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LITERATURE ANALYSIS ON THE ROLE OF ARTIFICIAL INTELLIGENCE IN STRENGTHENING CYBERSECURITY IN E-GOVERNMENT SERVICES Erfan Wahyudi; Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.455

The rapid expansion of e-government services has increased the importance of cybersecurity in protecting public digital infrastructure, citizen data, and the continuity of government operations. In this context, Artificial Intelligence (AI) has emerged as a promising approach to strengthening cyber defense through real-time monitoring, anomaly detection, intelligent classification, and adaptive threat response. This study examines the role of AI in strengthening cybersecurity in e-government services through a Systematic Literature Review (SLR) of 27 selected articles published between 2019 and 2025. The review synthesizes the literature at the intersection of AI, cybersecurity, and digital government to identify major research trends, dominant methodological approaches, thematic classifications, and key implementation challenges. The findings show that AI is increasingly positioned not only as a tool for improving administrative efficiency, but also as a strategic enabler of cyber resilience in public-sector digital ecosystems. The literature highlights that machine learning, deep learning, explainable AI, anomaly detection, and privacy-preserving learning models have substantial potential for improving the security of citizen portals, digital identity systems, inter-agency platforms, and smart-government infrastructures. However, implementation remains constrained by fragmented data environments, interoperability problems, institutional readiness gaps, limited explainability, privacy concerns, and the dual-use nature of AI in cyber defense and cyber offense. This study concludes that AI is most effective when integrated into a broader socio-technical framework encompassing governance, accountability, transparency, and organizational capacity.

CONSTITUTIONAL ACCOUNTABILITY OF THE GOVERNMENT FOR MACHINE LEARNING-BASED SYSTEM ERRORS IN DIGITAL PUBLIC SERVICES Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 3 No. 3 (2024): September 2024
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v3i3.480

This study examines the constitutional accountability of the government for machine learning-based system errors in Indonesia’s digital public services. The objective is to analyze how state responsibility should be formulated when digital systems misread data, reject applications, delay access, produce inaccurate classifications, or incorrectly process citizens’ rights. This research applies a qualitative legal method with normative-juridical, conceptual, and socio-legal approaches. The analysis is based on constitutional norms, public service law, government administration law, personal data protection law, electronic-based government regulations, and recent scholarly debates on automated decision-making and public-sector AI governance. The findings show that machine learning-based errors cannot be treated as ordinary technical failures when they affect citizens’ access to public services. Such errors must be understood as failures of public authority because the system operates within the institutional responsibility of the state. Indonesia already has legal foundations for public service, administrative responsibility, digital government, and personal data protection, but it lacks a specific accountability framework for machine learning-based public service errors. This study proposes the concept of state constitutional responsibility for governmental technology failure, consisting of preventive, explanatory, corrective, institutional, and remedial accountability. The contribution of this study lies in framing machine learning errors in public services as constitutional accountability issues, not merely as technical, administrative, or contractual problems.

CONSTITUTIONAL IMPLICATIONS OF THE USE OF MACHINE LEARNING IN INDONESIA’S SOCIAL ASSISTANCE SELECTION AND DISTRIBUTION SYSTEM Erfan Wahyudi; Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 2 No. 3 (2023): September 2023
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v2i3.481

This study examines the constitutional implications of using machine learning in Indonesia’s social assistance selection and distribution system. The main objective is to analyze how algorithmic decision-making may affect citizens’ constitutional rights to social security, welfare, equality before the law, legal certainty, and protection from discrimination. This research applies a qualitative legal method with normative-juridical and socio-legal approaches. The analysis is based on constitutional provisions, statutory regulations, social welfare data governance, and policy documents related to Indonesia’s social assistance system, particularly DTKS and SIKS-NG. The findings show that machine learning may improve targeting accuracy and administrative efficiency in social assistance distribution. At the same time, it may reproduce or intensify existing problems in welfare data, especially when the system relies on incomplete, outdated, biased, or unevenly collected information. Algorithmic discrimination may occur indirectly through proxy variables such as residence, housing condition, employment status, digital access, and household composition. This study argues that machine learning should be positioned only as a decision-support tool, not as an autonomous decision-maker. Its constitutional legitimacy depends on data quality, explainability, meaningful human oversight, contestability, independent audit, and clear institutional accountability. The contribution of this study lies in framing machine learning-based social assistance as a constitutional issue, not merely as a technical matter of prediction accuracy or administrative efficiency.

