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Buletin Ilmiah Sarjana Teknik Elektro
Published by Universitas Ahmad Dahlan
ISSN : 26857936     EISSN : 26859572     DOI : 10.12928
Core Subject : Engineering,
Electrical & Electronics Engineering
Buletin Ilmiah Sarjana Teknik Elektro (BISTE) adalah jurnal terbuka dan merupakan jurnal nasional yang dikelola oleh Program Studi Teknik Elektro, Fakultas Teknologi Industri, Universitas Ahmad Dahlan. BISTE merupakan Jurnal yang diperuntukkan untuk mahasiswa sarjana Teknik Elektro. Ruang lingkup yang diterima adalah bidang teknik elektro dengan konsentrasi Otomasi Industri meliputi Internet of Things (IoT), PLC, Scada, DCS, Sistem Kendali, Robotika, Kecerdasan Buatan, Pengolahan Sinyal, Pengolahan Citra, Mikrokontroller, Sistem Embedded, Sistem Tenaga Listrik, dan Power Elektronik. Jurnal ini bertujuan untuk menerbitkan penelitian mahasiswa dan berkontribusi dalam pengembangan ilmu pengetahuan dan teknologi.
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Articles 364 Documents
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Big Data Acquisition in Wireless Sensor Networks Using an AI-Based Interval Type-2 Fuzzy Unequal Clustering and Selective Multi-Hop Routing Framework Ammar Dawood Jasim; Tareq Abed Mohammed; Mas Al-Qutbi
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16952

Abstract

Wireless Sensor Networks (WSNs) constitute a critical data-acquisition layer for large-scale sensing and big-data analytics; however, limited battery capacity, uneven energy dissipation, hotspot formation, and excessive clustering overhead can interrupt continuous data collection and reduce network lifetime. This paper proposes an Interval Type-2 Fuzzy Unequal Clustering with Selective Multi-Hop and Adaptive Re-clustering protocol (IT2F-UC-SMH-AR) for reliable and energy-efficient WSN data acquisition. The framework combines interval Type-2 fuzzy-based cluster-head selection, unequal cluster formation, load-aware node association, selective relay-based forwarding, and energy-dependent re-clustering. By preserving sensing-node availability, balancing forwarding loads, and sustaining data delivery to the base station, the proposed protocol strengthens the upstream data pipeline required for subsequent storage, processing, and big-data analytics. Its performance is evaluated through MATLAB simulations under three deployment scenarios and compared with Low-Energy Adaptive Clustering Hierarchy (LEACH), Cluster Head Election using Fuzzy logic (CHEF), and Gupta fuzzy logic-based scheme (Gupta-FL). The results demonstrate that IT2F-UC-SMH-AR delays early node failure, improves cluster-head stability and energy balance, and maintains competitive packet delivery under different network sizes and communication distances. Its advantages become particularly evident in scenarios with increased routing complexity, where unequal clustering and selective multi-hop transmission reduce long-range communication costs. Although LEACH achieves higher throughput in some compact or dense deployments, the proposed protocol provides a more favorable trade-off between network stability, energy preservation, and reliable data acquisition. These findings establish IT2F-UC-SMH-AR as a promising framework for energy-constrained WSN applications supporting continuous, large-scale data collection.
A Hybrid BSA-PSO Algorithm with Dynamic Parameters for Heterogeneous Data Classification Basem Abdullah Mohammed Al Titjri; Mohammed Albaker Najm Abed; Salman Rasheed Owid; Mohammed Jasim Alkhafaji; Olha Lobova
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.14941

Abstract

The explosive growth and immense diversity of modern data,that often described as heterogeneous,which present a significant challenge for traditional sorting and classification methods. Handling mixe the data types like text, images, and numerical values efficiently has become a major hurdle. This research is confronts this problem by proposing the development and improvement of the Birds Algorithm (BSA),a nature-inspired optimization technique. The primary goal was to significantly enhanced both the classification accuracy and the performance speed when dealing with such complex datasets. To achieve that, it modified the algorithm collective search mechanism by introducing new dynamic parameters, that moving beyond static values. That included dynamically adjusting the inertia itight and the cognitive and social learning factors,which allowing the algorithm to intelligently adapt its search strategy over time. That hybrid approach was then rigorously tested using the heterogeneous dataset and its performance was benchmarked against to other standard artificial intelligence algorithms that including Particle Swarm Optimization (PSO) and Genatic Algorithm (GA). The results from that comparative study itre definitive,that demonstrating the clear superiority of our developed algorithm in the both accuracy and execution time. The proposed modified BSA-PSO achieved the best performance with an average execution time of 0.95 seconds and an average final fitness of 0.05, significantly outperforming the Standard PSO, which recorded an execution time of 2.45 seconds and a fitness of 4.20, as itll as the GA, which shoitd an execution time of 3.10 seconds and a fitness of 3.80. This work underscores the urgent necessity of developing such adaptive, intelligent systems and confirms that combining optimization algorithms is a highly promising path toward managing the data challenges of our modern digital world.
Crocodile Optimizer-Based DC Chopper Control for Voltage Dip and Swell Mitigation in PMSG-Based WT Basiony Shehata Atia; Fajer M. Alelaj; M. Metwally Mahmoud; Alfian Ma’arif; Abdel-Magid M Ali
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.15464

