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All Journal International Journal of Nusantara Islam Research Horizon International Journal of Nusantara Islam
Ismail, Yana Chaeru Taufik
Universitas Islam Nusantara Bandung
Religion Arts Humanities Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Social Sciences

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Legal Risk Management in the Use of Artificial Intelligence Diagnosis at Cahaya Medika General Hospital, Makassar Muhammad Takwa; Yana Chaeru Taufik Ismail
International Journal of Nusantara Islam Vol 13 No 2 (2025): International Journal of Nusantara Islam
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ijni.v13i2.58657

Abstract

The use of Artificial Intelligence (AI) in medical diagnosis has significantly increased in Indonesian hospitals, including RSU Cahaya Medika Makassar which has integrated AI for radiology and pathology since 2024 (with a capacity of 500 beds and 20+ AI tools). Law No. 17/2023 on Health (Article 220) and Permenkes 75/2020 on AI in Health require accuracy >90%, algorithm transparency, and liability sharing between doctors-AI-vendors. However, legal risks emerge: AI diagnosis errors (15% false positive, Kemenkes 2025), malpractice claims (Article 29 Law 29/2004), and data responsibility (UU PDP 27/2022). A case at a Jakarta hospital (2024) lost a Rp2 billion lawsuit over AI breast cancer misdiagnosis; RSCM Makassar recorded 3 AI error incidents in 2025. Without risk management (policy, training, insurance), RSU Cahaya Medika is vulnerable to litigation, reputational damage, and costs. This study aims to identify main legal risks of AI diagnosis use and design an effective legal risk management framework according to ISO 31000 and Indonesian regulations. This research uses a qualitative case study with a normative-empirical juridical approach, involving in-depth interviews with 25 key informants, AI system observations, and document analysis. The results show that the main legal risks include criminal and civil malpractice due to AI errors, non-compliance with UU Health and Permenkes AI regulations, and complex liability sharing between doctors-vendor-AI-hospitals. The effective legal risk management framework must include risk identification, risk assessment, risk treatment, and continuous risk monitoring according to ISO 31000 standards.
Legal Liability of Medical Device Business Actors Towards Patient Safety in Health Services Mohammad Yusuf Rakhmatullah; Yana Chaeru Taufik Ismail
Research Horizon Vol. 6 No. 4 (2026): Research Horizon - Agustus 2026
Publisher : LifeSciFi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54518/rh.6.4.2026.1518

Abstract

Medical devices are an essential component of modern healthcare that directly impact patient safety. The increasing use of medical devices in healthcare facilities in Indonesia raises legal issues regarding the liability of business actors when patients suffer losses due to defective or malfunctioning medical devices. This study aims to analyze the legal liability of medical device business actors for patient safety based on the applicable laws and regulations in Indonesia, as well as to identify obstacles and efforts in law enforcement. This study uses a normative juridical approach with a statute approach and a conceptual approach. The findings show that the legal liability of medical device business actors encompasses fault-based liability, strict liability, and product liability under Law Number 8 of 1999 concerning Consumer Protection, Law Number 17 of 2023 concerning Health, and Government Regulation Number 28 of 2024 concerning the Implementation of Law Number 17 of 2023 concerning Health. Law enforcement remains constrained by weak post-market surveillance, limited incident reporting, insufficient supervisory resources, complex distribution chains, technological developments, and low legal awareness among business actors. Strengthening integrated materiovigilance, supervisory capacity, responsive regulations, and regulatory education is necessary to ensure effective patient safety protection.
Legal Risk Management in the Use of Artificial Intelligence Diagnosis at Cahaya Medika General Hospital, Makassar Muhammad Takwa; Yana Chaeru Taufik Ismail
International Journal of Nusantara Islam Vol 13 No 2 (2025): International Journal of Nusantara Islam
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ijni.v13i2.58657

Abstract

The use of Artificial Intelligence (AI) in medical diagnosis has significantly increased in Indonesian hospitals, including RSU Cahaya Medika Makassar which has integrated AI for radiology and pathology since 2024 (with a capacity of 500 beds and 20+ AI tools). Law No. 17/2023 on Health (Article 220) and Permenkes 75/2020 on AI in Health require accuracy >90%, algorithm transparency, and liability sharing between doctors-AI-vendors. However, legal risks emerge: AI diagnosis errors (15% false positive, Kemenkes 2025), malpractice claims (Article 29 Law 29/2004), and data responsibility (UU PDP 27/2022). A case at a Jakarta hospital (2024) lost a Rp2 billion lawsuit over AI breast cancer misdiagnosis; RSCM Makassar recorded 3 AI error incidents in 2025. Without risk management (policy, training, insurance), RSU Cahaya Medika is vulnerable to litigation, reputational damage, and costs. This study aims to identify main legal risks of AI diagnosis use and design an effective legal risk management framework according to ISO 31000 and Indonesian regulations. This research uses a qualitative case study with a normative-empirical juridical approach, involving in-depth interviews with 25 key informants, AI system observations, and document analysis. The results show that the main legal risks include criminal and civil malpractice due to AI errors, non-compliance with UU Health and Permenkes AI regulations, and complex liability sharing between doctors-vendor-AI-hospitals. The effective legal risk management framework must include risk identification, risk assessment, risk treatment, and continuous risk monitoring according to ISO 31000 standards.
Co-Authors Mohammad Yusuf Rakhmatullah Muhammad Takwa