Implementation of Personal Data Protection Against Wrongful Ticketing in The Electronic Law Enforcement System - Anthony Setiawan Eddy; Fajar Sugianto (Ridwan Institute, 2026)
This study examines the implementation of artificial intelligence-based Electronic Traffic Law Enforcement (ETLE) in Indonesia and its implications for personal data protection, particularly in cases of wrongful ticketing. The background highlights the increasing use of automated decision-making systems in traffic law enforcement, which aims to improve efficiency and road safety, but also raises concerns regarding data accuracy, algorithmic errors, and citizens' privacy rights. This research aims to analyze the legal protection of personal data subjects within the ETLE system and evaluate the effectiveness of Undang-Undang No. 27 of 2022 on Personal Data Protection in addressing system-related errors. The research employs a normative juridical and empirical legal approach by analyzing statutory regulations, scholarly literature, and field-based implementation issues related to ETLE practices in Indonesia. The findings indicate that while ETLE has a strong legal foundation under traffic and data protection laws, its implementation still produces wrongful ticketing due to system inaccuracies, database mismatches, and limited algorithmic transparency. These weaknesses result in potential violations of personal data rights, including issues of accountability and fairness in automated enforcement. The study concludes that although the ETLE system is legally recognized, its operational framework requires stronger institutional oversight, improved data accuracy mechanisms, and enhanced transparency to ensure compliance with personal data protection principles. Strengthening regulatory enforcement, establishing an independent supervisory authority, and integrating correction and deletion mechanisms are essential to safeguard citizens' rights in AI-based law enforcement systems in Indonesia.