Klasifikasi Ujaran Kebencian pada Media Sosial Twitter MenggunakanSupport Vector Machine

Klasifikasi Ujaran Kebencian pada Media Sosial Twitter MenggunakanSupport Vector Machine

classification, support vector machine, hate speech, twitter, kernel

Nowadays social media has become a place for peoples to express their opinions, there are many ways that can be done to express both positive andnegativeopinions. Hate speech is one of the problems that we find quite a lot in cyberspace, thatthings can be detrimental to many parties. Twitter as one of social media,can be used as a source of analysis about people's behavior in cyberspace. Many of our society that unconsciouslyact of hate speech on social media, thereforethis study findsout how people's behavior patterns in cyberspace and the main issue of hate speech on a particular topic and time period by classify it into five classes, namely ethnicity, religion, race, inter-groups and neutral using Support Vector Machine. In this study also compares three kernel that common to use and the result isthe system can classify hate speech by usingRBF kernelandgot the highest result with 93% accuracy on 700 data train and 300data test

Oryza Habibie Rahman1, Gunawan Abdillah2, Agus Komarudin

https://jurnal.iaii.or.id/index.php/RESTI/issue/view/20

Universitas Jenderal Achmad Yani

13 februari 2021

Fajar bagus W

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Indonesia

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