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All Journal Journal of Humanities and Social Studies bit-Tech Jurnal Ilmiah Akuntansi Kesatuan Journal of Business, Management and Social Studies Journal of Mutidisciplinary Issues
Princes, Elfindah
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Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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The Concept of Justice in AI-Driven Legal Decision Making Princes, Elfindah; Rasji, Rasji; Michael
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2338

Abstract

The integration of Artificial Intelligence (AI) into legal decision-making processes has introduced significant advancements in efficiency and predictive capability. However, its implications for justice—particularly fairness, impartiality, transparency, and due process—remain critically debated. This study employs a Systematic Literature Review (SLR) methodology to examine how AI-driven legal decision-making aligns with classical and contemporary philosophical concepts of justice. Drawing on 48 peer-reviewed articles, policy documents, and case studies published between 2015 and 2024, the research identifies four core thematic issues: the persistence of algorithmic bias, the lack of transparency in AI systems, inconsistencies in global regulatory frameworks, and the misalignment of AI logic with moral reasoning. While AI offers promising tools for streamlining judicial processes, its application often risks reinforcing existing inequities and undermining legal principles such as corrective justice and procedural fairness. The study concludes with targeted recommendations for the development of transparent, accountable, and ethically governed AI systems that support—rather than supplant—human judicial discretion. This research contributes to the growing discourse on legal AI by highlighting the necessity of embedding justice-oriented values at the core of technological innovation in the legal sector. This research has several limitations: not based on empirical findings and no validations from experts both in AI and in legal theories. Future research should address these limitations.
Camping Site Recommendation System Using Collaborative Filtering Method on Campsite Indonesia Mobile Application Cakrawala, Emerald Shan; Princes, Elfindah
Jurnal Ilmiah Akuntansi Kesatuan Vol. 13 No. 6 (2025): JIAKES Edisi Desember 2025
Publisher : Institut Bisnis dan Informatika Kesatuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37641/jiakes.v13i6.4525

Abstract

Information overload in tourism applications poses significant challenges for users selecting relevant destinations from numerous options. This research implements Collaborative Filtering (CF) to address information overload in the Campsite Indonesia mobile application, where users face difficulties choosing from 246 camping locations. Three CF variants are evaluated: User-Based CF, Item-Based CF, and Hybrid Collaborative Filtering. The dataset comprises 746 users, 246 camping locations, 350 explicit feedback interactions (likes), and 7,306 implicit feedback interactions (views) from August 2022 to July 2025, with 94.05% sparsity in the user-item interaction matrix. The research employs CRISP-DM methodology encompassing data preparation, modeling, evaluation, and deployment phases. Experimental results demonstrate that Item-Based CF achieves superior performance with Hit Rate@10 of 0.2222 and NDCG@10 of 0.0743, significantly outperforming User-Based CF (HR@10: 0.0556, NDCG@10: 0.0215) and Hybrid CF (HR@10: 0.0000, NDCG@10: 0.0000). Item-Based CF also exhibits the highest coverage (41.10%) with 60 unique recommended locations. The system is deployed through a Flask-based REST API server with five endpoints for recommendation scenarios. This research contributes domain-specific insights for camping location recommendations in developing countries. 
Co-Authors Abdinagoro, Sri Bramantoro Adler Haymans Manurung Amini, Nuzulia Bambang Setiono Cakrawala, Emerald Shan Erlis, Erlis Firmansyah, Fatah Panji Idris Gautama So, Idris Gautama Michael Oetama, Raymond Sunardi Pangaribuan, Christian Haposan Rasji, Rasji Romprasert, Suppanunta Setiawan, Johan Silalahi, Wilma Soeryanto, Novianti Yosevine, Prisca