Multinomial Naive Bayes Algorithm for Indonesian language Sentiment Classification Related to Jakarta International Stadium (JIS)
DOI:
https://doi.org/10.58776/ijitcsa.v2i1.118Keywords:
review, sentiment analysis, Jakarta International Stadium (JIS), Multinomial Naive Bayes, ClassificationAbstract
The research focuses on analysing public evaluations, particularly those on Google Maps, about the Jakarta International Stadium (JIS). The study aims to employ the multinomial Naive Bayes algorithm to ascertain the sentiment expressed in these reviews. The objective of this study was to employ the multinomial Naive Bayes method to analyse the reviews on Google Maps pertaining to the Jakarta International Stadium (JIS). The utilised data consists of 2971 public reviews on Google Maps specifically pertaining to Jakarta International Stadium (JIS). These reviews were acquired through web scraping using a data miner. The acquired data is next processed in the text preparation phase to generate a prepared dataset suitable for analysis. This preprocessing stage includes operations such as casefolding, stopword removal, tokenizing, and stemming. The study yielded an accuracy of 0.83, or 83%, when tested on 733 data points. Out of these, 292 positive data points were correctly anticipated, while 59 positive data points were incorrectly forecast. Additionally, 317 negative data points were correctly predicted, while 65 negative data points were incorrectly predicted. The conducted modelling is subsequently categorised using a novel dataset of 161 review data points, with the objective of discerning the sentiment expressed within the dataset. The analysis of the new dataset yielded 101 reviews with positive sentiment and 50 reviews with negative sentiment.References
. “Stadion,” Wikipedia. Dec. 17, 2022.
. “Profil JIS: Stadion Mewah Jakarta yang disebut PSSI tak Standar FIFA,” CNN Indonesia, Sep. 12, 2022.
. A. J. Fadhillah, “Analisis Sentimen Terhadap Gerai Minuman Xing Fu Tang Indonesia Menggunakan Data Ulasan Google,” 2022.
. A. Erfina and D. S. Utami, “Analisis Sentimen Objek Wisata Bali Di Google Maps Menggunakan Algoritma Naive Bayes,” 2022.
. M. Permana, S. Widiastuti, and S. Saepudin, “ANALISIS SENTIMEN PENGGUNAAN APLIKASI VIDEO CONFERENCE PADA ULASAN GOOGLE PLAY STORE MENGGUNAKAN METODE NBC (NAIVE BAYES CLASSIFIER),” JURSISTEKNI (Jurnal Sistem Informasi dan Teknologi Informasi), vol. 5, pp. 178–191, Jan. 2023.
. D. R. Lazuardi, T. A. Munandar, H. Harsiti, Z. Mutaqin, and R. N. Hays, “Sentiment analysis of public opinions on the welfare of honorary educators using Naive Bayes,” in IOP Conference Series: Materials Science and Engineering, Institute of Physics Publishing, May 2020. doi: 10.1088/1757-899X/830/3/032018.
. A. P. Giovani, A. Ardiansyah, T. Haryanti, L. Kurniawati, and W. Gata, “ANALISIS SENTIMEN APLIKASI RUANG GURU DI TWITTER MENGGUNAKAN ALGORITMA KLASIFIKASI,” Jurnal Teknoinfo, vol. 14, no. 2, p. 115, Jul. 2020, doi: 10.33365/jti.v14i2.679.
. R. Alamsyah, T. Ai Munandar, F. Nidaul Khasanah, and S. Setiawati, “Sentiment Analysis Destinasi Wisata Kabupaten Bekasi Berdasarkan Opini Masyarakat Menggunakan Naive bayes,” Journal DINDA, vol. 2, no. 2, pp. 64–74, 2022, [Online]. Available: http://journal.ittelkom-pwt.ac.id/index.php/dinda
. M. A. Fauzi and S. Adinugroho, “Analisis Sentimen Pariwisata di Kota Malang Menggunakan Metode Naive Bayes dan Seleksi Fitur Query Expansion Ranking Text clustering View project Twitter Sentiment Analysis View project,” 2018. [Online]. Available: https://www.researchgate.net/publication/322959527
. J. Winahyu and I. Suharjo, “Aplikasi Web Analisis Sentimen Dengan Algoritma Multinomial Naïve Bayes,” Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika (KARMAPATI), vol. 10, no. 2, 2021.
