Implementation of Personal Data Protection Against Wrongful Ticketing in The Electronic Law Enforcement System
DOI:
https://doi.org/10.46799/ijssr.v6i6.1437Keywords:
Law Enforcement, Automated Decision Making (ADM), Artificial Intelligence (AI), Electronic Traffic Law Enforcement (ETLE), Personal Data ProtectionAbstract
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.
References
Albakjaji, M., & Kasabi, M. (2021). The right to privacy from legal and ethical perspectives. Journal of Legal, Ethical and Regulatory Issues, 24(S5), 1–10.
Alfred, Y. (2021). Perlindungan data pribadi dengan prinsip mengutamakan melindungi privasi pengguna dalam upaya mewujudkan tujuan hukum di Indonesia. Satya Dharma: Jurnal Ilmu Hukum, 4(1), 11–12. https://ejournal.iahntp.ac.id/index.php/satya-dhamat
Azzani, A. N., & Nida, Q. (2025). Penerapan sistem Electronic Traffic Law Enforcement (ETLE) dalam menurunkan tingkat pelanggaran lalu lintas di Kota Serang. Jurnal Studi Hukum dan Administrasi Publik, 2(2), 57–69.
Bambang, F. (2025). Tinjauan yuridis tanggung jawab hukum bank terhadap kerugian nasabah akibat kecerdasan buatan (AI) dalam pengambilan keputusan kredit. Milthree Law Journal, 1(1).
Bantekas, I., & Bratsiakou, V. (2026). Automated decision-making systems and black box challenges under European Union administrative law. Fordham International Law Journal, 49(1), 2–15. https://www.fordhamilj.org/volume-49-issue-1/2026/1/21/automated-decision-making-systems-and-black-box-challenges-under-european-union-administrative-law
Demetzou, K. (2019). Data protection impact assessment: A tool for accountability and the unclarified concept of “high risk” in the GDPR. Computer Law & Security Review, 35(6), 105342. https://doi.org/10.1016/j.clsr.2019.105342
Denny, S. (2025). Legal analysis of the application of artificial intelligence (AI) in a justice-based judicial system. In The 8th Legal International Conference and Studies: Justice, Human Rights, and Law. KnE Social Sciences. https://doi.org/10.18502/kss.v10i28.20123
Fitrianto, B. (2025). Tinjauan yuridis tanggung jawab hukum bank terhadap kerugian nasabah akibat kecerdasan buatan (AI). Milthree Law Journal, 1(1).
Gryz, J., & Rojszczak, M. (2021). Black box algorithms and the rights of individuals: No easy solution to the explainability problem. Internet Policy Review, 10(2), 2. https://doi.org/10.14763/2021.2.1564
Hukom, R. (2025). The effect of artificial intelligence in judicial decision-making in Indonesia. Jurnal Ilmu Hukum dan Sosial, 3(1), 1032–1051. https://doi.org/10.51903/hakim.v3i1.2298
Jabar, S., Frinaldi, A., & Roberia. (2024). Akuntabilitas dan transparansi dalam perspektif hukum administrasi negara. Gudang Jurnal Multidisiplin Ilmu, 2(12). https://doi.org/10.59435/gjmi.v2i12.1196
Johnson, G. M. (2020). Algorithmic bias: On the implicit biases of social technology. New York University.
Khair, F., & Wiraguna, S. A. (2025). Data Protection Impact Assessment (DPIA) sebagai instrumen kunci UU PDP. Jurnal Hukum, Politik dan Humaniora, 2(2), 253. https://doi.org/10.62383/progres.v2i2.1821
Leonita, A., Islah, I., & Hisbah, H. (2022). Penegakan hukum terhadap pelanggaran lalu lintas melalui ETLE. Jurnal Ilmiah Universitas Batanghari Jambi. https://doi.org/10.33087/jiubj.v22i3.2823
Malquna, O. V., Sihombing, A., & Nuraeni, Y. (2026). Electronic Traffic Law Enforcement and traffic law enforcement. Awang Long Law Review, 8(3), 749–755.
Prasetyo, B., Handayani, I. G. A. K. R., & Sulistiyono, A. (2025). Data protection laws in Indonesia. SIDE: Scientific Development Journal, 2(1).
Qamar, N. (2020). Metode penelitian hukum: Doktrinal dan non-doktrinal. CV Social Politic Genius.
Rizk, A., & Lindgren, I. (2025). Automated decision-making in public administration. Government Information Quarterly, 42(3), 101234.
Sajid, A., et al. (2023). Explainable artificial intelligence (XAI). Information Fusion, 99, 101805.
Wulansari, E. M. (2020). Konsep perlindungan data pribadi sebagai aspek fundamental norm. Jurnal Surya Kencana Dua, 7(2), 269. https://doi.org/10.32493/SKD.v7i2.y2020.9214
Zuiderveen Borgesius, F. J. (2020). Strengthening legal protection against discrimination by algorithms. The International Journal of Human Rights, 24(10), 1573.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Anthony Setiawan Eddy, Fajar Sugianto
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International. that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
