ANALISA SENTIMEN MASYARAKAT TERHADAP ISU LESBIAN, GAY, BISEX, DAN TRANSGENDER MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE
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Date
2023-02
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Journal ISSN
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Publisher
Elfitra
Abstract
Sentiment 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 sentiments
Description
Keywords
LGBT, Twitter, Sentiment, Term Frequency (TF) – Inverse Document Frequency (IDF), Support Vector Machine
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