Bayes (Studi Kasus: Facebook Page BerryBenka)," in 4th Applied Business and Engineering Conference, Riau, 2016.
E. Indrayuni, "Analisa Sentimen Review Hotel Menggunakan Algoritma Support Vector Machine Berbasis Particle Swarm Optimization," Evolusi: Jurnal Sains dan Manajemen, vol. 4, no. 2, pp. 20-27, 2016.
M. H. Azhar, P. P. Adikari and Y. A. Sari, "Analisis Sentimen pada Ulasan Hotel dengan Fitur Score Representation dan Identifikasi Aspek pada Ulasan Menggunakan K-Modes," Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 2, no. 9, p. 2777–2782, 2018.
M. Wongkar and A. Angdresey, "Sentiment Analysis Using Naive Bayes Algorithm of The Data Crawler: Twitter," in 2019 Fourth International Conference on Informatics and Computing (ICIC), Semarang, 2019.
Downloads
Published
How to Cite
Issue
Section
License
 Creative Common Attribution-ShareAlike 3.0 International (CC BY-SA 3.0)
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).