Sianipar, Srikandi Karmeli Lusia
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IMPLEMENTATION OF CRIMINAL LIABILITY FOR CHEMICAL CASTRATION FOR DOERS OF SEXUAL VIOLENCE CRIMES AGAINST CHILDREN Sianipar, Srikandi Karmeli Lusia; Naldo, Rony Andre Christian; Pasaribu, Muldri P.J.
Jurnal Ilmiah Advokasi Vol 13, No 1 (2025): Jurnal Ilmiah Advokasi
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jiad.v13i1.6191

Abstract

Children must receive legal protection from crimes of sexual violence. The legal fact is that up to now there are still children who are victims of sexual violence crimes. Likewise with the legal facts that occurred in Pematangsiantar City. This research discusses criminal liaibility for doers of crimes of sexual violence against children. In this regard, this research is focused on examining the implementation of chemical castration criminal liability for doers of crimes of sexual violence against children. This research is prescriptive analytical in nature, using normative juridical methods, using a statutory approach and a conceptual approach. The type of data used is secondary data. The research results concluded that D.D. who are doers of crimes of sexual violence against children in Pematangsiantar City, criminal liability for chemical castration is not implemented. Key Words: Castration; Sexual; Child.
Artificial Intelligence and Criminal Liability: A Preliminary Study within the Indonesian Legal System Hutapea, Novelina Mutiara Sariati; Sitepu, Desy Kartika Caronina; Damanik, Jenriswandi; Sianipar, Srikandi Karmeli Lusia
Jurnal Ilmu Hukum Kyadiren Vol 7 No 2 (2026): Jurnal Ilmu Hukum Kyadiren
Publisher : PPPM, Sekolah Tinggi Ilmu Hukum (STIH) Biak-Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46924/jihk.v7i2.330

Abstract

The rapid development of Artificial Intelligence (AI) presents significant challenges for Indonesian criminal law, particularly in determining accountability for actions involving AI, whether as an auxiliary tool or as an indirect perpetrator. This study seeks to examine the current criminal law framework, identify deficiencies in the Criminal Code (KUHP), the Electronic Information and Transactions Law (ITE Law), and related regulations, and assess the applicability of alternative liability models, including vicarious liability and strict liability. Employing a normative juridical approach—through the analysis of statutory provisions, legal doctrine, and international case studies—this research finds that national regulations remain predominantly reactive, fail to adequately anticipate the emergence of autonomous AI, and encounter technical evidentiary challenges arising from the ‘black box’ phenomenon. The findings suggest that alternative liability models are better suited to the distinctive characteristics of AI. The study concludes that a responsive reformulation of criminal law norms is essential to ensure legal certainty, protect victims, and facilitate effective law enforcement in the context of AI.