Digital Fiscal Accountability under Indonesian Administrative Law: A Framework for AI-Driven Regional Budget Governance

Fitria Fitria; Eko Nuriyatman; Firdaus Arifin; Rahayu Repindowaty Harahap; Hanif Hardianto; Siti Fatimah; Rustian Mushawirya

doi:10.26740/jsh.v8n2.p324-353

Authors

Fitria Faculty of Law, Universitas Jambi, Indonesia https://orcid.org/0009-0009-4395-4561
Eko Nuriyatman Faculty of Law, Universitas Jambi, Indonesia https://orcid.org/0000-0002-6890-3121
Firdaus Arifin Faculty of Law, Universitas Pasundan Bandung, Indonesia https://orcid.org/0000-0002-4830-7605
Rahayu Repindowaty Harahap Faculty of Law, Universitas Jambi, Indonesia https://orcid.org/0000-0001-7655-5801
Hanif Hardianto Faculty of Law, Social, and Political Sciences, Universitas Terbuka, Indonesia https://orcid.org/0009-0000-3393-9493
Siti Fatimah Faculty of Social Sciences and Law, Universitas Veteran Bangun Nusantara, Indonesia https://orcid.org/0000-0003-3752-1769
Rustian Mushawirya Faculty of Law, Universitas Jambi, Indonesia https://orcid.org/0009-0008-8502-5456

DOI:

https://doi.org/10.26740/jsh.v8n2.p324-353

Abstract

Artificial intelligence (AI) is increasingly used to support public-sector fiscal analysis. Yet, its integration into regional budgeting creates a legal problem that existing Indonesian administrative-law arrangements do not expressly resolve: how AI-generated recommendations may be used without transferring legally binding decision-making authority from public officials to algorithmic systems. This article examines the normative conditions for using AI as a decision-support instrument in regional budget governance. It develops a digital fiscal accountability framework for addressing fiscal turbulence, transparency, responsibility, and reviewability. The research uses a normative juridical method based on statutory and conceptual approaches. Primary legal materials are analyzed to identify rules and principles concerning governmental authority, administrative procedure, accountability, data protection, and digital government, while secondary literature is used to construct the conceptual relationship between administrative law and algorithmic governance. The analysis finds that AI may improve fiscal forecasting, anomaly detection, and scenario analysis, but these benefits do not make AI an autonomous administrative decision-maker. The proposed framework therefore requires human validation, traceable decision records, data-quality controls, algorithmic auditability, contestability, and a clear allocation of responsibility among officials, institutions, and technology providers. Digital fiscal accountability is proposed as a normative reconstruction that connects existing administrative-law principles with AI-specific safeguards rather than as a claim that Indonesian law already comprehensively regulates AI-driven budgeting.

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Digital Fiscal Accountability under Indonesian Administrative Law: A Framework for AI-Driven Regional Budget Governance

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