Abstract

The increasing penetration of wind energy systems requires advanced control strategies capable of maintaining stable operation during grid disturbances while complying with modern GC requirements. This paper proposes a COA-based control scheme for a DC chopper integrated into a PMSWG system to enhance its FRTC under severe voltage disturbances. The COA is employed to optimally tune the controller parameters, ensuring effective regulation of the DC-link voltage and improved transient performance. The proposed approach is evaluated under four critical grid conditions, including three voltage dip scenarios corresponding to 100%, 80%, and 40% retained voltage levels, as well as a 20% voltage swell condition. Simulation results demonstrate that the proposed controller maintains the DC-link voltage close to its reference value of 1150 V, preventing excessive overvoltage during fault events and reducing stress on power electronic converters. Moreover, the control strategy satisfies GC requirements by providing appropriate reactive power support during VDs while ensuring controlled active power transfer. The optimized controller effectively suppresses electromagnetic torque oscillations, limits transient current peaks in the GSC, and enables rapid recovery of generator speed following fault clearance. Comprehensive MATLAB/Simulink studies confirm that the proposed COA-based DC chopper control significantly improves system transient stability, enhances grid-support capability, and ensures reliable operation under both voltage dip and swell conditions. In addition, the improved DC-link voltage regulation contributes to increased converter lifetime and reduced operational downtime, demonstrating the practicality and effectiveness of the proposed solution for modern wind energy conversion systems.
Adaptive Smart Energy Management for Wind-Battery Systems Considering Grid Fault Scenarios Habib Chaib; Housseyn Chaib; Belkacem Belabbas; Fajer M. Alelaj; Alfian Ma’arif; Mohamed Metwally Mahmoud; Vojtech Blazek; Shady M. Sadek
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16033

Abstract

This work introduces a novel energy management system based on radial basis function neural network (RBFNN) adapted for both grid-connected and segmented modes. The system components are electrical distribution grid, wind generator, power electronic converters and batteries. The study uses intelligent control and prevents the spread of potential problems or disturbances. This system incorporates various controllers responsible of specific functions like MPP monitoring, of battery charging and discharging, and of an inverter for effectively managing the transition between energy sources based on load requirements and available sources operating at their MPP. The objectives are to facilitate coordinated operation among distributed energy resources, ensuring the provision of necessary active power and additional services as necessary. The simulation uses MATLAB/Simulink environment. Simulation results demonstrate the effectiveness and feasibility of the proposed strategy. Overall, the obtained results affirm the practicality and advantages of employing neural networks in energy management systems.
Kinematic Modeling of 6-DOF Articulated Robot Arm Denso VS 6577 Wiroj Khawlaor; Anuchart Srisiriwat
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16049

Abstract

This paper presents a virtual-to-real validation framework for the kinematic modeling of a 6-DOF articulated industrial manipulator, Denso VS-6577. The proposed framework integrates analytical forward and inverse kinematics with a virtual simulation environment and physical robot experiments to evaluate trajectory consistency between simulated and real-world robotic environments. Closed-form inverse kinematic solutions based on the Denavit–Hartenberg (DH) convention are derived to enable computationally efficient real-time joint computation and continuous and smooth joint trajectory generation. A graphical simulation environment developed using MATLAB and V-Realm is employed to visualize and analyze robot motion under multiple joint configurations, including elbow-up posture selection and continuity-aware joint configuration management to maintain continuous manipulator motion throughout trajectory execution. To validate the proposed framework, identical circular trajectories are executed in both simulation and physical robot environments using the built-in closed-loop servo control system of the industrial manipulator. Trajectory tracking performance is evaluated by comparing Cartesian position errors along the x, y, and z axes using root-mean-square error (RMSE) analysis. Experimental results show simulation RMSE values of 1.85 mm, 0.49 mm, and 0.054 mm along the x, y, and z axes, respectively, while the physical robot experiments produce RMSE values of 3.125 mm, 1.318 mm, and 0.089 mm. The computational cost of the analytical inverse kinematic solution is less than 5 ms, demonstrating suitability for real-time robotic implementation. The results demonstrate satisfactory agreement between simulation and physical robot trajectories during continuous circular motion, while larger deviations are observed during transitional point-to-point movements. These discrepancies are primarily attributed to actuator dynamics, servo response delay, joint compliance, and mechanical backlash that are not represented in the analytical kinematic model. The proposed framework provides a unified approach for analytical kinematic validation, trajectory evaluation, and virtual-to-real robotic verification. The proposed framework can support future development of digital twin systems, advanced motion planning, and industrial robotic trajectory optimization.
An Adaptive Droop Control Strategy for Frequency Restoration in an AC Islanded Microgrid Haider H. Ali; Basil H. Jasim
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16077

