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All Journal Micronic: Journal of Multidisciplinary Electrical and Electronics Engineering
Andi Shridivia Nuran
State University of Makassar
Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering

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Optimalisasi Deteksi Kerusakan Elektrikal Panel Surya dengan Transfer Learning dan Augmentasi Terkontrol berbasis YOLOv8 Andi Nur Faisal; Andi Shridivia Nuran
Micronic: Journal of Multidisciplinary Electrical and Electronics Engineering Volume 3, Issue 1, Juni 2025
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/jm3e.v3i1.970

Abstract

Electrical fault detection in solar panels is a critical challenge in maintaining the efficiency of large-scale photovoltaic energy systems. This research develops a deep learning-based automated classification model by leveraging the YOLOv8-CLS architecture, refined through transfer learning and systematically applied data augmentation. The dataset consists of two panel condition classes, clean and electrical-damage, which were preprocessed through image size normalization, tensor transformation, and augmentation using RandAugment and random erasing. The model was trained for 15 epochs with fine-tuning applied to the head, while the backbone retained pretrained weights. Performance evaluation showed that the model achieved a Top-1 Accuracy of 98.21%, with precision for the electrical-damage class reaching 100%, recall at 94.12%, and an F₁-score of 0.9697. Furthermore, an average inference time of 18.82 milliseconds per image demonstrates high computational efficiency for real-time deployment. These findings indicate that the integration of the YOLOv8 architecture with transfer learning and controlled augmentation is effective for detecting electrical faults in solar panels and is suitable for implementation in automated monitoring systems based on edge or cloud computing.
Studi Audit Energi pada Gedung Sekolah untuk Optimalisasi Penggunaan Energi Aulia Rahmah; Andi Shridivia Nuran; Fathiyah Nurislamiah
Micronic: Journal of Multidisciplinary Electrical and Electronics Engineering Volume 3, Issue 1, Juni 2025
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/jm3e.v3i1.1014

Abstract

An energy audit at Madrasah Ibtidaiyah Negeri 1 Gowa was conducted to evaluate the efficiency of electricity consumption and identify potential energy savings in daily school operations. The methods included a preliminary energy audit involving annual energy consumption data collection and calculation of Energy Consumption Intensity (ECI), as well as a detailed audit of the lighting system. The results showed that the school building was categorized as efficient, with an initial ECI value of 0.701 kWh/m²/month. However, several rooms were found to have lighting levels below the standard, prompting the addition of energy-saving LED lamps. After these improvements, the ECI increased to 1.39 kWh/m²/month but remained within the efficient category. This audit demonstrates that improving lighting quality can be achieved without sacrificing overall energy efficiency and provides concrete recommendations for school energy management to support sustainable energy efficiency and environmental preservation
Co-Authors Andi Nur Faisal Aulia Rahmah Fathiyah Nurislamiah