ANALISIS SENTIMEN OPINI MASYARAKAT TERHDAP LESBIAN, GAY, BISEKSUAL, DAN TRANSGENDER (LGBT) DI MEDIA SOSIAL TWITTER DENGAN METODE SUPPORT VECTOR MACHINE

Khairi, Fakhri (2021) ANALISIS SENTIMEN OPINI MASYARAKAT TERHDAP LESBIAN, GAY, BISEKSUAL, DAN TRANSGENDER (LGBT) DI MEDIA SOSIAL TWITTER DENGAN METODE SUPPORT VECTOR MACHINE. Tugas Akhir thesis, University of Technology Yogyakarta.

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Abstract

Fakhri Khairi Department of Informatics, Faculty of Science & Technology University of Technology Yogyakarta North Ringroad St., Jombor Sleman Yogyakarta E-mail: fakhrikhairi03@gmail.com muhammad.fachrie@staff.uty.ac.id ABSTRACT The majority of Indonesians consider LGBT to be a topic that is haraam or not allowed to happen. According to dr. Teddy Hidayat, SpKj that the normal or abnormal size of LGBT can be seen from statistics. If the figure is only 30%, then LGBT groups belong to minorities. So statistically beyond average numbers. Sentiment analysis on Twitter is the process of understanding, extracting and processing tweets automatically to get the sentiment information. LGBT-related community tweets can be used to see an overview of people's opinions on LGBT topics. The large number of tweets coming in about LGBT encourages the need for methods that help to see public opinion effectively. In this study, the classification of tweet sentiment using the Support Vector Machine method was conducted. This method will classify whether a tweet contains positive or negative sentiment by searching for the best hyperplane of the two classification classes. The results of the classification are expected to reflect the growth of LGBT in Indonesia. Keywords: Sentiment Analysis, LGBT, Support Vector Machine, Classification

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 07 Sep 2021 04:28
Last Modified: 07 Sep 2021 04:28
URI: http://eprints.uty.ac.id/id/eprint/7990

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