Abstract

Recently, industrial sectors have become more and more enthusiastic about microgrid solutions. Most of these microgrids are based on using green and renewable energy sources. Such microgrids can either be connected to the main utility grid for purposes like cost savings, or they can be standalone independent island microgrids. Typically, microgrid control systems employ a three-layer method: primary, secondary, and tertiary. One major issue for islanded microgrids is that they lack a reference point for voltage and frequency since they are not connected to the utility grid. The Camel Algorithm (CA) is an optimization method inspired by nature that imitates how camels adapt and travel in desert environments. This paper applies the CA to adjust the active power droop coefficient dynamically in real time. The case scenario is a microgrid powered by a three distributed generator (DG) AC Island capable of standing alone with an actively varying load from 5 kW to 10 kW through unequal feeder impedances. Simulation results indicate that the proposed controller can maintain the microgrid frequency in a narrow range of 49.95-50 Hz, with a settling time of about 0.22 s. Moreover, the proposed method improves the active power-sharing dynamics and significantly reduces frequency deviations compared to the conventional fixed-droop control schemes.
Intelligent Tutoring Systems for Adaptive and Personalized Learning in Vocational Education: A Systematic Literature Review Asyraf Rahmat Hidayatulloh Asyraf; Rina Harimurti; Yeni Anistyasari; Widi Aribowo
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16270

Abstract

Rapid advances in Artificial Intelligence (AI) have driven the growth of Intelligent Learning Systems (ITS) that support adaptive and personalized learning, however, the implementation of ITS in vocational education remains limited and has not been fully integrated into real-world, competency-based training environments. The research contribution of this study is threefold: a comprehensive synthesis of recent AI-based ITS research, a quantified account of the persistent research gap in vocational-education applications, and a conceptual framework for implementing ITS in vocational settings that integrates competency-based content, dual cognitive-psychomotor student modelling, and simulation-based pedagogy. This study applies a Systematic Literature Review guided by the PRISMA protocol. From 300 articles identified across major scientific databases, a staged process of screening, eligibility assessment, and quality assessment yielded 30 articles published between 2019 and 2025 for final analysis. The findings show a sharp increase in ITS publications, with 46.7% published in 2025 alone, driven largely by the adoption of generative AI and large language models. By research type, 50% were systematic reviews, 23.3% empirical studies, 13.3% technology-development studies, and 13.3% conceptual studies. Most studies (63.3%) were conducted in general education contexts, while only 6.7% specifically addressed vocational or workforce-based education, confirming a clear and persistent research gap. ITS was found to effectively support adaptive learning through dynamic content adjustment, personalized learning pathways, real-time feedback, and data-driven performance prediction enabled by the integration of Learning Analytics and Educational Data Mining. AI-based ITS holds substantial potential to enhance learning effectiveness, but further empirical research is needed to validates its implementation in vocational education, particularly through the conceptual framework proposed in this study.
Fostering Critical Thinking, Creativity, Communication, and Collaboration through Project-Based Learning in Vocational Education: A Systematic Literature Review Nova Kristiana; Ekohariadi Ekohariadi; Ratna Suhartini; Indro Moerdisuroso; Bing Bedjo Tanudjaja; Ahmad Sofiyuddin Bin Mohd Shuib
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16415

