PENGAWASAN MASSAL BERBASIS AI (FACIAL RECOGNITION) OLEH NEGARA DAN IMPUNITAS TERHADAP HAK ATAS PRIVASI DIGITAL: KAJIAN YURIDIS, SOSIOLOGIS, DAN FILOSOFIS
DOI:
https://doi.org/10.51878/yurisdiksi.v1i2.15087Keywords:
Facial Recognition Technology, data biometrik, UU PDP, proportionality test, Chilling EffectAbstract
ABSTRACT
The development of Facial Recognition Technology (FRT) in public services and law enforcement offers benefits for identification efficiency, while simultaneously raising concerns regarding biometric data protection, privacy, and civil liberties. These concerns become more complex when processing is conducted extensively and automatically without clear limits on governmental authority or adequate oversight. This study aims to analyze the limits of state authority in using FRT under Law Number 27 of 2022 on Personal Data Protection (PDP Law), as well as its social and philosophical implications for freedom, autonomy, and human dignity. The study employs normative legal research as its primary design, complemented by a socio-legal approach based on literature and documentary analysis and a legal philosophy approach. Legal materials are analyzed using the Siracusa Principles and the proportionality test, while social implications are examined through the concepts of the Chilling Effect and Digital Panopticon. The findings show that biometric data constitutes specific Personal Data, while extensive and indiscriminate FRT use requires stronger legal grounds, legitimate purposes, necessity, proportionality, and safeguards. Indiscriminate use without adequate oversight potentially restricts privacy and civil liberties. The study recommends strengthening independent oversight, algorithmic audits, transparency, retention limits, and effective remedies.
ABSTRAK
Perkembangan Facial Recognition Technology (FRT) dalam layanan publik dan penegakan hukum menghadirkan manfaat bagi efisiensi identifikasi, tetapi sekaligus menimbulkan persoalan pelindungan data biometrik, privasi, dan kebebasan sipil. Persoalan menjadi semakin kompleks ketika pemrosesan dilakukan secara luas, otomatis, dan tanpa batas kewenangan serta pengawasan yang memadai. Penelitian ini bertujuan menganalisis batas kewenangan negara dalam penggunaan FRT berdasarkan Undang-Undang Nomor 27 Tahun 2022 tentang Pelindungan Data Pribadi (UU PDP), serta mengkaji implikasi sosial dan filosofisnya terhadap kebebasan, otonomi, dan martabat manusia. Penelitian menggunakan penelitian hukum normatif sebagai desain utama dengan pendekatan socio-legal berbasis studi kepustakaan dan pendekatan filsafat hukum. Bahan hukum dianalisis menggunakan Siracusa Principles dan proportionality test, sedangkan implikasi sosial dikaji melalui konsep Chilling Effect dan Digital Panopticon. Hasil penelitian menunjukkan bahwa data biometrik merupakan Data Pribadi yang bersifat spesifik, sementara penggunaan FRT yang luas dan tidak terarah memerlukan dasar hukum, tujuan, kebutuhan, proporsionalitas, serta safeguards yang lebih kuat. Penggunaan indiscriminate tanpa pengawasan memadai berpotensi membatasi privasi dan kebebasan sipil. Penelitian merekomendasikan penguatan pengawasan independen, audit algoritma, transparansi, pembatasan retensi, dan mekanisme pemulihan.
References
Almeida, D., Shmarko, K., & Lomas, E. (2022). The ethics of facial recognition technologies, surveillance, and accountability in an age of artificial intelligence: A comparative analysis of US, EU, and UK regulatory frameworks. AI and Ethics, 2, 377–387.
https://doi.org/10.1007/s43681-021-00077-w
Anggriawan, R., Hamsin, M. K., Karsai, K., & He, Y. (2026). Facial recognition in asylum seeker procedures: Criminal implications of data misuse and profiling. Jurnal Media Hukum, 33(1), 99–117. https://doi.org/10.18196/jmh.v33i1.29861
Basron, B., Adellah, A., & Athaya, N. (2026). Penerapan artificial intelligence (AI) dalam sistem administrasi publik: Peluang, tantangan, dan etika pelayanan publik di Indonesia. Public Service and Governance Journal, 7(1), 217–229.
https://doi.org/10.56444/psgj.v7i1.3579
Fadhilla, S. R., & Putra, M. S. (2024). Kompleksitas penggunaan face recognition technology oleh PT Kereta Api Indonesia ditinjau dari aspek perlindungan data pribadi dan sistem interoperabilitas. Jurnal Al Azhar Indonesia Seri Ilmu Sosial, 5(3).
https://doi.org/10.36722/jaiss.v5i3.3031
Fauziah, H. Y., & Kusuma, T. M. (2025). Penerapan Deepface dan Retinaface dalam pengenalan wajah parsial untuk aplikasi keamanan digital. Jurnal Ilmiah Informatika Komputer, 30(2). https://doi.org/10.35760/ik.2025.v30i2.241
Gabrielli, G. (2025). The use of facial recognition technologies in the context of peaceful protest: The risk of mass surveillance practices and the implications for the protection of human rights. European Journal of Risk Regulation, 16(2), 514–541.
https://doi.org/10.1017/err.2025.26
Girsang, S. Y. B. (2024). Pentingnya regulasi khusus sistem face recognition technology sebagai produk artificial intelligence dalam peningkatan keamanan dan penegakan hukum di Indonesia. Nommensen Journal of Legal Opinion, 5(2), 86–98.
