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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 (On Progress)
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
An innovative winding configuration to enhance 3-phase induction motor performance Anthony, Zuriman; Nazir, Refdinal; Hamid, Muhammad Imran
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.