Rekonstruksi Obstruction of Justice atas Manipulasi Adversarial Bukti Elektronik Berbasis AI dalam KUHP dan KUHAP Indonesia
DOI:
https://doi.org/10.55681/seikat.v5i5.4426Keywords:
Obstruction of justice, Adversarial manipulation, Electronic evidence, Artificial Intelligence, Criminal evidenceAbstract
The development of artificial intelligence has transformed criminal evidence, particularly when electronic evidence is not merely falsified but adversarially manipulated to deceive AI-based analytical systems. This study aims to reconstruct the concept of obstruction of justice concerning adversarial manipulation of electronic evidence within Indonesia’s Criminal Code and Criminal Procedure Code. It employs normative legal research using statutory, conceptual, case, and comparative approaches. The findings show that adversarial manipulation differs from conventional digital falsification because attacks may target an AI system’s inference process without significantly altering the visible appearance of evidence. Normatively, Article 278 of the Criminal Code has the strongest connection to direct manipulation of evidence, while Articles 281 and 282 may only apply when their specific elements are satisfied. In procedural law, electronic evidence authentication should be supplemented by assessment of analytical reliability, including model transparency, error rates, reproducibility, and adversarial robustness. This study proposes the Adversarial Evidence Interference Test, consisting of judicial-process nexus, adversarial act, knowledge and purpose, material interference capability, and forensic causal traceability. This reconstruction enables criminal law to adapt to AI developments without expanding criminalization by analogy and strengthens protection for the integrity of criminal evidentiary processes. It promotes accountable, transparent, and reviewable digital adjudication.
Keywords: Obstruction of justice; Adversarial manipulation; Electronic evidence; Artificial intelligence; Criminal evidence.
Downloads
References
Agatha, C., & Rahaditya, R. (2026). Fragmented digital forensic standards in Indonesian criminal evidence. Indonesian Journal of Law and Economics Review, 21(2). https://doi.org/10.21070/ijler.v21i2.1558
Al Alif, S. S., Rindiani, A., & Marhayati, C. (2025). Konstruksi hukum pidana dalam penanggulangan kejahatan siber berbasis teknologi deepfake di Indonesia. Legal Standing: Jurnal Ilmu Hukum, 9(5), 1169–1183. https://doi.org/10.24269/ls.v9i5.12406
Antoro, H., Budhijanto, D., & Somawijaya. (2026). Admissibility of artificial intelligence as electronic evidence: Comparative perspectives from Indonesia, the United States, and Japan. Jurnal IUS Kajian Hukum dan Keadilan, 14(1), 122–139. https://doi.org/10.29303/ius.v14i1.1880
Azis, M. A., Pujiyono, & Putri, R. A. K. (2026). Reconstructing reliability standards for deepfake detectors as electronic evidence in Indonesia’s criminal justice system. West Science Law and Human Rights, 4(3), 299–309. https://doi.org/10.58812/wslhr.v4i03.3022
Chen, P., Xu, M., & Qi, J. (2024). DeepFake detection against adversarial examples based on D-VAEGAN. IET Image Processing, 18(3), 615–626. https://doi.org/10.1049/ipr2.12973
Choudhary, K. (2024). Which method should I select for my legal research: Doctrinal, empirical, multi-method or something else? Teisė, 132, 135–144. https://doi.org/10.15388/Teise.2024.132.10
Cirillo, L., Gervasio, A., & Amerini, I. (2025). Explainability-driven adversarial robustness assessment for generalized deepfake detectors. EURASIP Journal on Information Security, 2025, Article 23. https://doi.org/10.1186/s13635-025-00211-9
Jamil, A., & Saifuddin, S. (2026). The use of artificial intelligence in the court process in Indonesia: A review of procedural law on the aspect of evidence and decision-making. Lex Scientia Law Review, 10(1), 521–550. https://doi.org/10.15294/lslr.v10i1.28681
Majeed, N., Hilal, A., & Khan, A. N. (2023). Doctrinal research in law: Meaning, scope and methodology. Bulletin of Business and Economics, 12(4). https://doi.org/10.61506/01.00167
Mangrulkar, R., Pravin, H., & Pravin, S. (2024). Digital forensics in the age of AI and ML: Evidence handling, validation and reporting. Open Access Journal of Data Science and Artificial Intelligence, 2(1), 1–5. https://doi.org/10.23880/oajda-16000132
Negara, T. A. S. (2023). Normative legal research in Indonesia: Its originis and approaches. Audito Comparative Law Journal, 4(1), 1–9. https://doi.org/10.22219/aclj.v4i1.24855
