Analisis Sentimen Dan Emosi Terhadap RUU Perampasan Aset Pada Komentar Youtube Menggunakan IndoBERT

Adam, Bima Kaka Bani (2026) Analisis Sentimen Dan Emosi Terhadap RUU Perampasan Aset Pada Komentar Youtube Menggunakan IndoBERT. Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

YouTube is a social media platform for people to express their opinions on public policy issues. Comments on the platform contain various sentiments and emotions that can be analyzed to understand public perceptions of government policies. This study aims to analyze sentiment and emotions in YouTube comments related to the Asset Forfeiture Bill using the IndoBERT model. The research method used refers to CRISP-DM, which includes Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The dataset was obtained through a process of scraping YouTube comments, followed by pre-processing stages such as cleaning, case folding, and normalization. This study uses three variants of the IndoBERT model: Indolem/indoBERT-base-uncased, indoBenchmark/indoBERT-base-p2, and IndoBERTweet with data split scenarios of 70:30 and 80:20. The results showed that the indoBenchmark/indoBERT-base-p2 model with a data split ratio of 80:20 achieved the best performance in sentiment classification with an accuracy of 92%, while in emotion classification it achieved an accuracy of 85%. Furthermore, the model was successfully implemented into a web-based application using Flask to perform automatic sentiment and emotion analysis.

Item Type: Thesis (Undergraduate)
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorWahyuni, Eka DyarNIDN00011128406ekawahyuni.si@upnjatim.ac.id
Thesis advisorWibowo, Nur CahyoNIDN0717037901nurcahyo.si@upnjatim.ac.id
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science > Departemen of Information Systems
Depositing User: Bima Kaka Bani Adam
Date Deposited: 20 Jul 2026 02:52
Last Modified: 20 Jul 2026 04:09
URI: https://repository.upnjatim.ac.id/id/eprint/56094

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