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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Applied Power Engineering (IJAPE) JURNAL NASIONAL TEKNIK ELEKTRO Proceeding of the Electrical Engineering Computer Science and Informatics Briliant: Jurnal Riset dan Konseptual Indonesian Journal of Electrical Engineering and Computer Science Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Andalasian International Journal of Applied Science, Engineering, and Technology Journal of Renewable Energy, Electrical, and Computer Engineering Andalas Journal of Electrical and Electronic Engineering Technology Jurnal Andalas: Rekayasa dan Penerapan Teknologi ASEAN Marketing Journal Journal Of Artificial Intelligence And Software Engineering Jurnal INFOTEL Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering)
Refdinal Nazir
Universitas Andalas
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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Enhanced incremental conductance MPPT method for maximizing photovoltaic power generation Asnil, Asnil; Nazir, Refdinal; Krismadinata, Krismadinata; Nasir, Muhammad
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i4.pp2757-2767

Abstract

This research proposes an enhanced maximum power point tracking (MPPT) algorithm that integrates the variable step size (VSS) method to significantly improve power extraction from photovoltaic (PV) systems. The primary objective is to optimize performance under dynamic environmental conditions. Through comprehensive experimental studies, the proposed algorithm’s performance was evaluated and directly compared against conventional incremental conductance (INC) and perturb and observe (P&O) algorithms. The results demonstrate a substantial increase in power generation, with the proposed algorithm delivering 18.79% more power compared to INC and 39.67% more power than P&O. These findings underscore the efficacy of the developed algorithm at improving the efficiency and robustness of PV power generation, particularly in variable operating environments.
A Classification Model of Children’s Digital Device Dependency Based on the Learning Vector Quantization (LVQ) Algorithm Urva, Gellysa; Nazir, Refdinal
Journal of Artificial Intelligence and Software Engineering Vol 5, No 4 (2025): Desember
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i4.8244

Abstract

Digital device dependency among children has become a critical issue in the modern era, influencing cognitive, social, and health aspects. Excessive use of digital devices may lead to decreased concentration, academic performance, and social interaction. The identification of children's digital dependency levels has often relied on manual observation by parents or teachers, which tends to be subjective. Therefore, this study aims to develop a classification model for children's digital device dependency using the Learning Vector Quantization (LVQ) algorithm. The data were collected through a questionnaire distributed to 110 respondents, consisting of parents of elementary school students in Dumai City. The questionnaire contained 34 items measured using a five-point Likert scale (1–5). The data were processed using Python with supporting libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, and Neupy. The experimental results showed that the LVQ algorithm successfully classified children's dependency levels into three categories low, moderate, and high with an accuracy of 87.5%, an average precision of 85.4%, and an average recall of 86.2%. The findings revealed that most children belong to the moderate dependency category, with an average score of 3.03. The main factors influencing digital dependency include usage duration, habits of using devices while eating or before sleeping, and decreased social interaction. The application of the LVQ algorithm proved effective in identifying children’s digital usage patterns and can serve as a foundation for developing early detection systems and promoting digital literacy policies within elementary education environments
Analisis Variasi Lebar Magnet pa ANALISIS PENGARUH LEBAR MAGNET NEODYMIUM PADA KINERJA PERMANENT MAGNET SYNCHRONOUS GENERATOR (PMSG) 12 SLOT 8 POLE MENGGUNAKAN SOFTWARE MAGNET INFOLYTICA Muhammad Afdhal Izzati; Refdinal Nazir; Anna Cyntia Pahsa De Yudanur; Maulana Naseem Hamed
BRILIANT: Jurnal Riset dan Konseptual Vol 11 No 2 (2026): Volume 11 Nomor 2, Mei 2026
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/briliant.v11i2.2378

Abstract

Permanent Magnet Synchronous Generator (PMSG) with 12 slots 8 poles, using Magnet Infolytica software. The main focus of the research is to evaluate the impact of changes in the width of the permanent magnet (32 mm to 52 mm) on electromagnetic characteristics, such as current, voltage, torque, input power, output power, and energy conversion efficiency. Simulations were carried out at a rotational speed of 750 rpm with a resistive load of 70 Ohm. The results showed that increasing the width of the permanent magnet had a positive impact on the performance of the PMSG, the best generator at a variation of the magnet width of 44 mm which had an efficiency of 88.6% with a current of 8.9 A, a voltage of 565.97 V, a torque of -66.08 N/m, an input power of 5189.79 Watts, and finally an output power of 4598.67 Watts. These findings are expected to be a reference in designing an optimal PMSG for small to medium-scale renewable energy power generation applications, especially in Wind Power Generation (PLTB) systems.
Enhancing the performance of 3-phase induction motors by developing a 40-degree asymmetrical coil design for the stator coil Zuriman Anthony; Refdinal Nazir; Muhammad Imran Hamid
Indonesian Journal of Electrical Engineering and Computer Science Vol 42, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v42.i3.pp678-687

