Repository Universitas PakuanSentiment Analysis of the RUU Perampasan Aset Using a Comparative Approach on Bidirectional Encoder Representations from Transformers (BERT) ModelsResiAlindianaauthorSentiment Analysis of the RUU Perampasan Aset Using a Comparative Approach on Bidirectional Encoder Representations from Transformers (BERT) Models Resi Alindiana1*, Arie Qur'ania2 , Heri Bambang Santoso3 1 Department of Computer Science, Faculty of Mathematics and Natural Sciences, Pakuan University, Bogor, Indonesia 2 Department of Computer Science, Faculty of Mathematics and Natural Sciences, Pakuan University, Bogor, Indonesia 3 Department of Computer Science, Faculty of Mathematics and Natural Sciences, Pakuan University, Bogor, Indonesia * Correspondence: [065121081@student.unpak.ac.id] Abstract: The RUU Perampasan Aset has existed since 2003 but has not yet been enacted and continues to attract public attention, particularly on the social media platform X (Twitter), alongside the increasing discussion of corruption cases. Therefore, this study aims to analyze public perception of the RUU Perampasan Aset from a linguistic perspective. Sentiment analysis is conducted by comparing three BERT-based models—mBERT, IndoBERT, and IndoBERTweet which are capable of understanding bidirectional textual context. Sentiment classification is divided into positive and negative categories. Positive sentiment represents supportive opinions expressed in polite and ethical language, while negative sentiment represents supportive opinions conveyed in a sarcastic and pessimistic manner. The research process follows the Knowledge Discovery in Databases (KDD) methodology. Evaluation results using variations of epochs and batch sizes show that IndoBERT achieves the best performance with an accuracy of 92%, followed by mBERT at 91% and IndoBERTweet at 90%. These findings indicate performance differences among the three models, suggesting that model effectiveness is influenced not only by architectural design but also by dataset characteristics . Keywords: RUU Perampasan Aset, Sentiment Analysis, X (Twitter), mBERT, IndoBERT, IndoBERTweet.Ilmu Komputer2025-06-16Universitas Pakuan;Fakultas Matematika dan Pengetahuan AlamThesis

For work being deposited by its own author: In self-archiving this collection of files and associated bibliographic metadata, I grant Repository Universitas Pakuan the right to store them and to make them permanently available publicly for free on-line. I declare that this material is my own intellectual property and I understand that Repository Universitas Pakuan does not assume any responsibility if there is any breach of copyright in distributing these files or metadata. (All authors are urged to prominently assert their copyright on the title page of their work.)

For work being deposited by someone other than its author: I hereby declare that the collection of files and associated bibliographic metadata that I am archiving at Repository Universitas Pakuan) is in the public domain. If this is not the case, I accept full responsibility for any breach of copyright that distributing these files or metadata may entail.

Clicking on the deposit button indicates your agreement to these terms.