APPLICATION OF ALGORITHM TO GENERAL PRINCIPLES OF GOOD GOVERNMENT IN GOOD GOVERNANCE

Abstract

The digital transformation of government in Indonesia has encouraged the use of algorithms and artificial intelligence (AI) systems in various stages of state administration, from risk-based licensing (OSS-RBA) and electronic law enforcement to data-driven decision support systems. This development raises fundamental questions regarding the suitability of algorithm implementation with the General Principles of Good Governance (AUPB) as stipulated in Law Number 30 of 2014 concerning Government Administration, which is a derivative of the concept of good governance. This study aims to examine the extent to which the application of algorithms in administrative decision-making aligns with the principles of legal certainty, accuracy, non-abuse of authority, openness, public interest, and good service, and to identify the legal challenges arising from it. The study used a normative juridical method combined with a systematic literature review of 20 scientific sources published between 2021 and 2026. The results of the study indicate that the implementation of algorithms has the potential to strengthen the efficiency, consistency, and objectivity of public services, but at the same time creates new risks in the form of algorithm opacity (black box), systemic bias, accountability gaps, and unclear shifts in legal responsibility between officials, system developers, and government institutions. This study recommends the need for a legal framework that explicitly integrates the principles of explainability, periodic algorithm audits, and human oversight into the substance of the AUPB so that the implementation of algorithms in government remains consistent with the ideals of good governance.