SENTIMENT ANALYSIS ON E-SPORTS FOR EDUCATION CURRICULUM USING NAIVE BAYES AND SUPPORT VECTOR MACHINE

  • Rian Ardianto STMIK Nusa Mandiri
  • Tri Rivanie
  • Yuris Alkhalifi
  • Fitra Septia Nugraha
  • Windu Gata
DOI: https://doi.org/10.21609/jiki.v13i2.885
Keywords: Text Mining, Sentiment Analysis, Naïve Bayes, Support Vector Machine, SMOTE.

Abstract

The development of e-sports education is not just playing games, but about start making, development, marketing, research and other forms education aimed at training skills and providing knowledge in fostering character. The opinions expressed by the public can take form support, criticism and input. Very large volume of comments need to be analyzed accurately in order separate positive and negative sentiments. This research was conducted to measure opinions or separate positive and negative sentiments towards e-sports education, so that valuable information can be sought from social media. Data used in this study was obtained by crawling on social media Twitter. This study uses a classification algorithm, Naïve Bayes and Support Vector Machine. Comparison two algorithms produces predictions obtained that the Naïve Bayes algorithm with SMOTE gets accuracy value 70.32%, and AUC value 0.954. While Support Vector Machine with SMOTE gets accuracy value 66.92% and AUC value 0.832. From these results can be concluded that Naïve Bayes algorithm has a higher accuracy compared to Support Vector Machine algorithm, it can be seen that the accuracy difference between naïve Bayes and the vector machine support is 3.4%. Naïve Bayes algorithm can thus better predict the achievement of e-sports for students' learning curriculum.
Published
2020-07-01
How to Cite
Ardianto, R., Rivanie, T., Alkhalifi, Y., Nugraha, F. S., & Gata, W. (2020). SENTIMENT ANALYSIS ON E-SPORTS FOR EDUCATION CURRICULUM USING NAIVE BAYES AND SUPPORT VECTOR MACHINE. Jurnal Ilmu Komputer Dan Informasi, 13(2), 109-122. https://doi.org/10.21609/jiki.v13i2.885
Issue
Vol. 13 No. 2 (2020): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Section
Articles

Authors who publish with this journal agree to the following terms:

  1. 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.
  2. 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.
  3. 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).