Authors:

Komang Dhiyo Yonatha Wijaya, Anak Agung Istri Ngurah Eka Karyawati

Abstract:

“During this pandemic, social media has become a major need as a means of communication. One of the social medias used is Twitter by using messages referred to as tweets. Indonesia currently undergoing mass social distancing. During this time most people use social media in order to spend their idle time However, sometimes, this result in negative sentiment that used to insult and aimed at an individual or group. To filter that kind of tweets, a sentiment analysis was performed with SVM and 3 different kernel method. Tweets are labelled into 3 classes of positive, neutral, and negative. The experiments are conducted to determine which kernel is better. From the sentiment analysis that has been performed, SVM linear kernel yield the best score Some experiments show that the precision of linear kernel is 57%, recall is 50%, and f-measure is 44%”

Keywords

Keyword Not Available

Downloads:

Download data is not yet available.

References

References Not Available

PDF:

https://jurnal.harianregional.com/jlk/full-64395

Published

2020-11-22

How To Cite

YONATHA WIJAYA, Komang Dhiyo; KARYAWATI, Anak Agung Istri Ngurah Eka. The Effects of Different Kernels in SVM Sentiment Analysis on Mass Social Distancing.JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 9, n. 2, p. 161-168, nov. 2020. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/64395. Date accessed: 08 Jul. 2024. doi:https://doi.org/10.24843/JLK.2020.v09.i02.p01.

Citation Format

ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License