. N. S. Wardani, A. Prahutama, and P. Kartikasari, “ANALISIS SENTIMEN PEMINDAHAN IBU KOTA NEGARA DENGAN KLASIFIKASI NAÏVE BAYES UNTUK MODEL BERNOULLI DAN MULTINOMIAL,” Jurnal GAUSSIAN, vol. 9, pp. 237–246, 2020, [Online]. Available: https://ejournal3.undip.ac.id/index.php/gaussian/
. H. Herwanto, N. L. Chusna, and M. S. Arif, “Klasifikasi SMS Spam Berbahasa Indonesia Menggunakan Algoritma Multinomial Naïve Bayes,” JURNAL MEDIA INFORMATIKA BUDIDARMA, vol. 5, no. 4, p. 1316, Oct. 2021, doi: 10.30865/mib.v5i4.3119.
. G. A. Buntoro, “Analisis Sentimen Calon Gubernur DKI Jakarta 2017 Di Twitter,” 2017. [Online]. Available: https://t.co/jrvaMsgBdH
. W. Yulita et al., “Analisis Sentimen Terhadap Opini Masyarakat Tentang Vaksin Covid-19 Menggunakan Algoritma Naïve Bayes Classifier,” JDMSI, vol. 2, no. 2, pp. 1–9, 2021.
. E. M. Sipayung, H. Maharani, and I. Zefanya, “PERANCANGAN SISTEM ANALISIS SENTIMEN KOMENTAR PELANGGAN MENGGUNAKAN METODE NAIVE BAYES CLASSIFIER,” 2016. [Online]. Available: http://ejournal.unsri.ac.id/index.php/jsi/index
. B. Mas Pintoko and K. Muslim, “Analisis Sentimen Jasa Transportasi Online pada Twitter Menggunakan Metode Naïve Bayes Classifier,” Bandung, Dec. 2018. Accessed: Jun. 20, 2023. [Online]. Available: https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/7447/7336
. R. Mitchell, Web Scraping with Python: Collecting More Data from the Modern Web, 2nd ed. United States Of America: O’Rielly Media, 2018.
. C. S. Sriyano and E. B. Setiawan, “Pendeteksian Berita Hoax Menggunakan Naive Bayes Multinomial Pada Twitter dengan Fitur Pembobotan TF-IDF,” 2021.
. V. Amrizal, “PENERAPAN METODE TERM FREQUENCY INVERSE DOCUMENT FREQUENCY (TF-IDF) DAN COSINE SIMILARITY PADA SISTEM TEMU KEMBALI INFORMASI UNTUK MENGETAHUI SYARAH HADITS BERBASIS WEB (STUDI KASUS: HADITS SHAHIH BUKHARI-MUSLIM),” JURNAL TEKNIK INFORMATIKA, vol. 11, no. 2, pp. 149–164, Nov. 2018, doi: 10.15408/jti.v11i2.8623.
. G. Singh, B. Kumar, and A. Tyagi, “Comparison between Multinomial and Bernoulli Naïve Bayes for Text Classification,” International Conference on Automation, Computational and Technology Management (ICACTM), Apr. 2019.
. C. D. Manning, Prabhakar. Raghavan, and Hinrich. Schütze, Introduction to information retrieval. Cambridge University Press, 2008.
. 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,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 5, no. 1, pp. 123–131, Feb. 2021, doi: 10.29207/resti.v5i1.2587.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Daffa Rizki Surya Pratama, Tb Ai Munandar, Khairunnisa Fadhilla Ramdhania
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
