Analysis of Public Sentiment Indonesia’s Personal Data Protection Law: A Comparison of SVM and IndoBERT on X Platform - Yulia Kurniawati; Ricky Bahari Hamid; Dana Indra Sensuse; Sofian Lusa; Prasetyo Adi Wibowo Putro; Sofiyanti Indriasari (Jurnal Teknik Informatika (Jutif), 2026)
The high number of data misuses, thefts, and leaks led to the enactment of the PDP Law, which regulates the rights and obligations of data owners and electronic system providers. The purpose of this study is to examine the public’s response to the implementation of the law through the X platform, using tweet harvest as a scraping tool, and to evaluate model performance through a comparative approach between SVM and BERT. The feature extraction used in this study is TF-IDF for SVM and BERT with IndoBERT. The accuracy results indicate that BERT is better with an accuracy of 86% compared to SVM with a training and test data ratio of 85:15. This advantage is because BERT can understand linguistic context that SVM cannot. On the other hand, SVM has advantages in computational efficiency and faster processing, making it a suitable choice in situations with limited computational resources. The sentiment analysis result revealed that data protection,  digital footprint and the institution's role were the most frequently discussed topics. Furthermore, periodic or real-time evaluations can be conducted on the public's response to the PDP Law to ensure it remains aligned and relevant to technological developments and societal needs.