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All Journal Jurnal Pengabdian Masyarakat Journal of Electrical Engineering and Informatics Media Elektrik
azizah fauziah misbahuddin
Universitas Negeri Makassar, Indonesia
Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Social Sciences

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PRIORITIZING THE RENEWABLE ENERGY TECHNOLOGIES IN TANAKEKE ISLAND, SOUTH SULAWESI: AN AHP APPROACH azizah fauziah misbahuddin; Afif Fahmi Misbahuddin
Jurnal Media Elektrik Vol. 22 No. 3 (2025): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v22i3.9203

Abstract

The transition toward sustainable and decentralized energy systems has heightened the urgency for renewable energy adoption, particularly in off-grid and remote areas. In Indonesia, many island communities remain disconnected from the central electricity grid and face chronic energy access issues. One such case is the Tanakeke Archipelago, located in Takalar Regency, South Sulawesi, where residents experience limited and unreliable electricity supply despite ongoing government electrification programs. This study aims to identify the most suitable renewable energy technology for Tanakeke Island using the Analytic Hierarchy Process (AHP), involving six key criteria: local natural resource potential, technical feasibility, investment and operational costs, system reliability, social acceptance, and environmental impact. Four alternative technologies were evaluated: Solar Power Plant (PLTS), Wind Power Plant (PLTB), Wave Power Generator (PLTO), and Micro Hydro Power Plant (PLTMH). Expert input was gathered from academics and local community figures. The results indicate that Wind Power Plant (PLTB) ranks highest with a global priority score of 2.72, followed by Solar Power Plant (PLTS) with 1.78, Wave Power Generator (PLTO) with 1.09, and Micro Hydro Power Plant (PLTMH) with 0.41. Among the six criteria, Technical Feasibility held the highest weight (0.32), followed by Local Resource Potential (0.25) and Investment Cost (0.21). These findings highlight that technical and resource-based considerations are the most influential in determining the appropriate energy solution for Tanakeke Island. This study provides a structured and data-driven approach to aid local governments and stakeholders in planning sustainable and context-appropriate energy infrastructure in underserved island communities.
Transient Stability Analysis of Inverter-Dominated Microgrids using Physics-Informed Deep Learning Andi Nur Faisal; Azizah Fauziah Misbahuddin; Andi Shridivia Nuran
Journal of Electrical Engineering and Informatics Vol. 3 No. 2 (2026): Journal of Electrical Engineering and Informatics
Publisher : Fakultas Teknik Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jeeni.v3i2.12490

Abstract

Inverter-dominated microgrids exhibit low rotational inertia and fast electromagnetic dynamics, making transient stability assessment significantly more challenging than in synchronous machine dominated systems. This paper proposes a physics informed deep learning (PIDL) framework to estimate post disturbance stability status and critical clearing time (CCT) directly from short window dynamic trajectories while embedding nonlinear inverter dynamics into model training. A total of 1200 disturbance scenarios were generated from reduced order time domain simulations of droop controlled inverter microgrids with randomized virtual inertia, droop damping, fault severity, clearing time, and stochastic renewable fluctuations. The proposed architecture combines a bidirectional temporal encoder with dual output heads and physics residual regularization, followed by two stage optimization (Adam and L-BFGS). On the held out test set, the model achieved 95.56% accuracy, 97.40% precision, 97.40% recall, and 97.40% F1-score for transient stability classification, with CCT error of 29.67 ms MAE and 45.55 ms RMSE. Inference speed reached 1.57 ms per sample, outperforming direct numerical simulation (8.37 ms per sample), and robustness testing under ±20% parameter scaling maintained 95.56% accuracy. These results indicate that integrating physical constraints with deep learning yields a practical and computationally efficient tool for real-time transient stability monitoring in inverter dominated microgrids.
Sosialisasi Penggunaan Bioaditif untuk Efisiensi Bahan Bakar pada Alat Mesin Pertanian di Kabupaten Takalar Azizah Fauziah Misbahuddin; Andi Nur Faisal; Andi Shridivia Nuran; Hamidah Hamris; Ramli Rasjid
Jurnal Pengabdian Masyarakat Vol. 4 No. 1 (2026): Jurnal Pengabdian Masyarakat (Abdimas)
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/abdimas.v4i1.12488

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pemahaman petani terhadap penggunaan bioaditif Econella sebagai solusi efisiensi bahan bakar pada alat dan mesin pertanian di Kabupaten Takalar. Metode yang digunakan meliputi pre-test, sosialisasi, demonstrasi penggunaan bioaditif, dan post-test untuk mengukur tingkat pemahaman peserta. Kegiatan dilaksanakan pada tanggal 16 Maret 2026 dengan melibatkan 7 orang petani. Hasil kegiatan menunjukkan adanya peningkatan yang signifikan pada tingkat pemahaman peserta, ditunjukkan dengan kenaikan rata-rata skor dari 17 menjadi 40 atau meningkat sebesar 135%. Seluruh peserta mengalami peningkatan kategori pemahaman dari tidak tahu menjadi tahu dan sangat paham, serta menunjukkan minat untuk menggunakan bioaditif. Dengan demikian, kegiatan sosialisasi ini terbukti efektif dalam meningkatkan literasi teknologi petani dan berpotensi mendorong penggunaan bioaditif untuk efisiensi bahan bakar pada sektor pertanian.
Co-Authors Afif Fahmi Misbahuddin Andi Nur Faisal Andi Shridivia Nuran Hamidah Hamris Ramli Rasjid