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All Journal Riau Journal of Computer Science JURNAL MEDIA INFORMATIKA BUDIDARMA Applied Information System and Management Informatika Zonasi: Jurnal Sistem Informasi REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer International Journal of Robotics and Control Systems Mejuajua Jurnal Minfo Polgan (JMP) Prosiding Snastikom Journal of Community Engagement Research for Sustainability RJOCS (Riau Journal of Computer Science) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Riau Jurnal Teknik Informatika Jurnal Kajian Ilmu dan Teknologi (JKIT)
Hendri Maradona, Hendri
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Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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Reviewing The Combination of Case-Based Reasoning and Machine Learning for Improving a Decision Support System Hendri Maradona; Fatchul Arifin; Sri Andayani
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v9i1.48904

Abstract

This study investigates the integration of case-based reasoning (CBR) with machine learning (ML) to enhance decision support systems. Due to the inadequate synthesis of empirical data in this domain by previous research, we undertook a systematic review of 46 indexed journal articles published between 2019 and 2024. The review adhered to PRISMA principles to ensure a transparent and rigorous selection and analysis procedure. We analyzed integration architectures and documented performance results, application areas, and persistent implementation challenges. The research indicates that hybrid CBR-ML systems typically surpass single-method systems in accuracy, precision, and flexibility, with an average improvement of approximately 7% over CBR-only systems. Sequential and ensemble approaches typically demonstrate effectiveness, though weighted hybrid designs often achieve superior precision and recall, particularly in complex problem domains such as healthcare and finance where accuracy is critical. Researchers based in Asia authored the majority of the reviewed studies, with contributions from Europe and Africa following. These regions concentrated high-impact applications in healthcare, finance, manufacturing, and environmental management. Notwithstanding these developments, several enduring challenges persist, including substantial computational demands, vulnerability to variations in data quality, and the continuing scarcity of clearly articulated evaluation protocols, which hinder the effective implementation of high-impact applications across these regions. Overall, existing findings suggest that integrating reasoning-oriented approaches with learning-based methods can yield a balanced trade-off between predictive accuracy and interpretability. 
Co-Authors Agung Setiawan Ahmad Albar Saragih Annisa Maulana, Dwi Asari, Wahyu Asep Supriyanto Basorudin - Bunda, Yola Permata Darmanta Sukrianto Darmanta Sukrianto Desiyanti, Vivi Dona Dona Dona Dona, Dona Fatchul Arifin Fatmawati, Dinni Hary Kurniawan Imam Rangga Bakti Jannah, Wirda Jannatul Khairul Sabri Khairul Sabri Khusairi, Fajri Kiki Yasdomi Kiki Yasdomi M Muhammadyodi Maharani Maharani Masdewi Masdewi Mirajul Rifqi Mi`rajul Rifqi Mi’rajul Rifqi Muhammad Ridho Muhammad Romi Nst Nasrizal Putra, Agus Mulya Rahayu, Dina Ridwan Rifki, Mi'rajul Rifqi, Mi'rajul Rifqi, Mi’rajul Rifqi, Mi`rajul Rifqi, Mi’rajul Rina Febrinova, Rina Rohmah, Rina Ari Sabri, Khairul Satria Riki Mustafa, Satria Riki Sri Andayani Sukrianto , Darmanta Susi Rahayu Urfi Utami Utami, Urfi Yuliansyah, Chandra