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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal FATEKSA : Jurnal Teknologi dan Rekayasa Akrab Juara : Jurnal Ilmu-ilmu Sosial Reviu Akuntansi, Manajemen, dan Bisnis Jurnal Teknologi dan Manajemen Industri Terapan Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Artificial Intelligence and Digital Business Eastasouth Journal of Effective Community Services Jurnal Pengabdian Masyarakat dan Riset Pendidikan Technologia Journal Technologia Journal Programming and Algorithm Fundamentals Intelligent Systems and Robotics
Rahanra, Nicodemus
Universitas Satya Wiyata Mandala
Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Social Sciences Other

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Journal : intelligent systems and robotics

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Explainable Artificial Intelligence Methods for Autonomous Robot Decision Making: A Multi Agent Framework with Safety Assurance and Ethical Constraint Optimization Harry Setya Hadi; Nicodemus Rahanra
Intelligent Systems and Robotics Vol. 1 No. 1 (2026): February: Intelligent Systems and Robotics
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isr.v1i1.43

Abstract

Autonomous decision-making systems increasingly rely on complex artificial intelligence models to operate in dynamic and safety-critical environments. While these models provide strong predictive capabilities, their black-box nature limits transparency, trust, and accountability. This study proposes a structured research methodology for integrating Explainable Artificial Intelligence (XAI) into autonomous decision-making systems. The research adopts a conceptual–analytical approach to develop an explainability-oriented framework that embeds transparency across perception, decision-making, and action execution stages. The methodology includes literature-driven problem identification, conceptual framework construction, classification and mapping of XAI methods, and formulation of explainability evaluation criteria. The results demonstrate that effective explainability in autonomous systems requires a hybrid integration strategy, combining in-model transparency with post-hoc explanation mechanisms. A structured mapping of XAI techniques to autonomous system components and a conceptual decision-flow diagram are presented to illustrate explainability integration. The findings highlight that layered and context-aware explainability enhances system interpretability, supports human oversight, and improves safety relevance without compromising autonomous operation. This study contributes a reusable methodological foundation for the design and evaluation of explainable autonomous systems, offering practical guidance for future empirical validation and real-world deployment in safety-critical applications.
Co-Authors Ahmad Ashifuddin Aqham Alisyah Pitri Amiruddin. A Andriyana, Erni Arfan. Palumpun ST,MT Cakranegara, Pandu Adi Dewanto Dewanto Dharsono, Wardhana Wahyu Dina Destari Eko Siswanto Ellyawati , Noor Harry Setya Hadi Harsya, Rabith Madah Khulaili Hermanus Jimy Suripatty Irianty Tampubolon Mawene, Brenstein Mira Wellya Fatma Mohammad Edy Nurtamam, Mohammad Edy Noviyanto, Jemy Paulus Boli Pratiwi, Vidya Rahanra, Musa Henri Janto Rahmawati Raymond, Christian Paul Santosa, Tomi Apra Satriawansyah, Tri Sukaesih, Atjih Suripatty, Hemanus J. Tebay, Selvi Thaniket, Rooy M. Toha, Abdul Hamid Usman Tahir Wahyudin Waroi, Elsina Novela Wiai, Steven Antonio