Analisis Sentimen Terhadap Industri E-Sports Pada Media Sosial Twitter Dengan Menggunakan Metode K-Nearest Neighbor

Authors

  • Desi Jasmiati Universitas Pamulang
  • Hidayatullah Al Islami Universitas Pamulang

Keywords:

Sentiment Analysis, E-sports, K-Nearest Neighbor, Twitter

Abstract

The phenomenon of e-sports has experienced significant developments along with the rapid development of information and communication technology during the industrial revolution 4.0. This industry has achieved several lucrative achievements and has become a popular topic that reaps a variety of comments on social media, one of which is Twitter. Sentiment analysis is useful for determining the tendency of public opinion to be positive or negative, so that later it can become structured information. The data used is 200 twitter comments. The processes carried out are crawling, preprocessing including cleaning, normalization, case folding, stopword removal, tokenizing, and stemming, carrying out sentiment labeling and weight calculations using TF-IDF. The classification method uses K-Nearest Neighbor, validation tests use 10-fold cross validation and accuracy calculations use the confussion matrix formula. The rapid miner tool is used to process the stages automatically. The final result obtained a value of k = 6 as the highest value with an accuracy of 66.00%, precision with a value of 67.34%, recall 78.06% and AUC with a value of 0.762. While the results of the sentiment classification obtained positive sentiment superior to negative sentiment. Based on these results, the K-Nearest Neighbor method is considered to be able to classify well and it is known that Indonesian people currently respond to the e-sports industry tends to provide more positive stigma and a good response.

References

Herdhianto, A. (2020). Sentiment Analysis Menggunakan Naïve Bayes Classifier (NBC) Pada Tweet Tentang Zakat. http://repository.uinjkt.ac.id/dspace/handle/123456789/53661

Hidayat, T. F. T., Garno, G., & Ridha, A. A. (2021). Analisis Sentimen Opini Pemindahan Ibu Kota Pada Twitter Dengan Metode Support Vector Machine. Jurnal Ilmu Komputer, 14(1), 49. https://doi.org/10.24843/jik.2021.v14.i01.p06

Jabal Tursina, M. (2019). Sentimen Analisis Sistem Zonasi Sekolah Pada Media Sosial Youtube Menggunakan Metode K-Nearest Neighbor Dengan Algoritma Levenshtein Distance. Universitas Islam Negeri Syarif Hidayatullah Jakarta.

Kusumawardhana, A. (2019). KLASIFIKASI SENTIMEN TERHADAP TOKOH PUBLIK PADA TWITTER MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR.

Masturoh, S. (2021). Analisis Sentimen Terhadap E-Wallet Dana Pada Ulasan Google Play Menggunakan Algoritma K-Nearest Neighbor. https://doi.org/10.33480/pilar.v17i1.2182

Rizki, M. M. (2019). Analisis sentimen terhadap produk otomotif dari twitter menggunakan kombinasi algoritma k-nearest neighbor dan pendekatan lexicon (studi kasus: mobil toyota). Repository.Uinjkt.Ac.Id. http://repository.uinjkt.ac.id/dspace/handle/123456789/48643

Safitri, R. N. (2020). Analisis Sentimen Review Pelanggan Hotel Menggunakan Metode K-Nearest Neighbor (K-NN) (Studi Kasus : Hotels.com, Booking.com, Agoda.com).

Simorangkir, H., & Lhaksmana, K. M. (2018). Analisis Sentimen pada Twitter untuk Games Online Mobile Legends dan Arena of Valor dengan Metode Naïve Bayes Classifier. E-Proceeding of Englineering, 5(3), 8131–8140. https://openlibrary.telkomuniversity.ac.id/pustaka/files/144621/jurnal_eproc/analisis-sentimen-pada-twitter-untuk-games-online-mobile-legends-dan-arena-of-valor-dengan-metode-na-ve-bayes-classifier.pdf

Tanggu Mara, A., Sediyono, E., & Purnomo, H. (2021). Penerapan Algoritma K-Nearest Neighbors Pada Analisis Sentimen Metode Pembelajaran Dalam Jaringan (DARING) Di Universitas Kristen Wira Wacana Sumba. Jointer - Journal of Informatics Engineering, 2(01), 24–31. https://doi.org/10.53682/jointer.v2i01.30

Wicaksana, F. A., & Nasvian, M. F. (2022). KOMUNIKASI, KOORDINASI, DAN KERJASAMA DALAM GAME KOMPETITIF MOBILE LEGEND. Jurnal Ilmiah Indonesia, 7(8.5).

Additional Files

Published

05-04-2024

How to Cite

Desi Jasmiati, & Hidayatullah Al Islami. (2024). Analisis Sentimen Terhadap Industri E-Sports Pada Media Sosial Twitter Dengan Menggunakan Metode K-Nearest Neighbor. OKTAL : Jurnal Ilmu Komputer Dan Sains, 3(04), 865–874. Retrieved from https://journal.mediapublikasi.id/index.php/oktal/article/view/2553

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