https://doi.org/10.51622/njlo.v5i2.1817
Hilmi, F., & Marpaung, Z. A. (2025). Perlindungan hukum bagi korban penggunaan teknologi pengenalan wajah. Jurnal Antologi Hukum, 5(1), 18–37.
https://doi.org/10.21154/antologihukum.v5i1.5128
Husna, N., Nurman, M., & Nugroho, Y. (2025). Pembentukan Peraturan Pemerintah tentang face recognition technology ditinjau dari Undang-Undang Nomor 27 Tahun 2022 tentang Perlindungan Data Pribadi. Jurnal Ilmiah AKSES, 3(2).
https://unars.ac.id/ojs/index.php/akses/article/view/7126
Kamal, M. Y., Azhar, M., & Suhartoyo. (2024). Implikasi penggunaan artificial intelligence terhadap hak-hak pekerja (studi terhadap face recognition boarding gate di Stasiun Semarang Tawang Bank Jateng). Diponegoro Law Journal, 13(2).
https://doi.org/10.14710/dlj.2024.43580
Kurniawan, K. S., & Kurniawan, I. G. A. (2025). The limitations of lex generalis: Analyzing the readiness of the GDPR and PDP Law for AI-based facial recognition technology. SIGn Jurnal Hukum, 7(2). https://doi.org/10.37276/sjh.v7i2.533
Meloni, F. (2026). Facial recognition on trial: Data protection, discrimination, and the ethics of algorithmic governance in policing. Information & Communications Technology Law. https://doi.org/10.1080/13600834.2026.2638629
Murray, D. (2024). Police use of retrospective facial recognition technology: A step change in surveillance capability necessitating an evolution of the human rights law framework. The Modern Law Review, 87(4), 833–863. https://doi.org/10.1111/1468-2230.12862
Pramudito, D. K. (2025). Facial recognition technology in Indonesia: Opportunities and ethical challenges. The Journal of Academic Science, 2(2). https://doi.org/10.59613/vfs73h61
Prartama, A. S., & Ahmad, G. A. (2025). Analisis peraturan pemrosesan data lintas negara Undang-Undang Perlindungan Data Pribadi Indonesia dibandingkan dengan General Data Protection Regulation (GDPR) Uni Eropa. Indonesian Journal of Contemporary Law, 2(5). https://journal.unesa.ac.id/index.php/ijcl/article/view/44672
Pratiwi, A., Rahmawyanet, M. E., Wibowo Putra, P. A., & Sensuse, D. I. (2025). Systematic literature review on artificial intelligence in Indonesia’s public sector: Reimagining digital government. JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer), 11(2).
https://doi.org/10.33480/jitk.v11i2.6842
Putri, D. T. (2025). Regulating digital privacy in Indonesia: The practice of data subject rights and controller duties in the FotoYu app. Istinbath: Jurnal Hukum, 22(2), 230–262.
https://doi.org/10.32332/istinbath.v22i02.art01
Rambe, R., & Abdurrahman, L. (2024). Implikasi etika dan hukum dalam penggunaan teknologi pengenalan wajah: Perlindungan privasi versus keamanan publik. Jurnal Hukum Caraka Justitia, 4(2), 90–104. https://doi.org/10.30588/jhcj.v4i2.1828
Robles, P., Mallinson, D. J., Best, E., et al. (2025). Global perspectives on regulating facial recognition technology utilization for criminal justice arrests. Global Public Policy and Governance, 5, 186–204. https://doi.org/10.1007/s43508-025-00117-9
Rustam, D. R., Widiasih, N. P. S., & Tise, S. (2026). The probative value of artificial intelligence-based facial recognition in the Electronic Traffic Law Enforcement (ETLE) system under the beyond a reasonable doubt standard. Jurnal Hukum Volkgeist, 10(2), 325–332.
https://www.jurnalumbuton.ac.id/index.php/Volkgeist/article/view/8336
Salam, S., Asmah, Kiro, M. R., Yasim, S., & Muhammed, I. K. (2026). Human rights protection in the ecosystem of surveillance technology and big data law enforcement. Indonesia Media Law Review, 5(1).
https://journal.unnes.ac.id/journals/imrev/article/view/44290
Sembiring, P. E., Ramli, A. M., & Rafianti, L. (2024). Implementasi desain privasi sebagai pelindungan privasi atas data biometrik. Veritas et Justitia, 10(1), 127–152.
https://doi.org/10.25123/vej.v10i1.7622
Supardi, D. A., Ghofar, H. S. A., Dzaki, D. H. N., Hadiyantina, S., & Magistra, M. R. (2026). Joint data controller responsibility in OSS RBA system interoperability after the Personal Data Protection Law enactment. Kertha Patrika, 48(1), 1–19.
https://doi.org/10.24843/KP.2026.v48.i01.p01
Syahputra, F., Sabrina, E., Sitorus, A., Lubis, K. M. N., Saragi, F. J., & Sinaga, N. N. (2026). Keamanan pengenalan wajah berbasis deep learning: Tinjauan sistematis serangan adversarial dan strategi pertahanan (systematic literature review). TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora, 6(4).
https://doi.org/10.33650/trilogi.v6i4.13424
Wiredarme. (2025). Constitutional limits on government use of facial recognition technology in public services and public security. Jurnal Kecerdasan Buatan dan Teknologi Informasi, 4(3), 356–363.
https://ojs.ninetyjournal.com/index.php/JKBTI/article/view/491
Zahro, A. K. (2025). Perlindungan privasi individu dalam penggunaan face recognition: Tinjauan hukum dan etika. SPEKTRUM HUKUM, 21(2), 150–159.
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