STATE DIGITAL SOVEREIGNTY IN THE GOVERNANCE OF ARTIFICIAL INTELLIGENCE WITHIN INDONESIA’S GOVERNMENT SYSTEM Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 2 No. 3 (2023): September 2023
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v2i3.482

This study examines state digital sovereignty in the governance of artificial intelligence within Indonesia’s government system. The main objective is to analyze how the state can maintain effective control over AI infrastructure, public-sector data, and government AI systems while preserving constitutional democracy, citizens’ rights, and public accountability. This research applies a qualitative legal method with normative-juridical, conceptual, and socio-legal approaches. The analysis is based on constitutional principles, statutory regulations, policy documents, and recent scholarly debates on AI governance, digital sovereignty, data sovereignty, and public-sector digital transformation. The findings show that Indonesia has developed important foundations for digital government through the Electronic-Based Government System, One Data Indonesia, the Personal Data Protection Law, and the National Strategy for Artificial Intelligence 2020–2045. Yet these instruments have not fully established a comprehensive framework for sovereign AI governance. The main risks include infrastructure dependency, weak control over public-sector data, vendor dominance, limited algorithmic accountability, and unclear responsibility for AI-based administrative decisions. This study argues that state digital sovereignty in AI governance requires strategic infrastructure control, public-sector data sovereignty, algorithmic accountability, meaningful human authority, and democratic oversight. The contribution of this study lies in framing AI governance not merely as a matter of technological innovation or administrative efficiency, but as a constitutional issue concerning the state’s capacity to govern digital power in the public interest.

THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN ELECTION SUPERVISION: BETWEEN DIGITAL EFFECTIVENESS AND THE PROTECTION OF CITIZENS’ POLITICAL RIGHTS Erfan Wahyudi; Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 3 No. 3 (2024): September 2024
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v3i3.483

This study examines the application of artificial intelligence in Indonesian election supervision, focusing on the balance between digital effectiveness and the protection of citizens’ political rights. The objective is to analyze how AI can support the monitoring of electoral violations, hoaxes, deepfakes, digital campaigns, and voter-data risks without weakening democratic principles. This research applies a qualitative legal method with normative-juridical, conceptual, and socio-legal approaches. The analysis is based on constitutional principles, election law, campaign regulations, personal data protection law, election supervisory regulations, and recent scholarly debates on AI, disinformation, deepfakes, and electoral integrity. The findings show that AI may strengthen election supervision by improving the speed, scale, and accuracy of digital monitoring. Yet AI may also create constitutional risks, including wrongful content classification, suppression of legitimate political expression, unequal enforcement, excessive surveillance, privacy violations, and wrongful voter-data profiling. This study argues that AI-based election supervision is constitutionally legitimate only when it is governed by legality, proportionality, transparency, accountability, and meaningful human oversight. The contribution of this study lies in framing AI in election supervision as a constitutional issue concerning political rights, democratic accountability, and electoral integrity, rather than merely as a technological tool for detecting violations.

CONSTITUTIONAL LIMITS ON GOVERNMENT USE OF FACIAL RECOGNITION TECHNOLOGY IN PUBLIC SERVICES AND PUBLIC SECURITY Wiredarme
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 4 No. 3 (2025): September 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v4i3.491

This study aims to examine the constitutional limits of government use of facial recognition technology in public services, public security, and citizen identification. The central issue addressed in this article is the tension between state interests in security and administrative efficiency on the one hand, and the protection of privacy, civil liberties, equality, due process, and constitutional rights on the other. This study employs a qualitative legal research method with a normative-doctrinal approach. The analysis is conducted through statutory, conceptual, and comparative approaches by examining constitutional principles, legal norms, regulatory frameworks, human rights standards, and recent academic literature on facial recognition, biometric governance, digital identity, and public-sector surveillance. The findings show that facial recognition is not merely a technical instrument, but a form of constitutional state action because it enables the government to collect, process, store, and act upon citizens’ biometric identity. In public services, the technology may improve verification and administrative efficiency, but it may also create forced consent and exclusion from essential services. In public security, facial recognition may support lawful identification, but it may also enable mass surveillance, chilling effects, discriminatory outcomes, and unchallengeable decisions. This study contributes a constitutional boundary framework based on legality, legitimate aim, necessity, proportionality, transparency, accountability, non-discrimination, meaningful human review, and effective remedy. The study implies that facial recognition may only be constitutionally justified when technological capability remains subject to strict rights-based legal control.

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