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All Journal Jurnal Pengabdian Masyarakat Micronic: Journal of Multidisciplinary Electrical and Electronics Engineering
Nuran, Andi Shridivia
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Humanities Computer Science & IT Education Electrical & Electronics Engineering Engineering Mechanical Engineering Social Sciences

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Optimalisasi Deteksi Kerusakan Elektrikal Panel Surya dengan Transfer Learning dan Augmentasi Terkontrol berbasis YOLOv8 Andi Nur Faisal; Nuran, Andi Shridivia
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: 10.61220/912s5p11

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; Nuran, Andi Shridivia; Nurislamiah, Fathiyah
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: 10.61220/77ghpj32

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
Pengenalan dan Pemanfaatan Kecerdasan Buatan Multiplatform untuk Pengembangan Bahan Ajar Digital yang Adaptif dan Konstektual misbahuddin, azizah fauziah; Nuran, Andi Shridivia; Faisal, Andi Nur; Mudarris; Udin
Jurnal Pengabdian Masyarakat Vol. 3 No. 1 (2025): Jurnal Pengabdian Masyarakat (AbdiMas)
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/abdimas.v3i1.8411

Abstract

Pesatnya perkembangan teknologi kecerdasan buatan (Artificial Intelligence/AI) memberikan peluang besar dalam dunia pendidikan, khususnya dalam pengembangan bahan ajar digital yang lebih adaptif dan kontekstual. Namun, pemanfaatan teknologi ini di kalangan guru, khususnya di daerah seperti Kabupaten Barru, masih tergolong rendah akibat keterbatasan pengetahuan dan keterampilan teknis. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memperkenalkan dan melatih para guru di SMKN 5 Barru dalam menggunakan platform AI untuk menyusun bahan ajar digital yang sesuai dengan karakteristik siswa dan konteks lokal. Metode pelaksanaan kegiatan meliputi ceramah, demonstrasi penggunaan AI multiplatform (seperti ChatGPT, Canva AI, dan tools edukatif lainnya), serta praktik langsung yang didampingi oleh tim pelaksana. Evaluasi dilakukan melalui pre-test dan post-test serta penilaian terhadap produk bahan ajar yang dikembangkan peserta. Hasil kegiatan menunjukkan peningkatan signifikan dalam pemahaman dan keterampilan guru, di mana sebanyak 80% peserta mampu mengintegrasikan AI ke dalam proses pengembangan bahan ajar digital. Kegiatan ini membuktikan bahwa pelatihan berbasis praktik langsung dan penggunaan teknologi yang aplikatif dapat meningkatkan kapasitas guru dalam menghadirkan pembelajaran yang lebih inovatif dan relevan dengan kebutuhan peserta didik. Kegiatan ini diharapkan menjadi awal dari transformasi digital dalam proses pembelajaran di sekolah vokasi.
Co-Authors Andi Nur Faisal Aulia Rahmah Faisal, Andi Nur Misbahuddin, Azizah Fauziah Mudarris Mudarris Nurislamiah, Fathiyah Udin