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All Journal Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK)
Zahra, Y
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Other

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Understanding and Mitigating AI-Generated Hoax Information Zahra, Y
Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK) Vol. 3 No. 2 (2025): JAFOTIK - August
Publisher : PT. Lentera Ilmu Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/jafotik.v3i2.84

Abstract

The rapid advancement of artificial intelligence has enabled the creation of highly convincing hoax information, posing serious challenges to information integrity and public trust. This study aims to understand the characteristics of AI-generated hoaxes and propose effective strategies to detect and mitigate their impact. A mixed-method framework was adopted, combining content analysis of AI-generated texts to identify patterns, vulnerabilities, and intervention points, with machine learning techniques for detection and social analysis to capture human and policy dimensions. Validation of the framework demonstrated improved detection accuracy, reduced misinformation reach, and stronger user resilience when supported by transparency measures and digital literacy efforts. The study contributes by offering a structured detection–response cycle that integrates technical, social, and policy approaches. This framework provides governments, organizations, and individuals with practical tools to anticipate and respond to the risks of AI-driven misinformation, ultimately strengthening digital resilience.
Ethical and Legal Implications of AI in Decision-Making Zahra, Y; Amirah
Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK) Vol. 2 No. 2 (2024): JAFOTIK - August
Publisher : PT. Lentera Ilmu Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/jafotik.v2i2.42

Abstract

This study explores the ethical and legal implications of integrating artificial intelligence (AI) into decision-making processes across various industries. As AI systems become increasingly prevalent, concerns arise regarding their transparency, fairness, and accountability. The study reviews examples from healthcare, finance, criminal justice, human resources, and retail to highlight issues such as bias, lack of transparency, and privacy concerns. Current regulations often inadequately address the unique challenges posed by AI, particularly regarding accountability and the ethical use of personal data. By developing a comprehensive framework that integrates ethical principles—such as fairness, justice, and autonomy—with legal concepts like liability and data protection, the study proposes practical solutions to mitigate these risks. The findings underscore the need for enhanced oversight, rigorous validation, and transparent practices to ensure AI systems are used responsibly, thereby aligning technological advancements with ethical and legal standards.
Co-Authors Amirah