Nugraha, R. S., & Silalahi, C. F. (2024). Pembaharuan berlakunya asas legalitas dalam Undang-Undang Nomor 1 Tahun 2023 tentang Kitab Undang-Undang Hukum Pidana. PALAR (Pakuan Law Review), 10(1), 73–81. https://journal.unpak.ac.id/index.php/palar/article/view/10164
Nurkholisah, S., et al. (2025). Deepfake sebagai bentuk kejahatan siber baru: Tantangan kriminalisasi dalam hukum pidana Indonesia. Jurnal USM Law Review, 8(3), 2421–2445. https://doi.org/10.26623/julr.v8i3.13060
Pettanasse, I., Rani, F. H., Saputra, M. A., & Ardha, D. J. (2024). Tindak pidana “obstruction of justice” dalam pengaturan Undang-Undang Nomor 1 Tahun 2023. Journal of Sharia and Legal Science, 2(2), 163–177. https://doi.org/10.61994/jsls.v2i2.651
Rajendra, J. B., & Thuraisingam, A. S. (2026). The role of explainability and human intervention in AI decisions: Jurisdictional and regulatory aspects. Information & Communications Technology Law, 35(2), 152–183. https://doi.org/10.1080/13600834.2025.2537514
Sandoval, M.-P., et al. (2024). Threat of deepfakes to the criminal justice system: A systematic review. Crime Science, 13, Article 41. https://doi.org/10.1186/s40163-024-00239-1
Stoykova, R. (2024). A new right to procedural accuracy: A governance model for digital evidence in criminal proceedings. Computer Law & Security Review, 55, 106040. https://doi.org/10.1016/j.clsr.2024.106040
Sumardiana, B., Pujiyono, Cahyaningtyas, I., & Wulandari, C. (2024). Evaluation of electronic evidence in criminal justice in the era of advanced artificial intelligence technology. Indonesian Journal of Criminal Law Studies, 9(2), 309–332. https://doi.org/10.15294/ijcls.v9i2.36634
Surakanti, S., Goundar, S., & Dwight, J. (2025). Countering anti-forensic tactics in cybercrime investigations: A systematic literature review. International Journal of Information Security, 24, Article 210. https://doi.org/10.1007/s10207-025-01131-y
Vanessa, V., & Firmansyah, H. (2025). Analysis of the validity of electronic evidence in criminal trial proceedings and the implementation of its admissibility. Indonesian Journal of Law and Economics Review, 20(4). https://doi.org/10.21070/ijler.v20i4.1395
Yamin, M., & Bawono, B. T. (2025). Law enforcement against obstruction of justice in eradicating criminal acts of corruption in Indonesia. Jurnal Hukum Khaira Ummah, 20(2), 585–601. https://doi.org/10.30659/jhku.v20i2.46094
Zhu, M., & Long, J. (2025). Detecting anti-forensic deepfakes with identity-aware multi-branch networks. Frontiers in Big Data, 8, 1720525. https://doi.org/10.3389/fdata.2025.1720525
Hooda, A., Mangaokar, N., Feng, R., Fawaz, K., Jha, S., & Prakash, A. (2024). D4: Detection of adversarial diffusion deepfakes using disjoint ensembles. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (pp. 3812–3822). IEEE. https://doi.org/10.1109/WACV57701.2024.00377
Garrett, B. L. (2025). Artificial intelligence and procedural due process (Duke Law School Public Law & Legal Theory Series No. 2025-15). Duke University School of Law. https://doi.org/10.2139/ssrn.5093989
Vassilev, A., Oprea, A., Fordyce, A., & Anderson, H. (2024). Adversarial machine learning: A taxonomy and terminology of attacks and mitigations (NIST AI 100-2e2023). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.AI.100-2e2023
Republik Indonesia. (2023). Undang-Undang Republik Indonesia Nomor 1 Tahun 2023 tentang Kitab Undang-Undang Hukum Pidana. Lembaran Negara Republik Indonesia Tahun 2023 Nomor 1, Tambahan Lembaran Negara Republik Indonesia Nomor 6842. https://peraturan.bpk.go.id/Details/234935/uu-no-1-tahun-2023
Mahkamah Konstitusi Republik Indonesia. (2025). Putusan Mahkamah Konstitusi Nomor 163/PUU-XXIII/2025. https://www.mkri.id/public/content/persidangan/putusan/putusan_mkri_13289_1760599508.pdf
Mahkamah Konstitusi Republik Indonesia. (2026). Putusan Mahkamah Konstitusi Nomor 71/PUU-XXIII/2025.
Mahkamah Konstitusi Republik Indonesia. (2026). Putusan Mahkamah Konstitusi Nomor 111/PUU-XXIV/2026.
Council of Europe. (2024). Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law (CETS No. 225). https://www.coe.int/en/web/conventions/full-list?module=treaty-detail&treatynum=225
European Parliament & Council of the European Union. (2024). Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence and amending Regulations and Directives (Artificial Intelligence Act). Official Journal of the European Union. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1689
Mahkamah Konstitusi Republik Indonesia. (2026, March 2). MK hapus pasal karet “obstruction of justice”. https://www.mkri.id/berita/mk-hapus-pasal-karet-%E2%80%9Cobstruction-to-justice%E2%80%9D-24696
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Andre Kurniawan, Herlita Eryke

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.








