ANALISA SENTIMEN MASYARAKAT TERHADAP ISU LESBIAN, GAY, BISEX, DAN TRANSGENDER MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

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dc.contributor.authorNasution, Abduh Maghfuri
dc.contributor.supervisoraminuddin, Al
dc.date.accessioned2023-05-05T03:11:47Z
dc.date.available2023-05-05T03:11:47Z
dc.date.issued2023-02
dc.description.abstractSentiment analysis is the process of analyzing data that will be classified according to the class of sentiment in an argument. The rise of Lesbian, Gay, Bisexual, and Transgender(LGBT) talk on the Twitter application has caused people to give positive and negative sentiments. So that the sexual culture becomes very sensitive among Indonesian people. The author uses a method for classifying with several stages, namely data collection, preprocessing, labeling, Term Frequency (TF) – Inverse Document Frequency (IDF) weighting, Support Vector Machine (SVM) classification with the Cross Validation method. Based on the stages of the method that has been carried out, a Machine Learning score is obtained with an average value of 0.776. The results of Machine Learning found 220 positive sentiments and 780 negative sentimentsen_US
dc.description.sponsorshipFakultas Matematika dan Ilmu Pengetahuan Alamen_US
dc.identifier.citationPerpustakaanen_US
dc.identifier.otherElfitra
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/10979
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectLGBTen_US
dc.subjectTwitteren_US
dc.subjectSentimenten_US
dc.subjectTerm Frequency (TF) – Inverse Document Frequency (IDF)en_US
dc.subjectSupport Vector Machineen_US
dc.titleANALISA SENTIMEN MASYARAKAT TERHADAP ISU LESBIAN, GAY, BISEX, DAN TRANSGENDER MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINEen_US
dc.typeArticleen_US

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