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Fadlina
Universitas Budi Darma
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Hybrid Fuzzy-Based Decision Modeling for Anomaly Prioritization in Smart Grid Systems Fadlina; Sugi Hartono Sinambela; Meng-Yun Chung
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 2 (2026): June 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/z5z1bk11

Abstract

Purpose – This study aims to develop an uncertainty-aware decision-support framework for prioritizing anomaly events in smart grid systems, addressing the limitation of existing approaches that focus primarily on binary anomaly detection rather than operational risk-based prioritization. Design/methods/approach – A hybrid framework is proposed by integrating lightweight statistical anomaly screening with a Mamdani-type fuzzy inference system (FIS) that models three risk dimensions: Impact, Likelihood, and Criticality. To enhance ranking performance while maintaining interpretability, fuzzy membership parameters and rule weights are optimized using a genetic algorithm (GA). The model is evaluated using the Open Power System Data dataset with 5-fold cross-validation. Findings - Experimental results show that the proposed model outperforms baseline methods, achieving NDCG@10 of 0.84, Recall@5 of 0.81, and F1-score of 0.86. The framework also reduces false alarm rates and maintains end-to-end latency below 300 ms on ARM-class hardware, demonstrating suitability for real-time edge deployment. Research implications/limitations – The study is limited to a single regional dataset and relies on offline optimization of fuzzy parameters. Future research may explore multi-regional validation, online adaptive learning, and integration with cyber-physical anomaly streams. Originality/value – This study introduces a novel hybrid framework that combines statistical screening, interpretable fuzzy risk modeling, and evolutionary optimization for anomaly prioritization. Unlike conventional detection-focused approaches, it emphasizes ranking quality, uncertainty handling, and real-time embedded feasibility, offering a practical and explainable solution for smart grid operations.
Co-Authors Abdul Karim Abdul Sani Sembiring Akmal Dirgantara Lubis Alwali Daini Udda Siregar AMRIZAL SALIDA Arief Satria Asrini Asrini Atika Suri Bagariang, Luhut F Afriando Darma Taksiah Sihombing, Darma Taksiah Daulay, Nur Hasanah Dicky Marsella Fince Tinus Waruwu Fitriani Fitriani Garuda Ginting Guidio Leonarde Ginting Haeril, Haeril Hery Sunandar Imam Saputra Indarwani, Indarwani Isti Ratnaningtyas, Delthawati Johan, Fakhri Juleha Juleha juminarni, Aryuni Khairah, Miftahul Kurnia Ulfa Kurniawan Kurniawan Lince Tomoria Sianturi Lisra, Lisra Luhut F Afriando Bagariang Mariam Makmur Mas'ud, Busrin Rahana Meng-Yun Chung Muhammad Jarnawi Muhammad Syahrizal Muhammad Taufiq Murdani Murdani Murdani, Murdani Ndruru, Eferoni Nelly Astuti Hasibuan Nurjannah Nurjannah Nurlela Nurlela Pratiwi, Rizka Dwi Ritonga, Soleh Rizky, Nadia Fariza Ronda Deli Sianturi Royanti Manurung Sahat Roni Saidi Ramadan Siregar Setyawati Arbaatun Siregar, Alwali Daini Udda Siregar, Anggi Yakup Siska Subuh Hati Tarigan Sitanggang, Taufan Siti Nurhabibah Hutagalung Sri Wahyuni Jumadi Sugi Hartono Sinambela Surya Darma Nasution Ulfa, Kurnia Usman Usman