Abstract

The use of three-phase induction motors in industry is very widespread due to their durability, simplicity, cost, and ease of use. These motors are continuously developed to improve performance. However, the increase in motor performance is directly proportional to the increase in the motor’s cost. Therefore, innovative solutions are needed to make three-phase induction motors more efficient without raising the motor’s price. The study’s goal is to create a motor coil design that won’t cost a lot more but will make 3-phase induction motors more efficient. This study developed a 2-layer coil design with a pair of poles for each layer. The second coil layer is located 40 electrical degrees away from the first layer. In the lab, the motor’s performance was assessed and compared to a conventional motor. This new motor uses identical materials as the conventional model; therefore, it does not incur additional costs. The results showed that this method could increase the rotor speed, output power, efficiency, and load torque of the motor by 0.21%, 16.29%, 15.90%, and 16.05%, respectively.
Literature Review: Quantification of Loss and Emission Reductions in Distributed Generation Optimization Rosnita Rauf; Refdinal Nazir; Muhammad Nasir
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 6 No. 1 (2026): March 2026
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v6i1.25820

Abstract

The integration of Distributed Generation (DG) into modern power distribution networks plays a vital role in enhancing operational efficiency and driving global decarbonization targets. However, capturing the full technical and environmental advantages of DG requires precise multi-objective optimization. This study presents a systematic literature review aimed at evaluating, synthesizing, and quantifying the methodologies used for power loss minimization and carbon emission reductions within radial distribution networks. Adhering to the PRISMA 2020 framework, a rigorous bibliometric and content analysis was performed using Publish or Perish (PoP) and VOSviewer. Out of 323 initially screened articles indexed in the Scopus database from 2017 to 2025, 112 peer-reviewed papers met the strict inclusion criteria and were comprehensively analyzed. The synthesis reveals that optimal DG placement utilizing swarm intelligence techniques—predominantly Particle Swarm Optimization (PSO) and Genetic Algorithms (GA)—consistently achieves substantial improvements, yielding active power loss reductions between 40% and 94% and annual greenhouse gas emission mitigations ranging from 25% to 65%. Bibliometric mapping highlights a mature focus on voltage profile enhancement and network reconfiguration, while critical gaps remain in standardizing dynamic hosting capacity and life-cycle assessment (LCA) frameworks for emissions. Although simulation-based optimization models show high technical maturity, they still require real-world validation. Future research must prioritize dynamic operational strategies under stochastic renewable uncertainty to bridge this implementation gap.
The Review of ELC and STATCOM Role in Electrical Power Generation from Renewable Energy Sources Based Three-Phase Self-Excited Induction Generator Melda Latif; Refdinal Nazir; Krismadinata Krismadinata
Andalasian International Journal of Applied Science, Engineering and Technology Vol. 6 No. 2 (2026): July 2026
Publisher : LPPM Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/aijaset.v6i2.354

Abstract

This paper reviews various control strategies employed in Electronic Load Controllers and Static Synchronous Compensators (STATCOMs) for renewable energy system (RES)-based Self-Excited Induction Generators (SEIGs), with particular emphasis on performance indicators such as voltage and frequency regulation, harmonic distortion mitigation, and dynamic response characteristics. The review was conducted using articles published in reputable scientific journals. A total of 52 articles were selected and analyzed based on predefined inclusion criteria. The findings indicate that the investigated control approaches range from conventional controllers, such as Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers, to intelligent control techniques, including Fuzzy Logic Controllers (FLCs) and Artificial Neural Networks (ANNs). Furthermore, hybrid control schemes, such as Fuzzy-PI controllers and optimization-assisted intelligent controllers (e.g., PI-PSO), have also been widely reported in the literature. The limitations of conventional PI/PID controllers, particularly their fixed gain parameters that are optimized for specific operating conditions, can be effectively addressed through intelligent control techniques. These advanced approaches provide improved adaptability, enhanced dynamic response, and superior harmonic compensation performance. As a result, the reported Total Harmonic Distortion values for both voltage and current are generally maintained within the limits specified by IEEE Standard 519, namely below 5% for both voltage THD and current THD.
An innovative winding configuration to enhance 3-phase induction motor performance Zuriman Anthony; Refdinal Nazir; Muhammad Imran Hamid
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i1.pp82-94

