Sentiment Analysis of Indonesian YouTube Reviews About Lesbian, Gay, Bisexual, and Transgender (LGBT) using IndoBERT Fine Tuning

Abstract

Lesbian, gay, Bisexual, and Transgender (LGBT) is an individual who has a sexual orientation or gender identity that is different from the heterosexual majority. The LGBT community now dares to appear openly on social media; nowadays, social media is used as a source of information and a place to provide comments. The Indonesian state generally still views the LGBT community as deviant behavior. This research was conducted to understand Indonesian society's views on LGBT through YouTube and social media. The text mining method analyzes and classifies the counter or pro sentences expressed in the comments. The model used in this research is IndoBERT because the research object studied is Indonesian. IndoBERT is part of the Bidirectional Encoder Representation From Transformers (BERT) model. The data sources used were 1,493 data. The stages carried out in this research included the preprocessing stage, which included case folding, data cleaning, tokenization, stopword removal, stemming, and normalization, then the data labeling stage, and finally, the model building stage with IndoBERT Fine Tuning. The level of accuracy achieved using IndoBERT is 74%.