Abstract

This study examines how Project-Based Learning (PjBL) has been implemented to support the development of 4C competencies, critical thinking, creative thinking, communication, and collaboration, within vocational education contexts. Beyond identifying reported learning outcomes, this review contributes by synthesizing the instructional elements, implementation patterns, and supporting frameworks that characterize successful PjBL practices across recent studies. This study employed a PRISMA-based Systematic Literature Review of 19 Scopus-indexed articles published between 2021 and 2025. The review process consisted of article identification, screening, eligibility assessment, data extraction, and thematic synthesis based on predefined inclusion and exclusion criteria. The findings indicate that PjBL is consistently associated with the development of 4C competencies through the use of authentic projects, workplace-related learning tasks, and student-centered activities. Across the reviewed studies, several recurring elements were identified as important for effective implementation, including authentic problem-solving, collaboration and teamwork, student voice and choice, inquiry processes, reflection and feedback, public presentation of project outcomes, and technology-supported learning environments. The review also found that quantitative research designs were most frequently used to investigate 4C skill development. Furthermore, the framework proposed by Jang, Yusri, and Mustapha emerged as a useful reference for organizing PjBL implementation through structured project planning, execution, and evaluation stages. In conclusion, the reviewed literature suggests that PjBL represents a promising pedagogical approach for supporting 4C competency development in vocational education. The study provides a synthesized set of implementation elements and framework considerations that may inform future research and instructional design in vocational learning environments.
A Robust Model Predictive Direct Speed Control Framework for PMSM Drives with Superior Speed and Torque Error Compensation Islam Khalid; Othman J. Alhayali; Sameh Aljanabi
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16737

Abstract

High-performance industrial drive systems utilize Permanent MagnetSynchronous Motors (PMSMs) due to their high power density, quickdynamic reaction, and outstanding efficiency. However, the dynamic andsteady-state performance of the drive system is impacted by conventionalModel Predictive Direct Speed control (MPDSC) schemes, which are verysusceptible to parameter mismatch, load disturbance, and model uncertainty.This work proposes a new MPDSC technique with an adaptive Sliding-ModeObserver (SMO) for the position and speed management of a PMSM in orderto address the aforementioned issues. After deriving a mathematical model ofthe PMSM in the synchronous (d)-(q) coordinate frame, an MPDSC approachcentered on the finite control set predictive control principle is put forward.The suggested observer minimizes chattering while ensuring resilience andaccurate disturbance assessment by adjusting the sliding mode coefficientsusing an adaptive approach. In MATLAB/Simulink, the efficacy of thesuggested approach is confirmed under various operating situations, includingfluctuating load torque and speed. The simulation findings display that theenhanced MPDSC method outperforms the conventional MPDSC strategy interms of dynamic response, including reduced overshooting, quicker settlingreaction, reduced speed error, and superior current quality performance. Forinstance, at the operating conditions utilized in the testing, the settling timewas reduced from around 40ms to 38ms, and the total harmonic distortion(THD) of the stator current was diminished from 13.95% to 2.41%.Furthermore, the suggested observer-based compensation technique mayenhance the robustness of the PMSM and efficiently suppress factordisturbances. The obtained findings confirm that the suggested adaptiveobserver-assisted MPDSC method is a practical and computationallyeconomical way to improve PMSM's dynamic performance and disturbancerejection capabilities.
Active Disturbance Rejection and Model Predictive Control for Mitigating Non-Torque-Producing Currents and Harmonic Distortion in Six-Phase Permanent Magnet Synchronous Motor Rjwan Ahmed Al-Hamdany; Jameel Kadhim Abed; Mustafa Naozad Taifor; Sarah A. Mohammed; Ali Falih Challoob; Naseer T. Alwan; Salam J. Yaqoob
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 4 (2026): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i4.16847

Abstract

The six-phase permanent magnet synchronous motor drives have high power density, fault tolerance, and reliability; however, conventional model predictive control is sensitive to load disturbances, unmodeled dynamics, and parameter uncertainties, which can lead to high non-torque-producing currents and harmonic distortion. To overcome these drawbacks, this work introduces an active disturbance rejection control approach with model predictive control (MPC). The research contribution is the combination of active disturbance estimation and compensation in the outer speed loop with the predictive current regulation in the inner current loop to improve disturbance rejection, reduce non-torque-producing currents, and improve the dynamic performance of the six-phase motor drives. The proposed scheme is modeled and validated through the MATLAB/Simulink simulation and compared to the standard MPC at the speed reference of 1000 rpm, load-torque steps of 10N·m applied in 0.05 s and 15N·m applied in 0.1 s, and motor inertia of 0.0048 kg·m². The simulation results show the current THD is reduced to 2.3% with the proposed strategy, and the average switching frequency is diminished to 10.8 kHz. The peak transient torque error is reduced from 0.65 N · m to 0.10 N · m, and steady-state torque ripple is lessened from 0.15 N·m to 0.02 N·m. Furthermore, the maximum speed deviation is lowered from about 150 rpm to 35 rpm, and the recovery time after a load disturbance is lowered from 40ms to 10ms. The obtained outcomes demonstrate the dominance of harmonic suppression, disturbance rejection, and dynamic efficacy of the proposed approach, indicating its prospective use in high-performance multiphase electric-drive systems.

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