Abstract

A three-phase induction motor is extensively employed in the industrial sector due to its robustness and cost-effectiveness. An enhancement of this motor is underway to optimize its performance. Enhancing motor performance is intricately linked to escalating motor production expenses. Consequently, an innovative strategy is essential to enhance motor performance without incurring substantial extra expenses. This study aimed to introduce a novel approach for designing 3-phase induction motor coils to enhance motor performance without significant additional expenses. This study concentrated on the design of a 3-phase induction motor coil, rated at 1 HP, 380 V, 2 A, 4 poles, and 24 slots, and arranged in a Y-connection. We fabricated the coil using a dual-layer approach, creating magnetic pole pairs on each layer. The study's results demonstrated an improvement in output power, efficiency, load torque, and rotor speed of the new motor design, specifically by 19.32%, 16.26%, 18.48%, and 0.72%, respectively. Despite a 3.05% rise in motor coil current during peak load conditions, the motor's overall performance significantly improves, enhancing its capabilities without considerable additional expenses. This study claims that the suggested way can make other 3-phase induction motors work better without costing a lot more.
Banana leaf wax performance as a coating material to reduce fouling and heat for photovoltaic improvement Andi Pawawoi; Refdinal Nazir; Muhammad Imran Hamid; Fajril Akbar
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i3.pp1212-1222

Abstract

The growing dependence on limited fossil fuels and their environmental impact drive the adoption of renewable energy, with photovoltaics (PV) being a leading option. However, PV performance often declines due to elevated operating temperatures and surface fouling, especially in tropical climates, leading to reduced efficiency. To address this, coating materials with dual functionalities of cooling and self-cleaning are needed. This study investigates banana leaf wax as a natural coating to enhance PV performance. The wax was extracted using n-hexane, applied via spray-coating, and characterized through light transmittance tests, scanning electron microscope (SEM) imaging, water contact angle (WCA), adhesion analysis, and field trials on PV modules. The wax demonstrated an average WCA of 127°, with a microcrystalline structure supporting hydrophobic and self-cleaning properties. Field implementation showed that a 9 μm wax layer reduced PV module temperature by approximately 5 °C and increased output power by 15-20% under high irradiance (G ≈1200 W/m²). The cooling effect proved more significant than transmission losses, confirming the potential of banana leaf wax as an effective tropical PV coating. Nevertheless, further studies are required to optimize thickness, strengthen adhesion through hybrid formulations, and integrate the material into advanced optoelectronic coatings for sustainable efficiency improvements.
Co-Authors ,, Kamsory Adytia Putra, Ryan Ahmad Ahmad Alfitman Alfitman Alfitman Alfitman Amalia, Rizka Andi Pawawoi Andi Pawowoi Anna Cyntia Pahsa De Yudanur Arief Rufiyanto Asnil Asnil Axel Doriza Dendi Adi Saputra M, Dendi Adi Dewi Purnama Sari Diana, Mery Eka Fitrianto Eka Fitrianto Eka Fitrianto Eka Fitrianto, Eka Elsi Alfionita Syawal Fajril Akbar Fitrianto, Eka Gellysa Urva Ghazali, Syafii Hamdi Reza Hasmat Malik Hidayat, Rahmat Kamsory , Kamsory Kamsory, Kamsory Kananda, Kiki Kiki Kananda Krismadinata Krismadinata Krismadinata Krismadinata, Krismadinata Kurniasih, Novi M. Yogi Riyantama Isjoni Maulana Naseem Hamed Melda Latif Melda Latif Mery Diana Mochammad Rismansyah Muhammad Afdhal Izzati Muhammad Hadi Putra, Muhammad Hadi Muhammad Imran Hamid Muhammad Nasir Muhammad Nurdin Muhammad Rahman Muharram, Igo Cikal Nasir, Muhammad Novi Kurniasih Pinto Anugrah Purnama Sari, Dewi Rahmat Hidayat Refki Budiman Reza, Hamdi Rika Ampuh Hadiguna Riska Amalia Rismansyah, Mochammad Rizka Amalia Rosnita Rauf Rufiyanto, Arief Ryan Adytia Putra Syafii . Syafii Ghazali Vera Pujani Vera Pujani Wahyu Rizki Muslyadi Yazrina Yahya Yazrina Yahya Yudi Arfan Zuheldi, Zuheldi Zuriman Anthony Zuriman Anthony