COMPARISON OF MACHINE LEARNING CLASSIFICATION ALGORITHM ON HOTEL REVIEW SENTIMENT ANALYSIS (CASE STUDY: LUMINOR HOTEL PECENONGAN)
Komparasi Algoritma Klasifikasi Machine Learning Pada Analisis Sentimen Review HOTEL (Studi Kasus: Luminor Hotel Pecenongan)
Analysis of hotel review sentiment is very helpful to be used as a benchmark or reference for making hotel business decisions today. However, all the review information obtained must be processed first by using an algorithm. The purpose of this study is to compare the Classification Algorithm of Machine Learning to obtain information that has a better level of accuracy in the analysis of hotel reviews. The algorithm that will be used is k-NN (k-Nearest Neighbor) and NB (Naive Bayes). After doing the calculation, the following accuracy level is obtained: k-NN of 60,50% with an AUC value of 0.632 and NB of 85,25% with an AUC value of 0.658. These results can be determined by the right algorithm to assist in making accurate decisions by business people in the analysis of hotel reviews using the NB Algorithm.
Basari, A. S. H., Hussin, B., Ananta, I. G. P., & Zeniarja, J. (2013). OpinionMining of Movie Review Using Hybrid Method of Support Vector Machine and Particle Swarm Optimization. Procedia Engineering, 53, 453–462. https://doi.org/10.1016/j.proeng.2013.02.059
Chandani, V., Wahono, R. S., & Purwanto, P. (2015). Komparasi Algoritma Klasifikasi Machine Learning Dan Feature Selection pada Analisis Sentimen Review Film. Journal of Intelligent Systems, 1(1), 56–60. http://www.journal.ilmukomputer.org/index.php?journal=jis&page=article&op=view&path%5B%5D=10
Dey, L., Chakraborty, S., Biswas, A., Bose, B., & Tiwari, S. (2016). Sentiment Analysis of Review Datasets Using Naïve Bayes‘ and K-NN Classifier. International Journal of Information Engineering and Electronic Business, 8(4), 54–62. https://doi.org/10.5815/ijieeb.2016.04.07
Dirsehan, T. (2016). Text Mining in the Hospitality Sector To Extend the Motivation Theory. Conference: International Marketing Trends Conference, January, 1–13. https://www.researchgate.net/publication/298070052_Text_Mining_in_the_Hospitality_Sector_to_Extend_the_Motivation_Theory
Effendy, V. (2015). ANALISIS SENTIMEN BERBAHASA INDONESIA DENGAN PENDEKATAN LEXICON BASED (STUDI KASUS : SOLUSI PENGELOLAAN SAMPAH). Jurnal Ilmiah Komputer Dan Informatika (KOMPUTA), 4(1), 55–60. http://komputa.if.unikom.ac.id/_s/data/jurnal/vol.4-no.1/22.214.171.124.2015-55-60-2089-9033.pdf/pdf/126.96.36.199.2015-55-60-2089-9033.pdf
Kontopoulos, E., Berberidis, C., Dergiades, T., & Bassiliades, N. (2013). Ontology-based sentiment analysis of twitter posts. Expert Systems with Applications, 40(10), 4065–4074. https://doi.org/10.1016/j.eswa.2013.01.001
Miharja, J., Putra, J. L., & Hadianto, N. (2020). Independent Research Final Report.
Muthia, D. A. (2016). Opinion Mining Pada Review Buku Menggunakan Algoritma Naive Bayes. Jurnal Teknik Komputer AMIK BSI, 2(1), 1–8. http://ejournal.bsi.ac.id/ejurnal/index.php/jtk/article/viewFile/357/266
Sipayung, E. M., Maharani, H., & Zefanya, I. (2016). Perancangan Sistem Analisis Sentimen Komentar Pelanggan Menggunakan Metode Naive Bayes Classifier. Jurnal Sistem Informasi, 8(1), 958–965. https://ejournal.unsri.ac.id/index.php/jsi/article/view/3250
Utami, L. D., Rachmi, H., & Nurlaela, D. (2018). Komparasi algoritma klasifikasi pada analisis review hotel. Jurnal Pilar Nusa Mandiri, 14(2), 261–266. https://doi.org/https://doi.org/10.33480/pilar.v14i2.77
Yordanova, S., & Kabakchieva, D. (2017). Sentiment Classification of Hotel Reviews in Social Media with Decision Tree Learning. International Journal of Computer Applications, 158(5), 1–7. https://doi.org/10.5120/ijca2017912806
Zhang, L., & Liu, B. (2017). Sentiment Analysis and Opinion Mining. In C. Sammut & G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining (pp. 1152–1161). Springer. https://doi.org/10.1007/978-1-4899-7687-1
Abstract viewed = 116 times
PDF downloaded = 61 times
Copyright (c) 2020 Jaja Miharja, Jordy Lasmana Putra, Nur Hadianto
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to the PILAR Nusa Mandiri journal as the publisher of the journal, and the author also holds the copyright without restriction.
Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases, and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , are allowed with written permission from the PILAR Nusa Mandiri journal.
PILAR Nusa Mandiri journal, the Editors and the Advisory International Editorial Board make every effort to ensure that no wrong or misleading data, opinions, or statements be published in the journal. In any way, the contents of the articles and advertisements published in the PILAR Nusa Mandiri journal are the sole and exclusive responsibility of their respective authors and advertisers.