ALGORITHMIC GHARAR AND LEGAL CERTAINTY IN BLOCKCHAIN-BASED SMART CONTRACTS: A COMPARATIVE STUDY OF INDONESIAN LAW AND ISLAMIC BUSINESS LAW

Authors

  • Didi Sukardi IAIN Syekh Nurjati Cirebon
  • Achmad Otong Busthomi Universitas Islam Negeri Siber Syekh Nurjati Cirebon
  • Afif Muamar Universitas Islam Negeri Siber Syekh Nurjati Cirebon

DOI:

https://doi.org/10.47685/focus.v7i1.915

Keywords:

Algorithmic Gharar; Blockchain; Smart Contracts; Indonesian Law; Islamic Business Law; Governance

Abstract

This article examines the legal certainty of blockchain-based smart contracts within Indonesia’s dual framework of positive law and Islamic business law. It asks how Indonesian contract and electronic-transaction rules accommodate automated agreements, how automation reshapes gharar, and what governance safeguards are needed. The study employs normative-comparative legal research, using legislation, regulatory instruments, Sharia standards, and scholarship selected for relevance and authority. Materials were analysed through doctrinal interpretation, cross-jurisdictional comparison, and thematic mapping of uncertainty. The findings indicate that Indonesian law may recognize smart contracts through contract and electronic-transaction rules, but the framework remains fragmented. Automation can reduce opportunistic non-performance while relocating uncertainty to code opacity, oracle reliability, tokenized asset rights, and irreversible execution. The article conceptualizes “algorithmic gharar” as an analytical lens, not a fiqh category, and proposes a Sharia-Compliant Smart Contract Governance model combining readable legal terms, code and Sharia audits, accountable data governance, limited reversibility, and coordinated oversight

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Published

2026-03-25

How to Cite

Sukardi, D., Busthomi, A. O., & Muamar, A. (2026). ALGORITHMIC GHARAR AND LEGAL CERTAINTY IN BLOCKCHAIN-BASED SMART CONTRACTS: A COMPARATIVE STUDY OF INDONESIAN LAW AND ISLAMIC BUSINESS LAW. FOCUS: Jurnal of Law, 7(1), 40–48. https://doi.org/10.47685/focus.v7i1.915