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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 73 Documents
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Search results for , issue "Vol 14, No 5: October 2025" : 73 Documents clear
The A3C-CCTSO-R2N2 algorithmic framework for precise edge-cloud parameter estimation Manonmani, Gangadharan; Ponmozhi, Krishnasamy; Balasubramanian, Krishnasamy
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.8982

Abstract

Efficient resource allocation is crucial in fog computing environments due to dynamic conditions and different user requirements; this work addresses the scheduling issues of internet of things (IoT) applications in such situations. Our proposed method, chaotic crossover tuna swarm optimizer (CCTSO), is based on metaheuristics and aims to reduce energy usage, reaction time, and SLA breaches; it should help with these problems. Improved system responsiveness and dependability are outcomes of the suggested approach's use of machine learning models for scheduling decision prediction and dynamic workload adaptation. The framework achieves a good balance between performance and energy efficiency by adjusting critical parameters and application settings. By reducing energy usage, reaction time, and operational cost while retaining reduced service level agreement (SLA) violation rates, our solution greatly outperforms previous techniques, according to experimental assessments. In real-world implementations, our results demonstrate that CCTSO is a strong solution for fog-based IoT scheduling, providing greater scalability and adaptability. Taken together, the results of this study provide a strong algorithmic foundation for better resource management in cloud, fog, and edge computing environments.
A review on radio-frequency transceiver architectures for low-power wireless sensor networks Narenahalli Ashok Kumar, Ambika; Mishra, Geetishree
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.10633

Abstract

Wireless sensor networks (WSNs) have garnered significant scientific attention because of their many uses, but their power usage is a fundamental barrier to their deployment. Energy constraints have a direct effect on important design elements including battery capacity, energy harvester effectiveness, and network longevity. To enable sustainable WSN operation, radio-frequency (RF)-based transceiver (TR) design has become a key area of study. A thorough examination of current RF-TR architectures is given in this paper, with a focus on low-power (LP) implementations designed for WSN applications. Amplifier-sequenced hybrid (ASH), superheterodyne (SHD), zero-intermediate frequency (Zero-IF), low-intermediate frequency (Low-IF), sliding-intermediate frequency (Sliding-IF), and super-regenerative (SRG) architectures are among the TR system designs that are categorized, with an emphasis on the performance trade-offs associated with each. Comparative evaluation shows that Zero-IF and SRG architectures are more energy efficient than other designs that were studied, which makes them viable options for ultra-low-power (ULP) WSN installations. Along with outlining important research issues in RF-TR design, such as hardware minimization, security, synchronization, and energy optimization, this review also suggests possible future paths to improve the sustainability and performance of WSN-based RF-TRs.
Performance analysis of 3D assets in virtual reality simulations for climate change: a case study in sustainable energy systems Miranto, Cahya; Firmanda, Ardiman; Rante, Hestiasari; Sukaridhoto, Sritrusta; Agus Zainuddin, Muhammad; Rahman, Haolia
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9532

Abstract

This study investigates the performance impact of 3D assets in a virtual reality (VR) simulation designed for climate change education, aiming to balance visual fidelity and system efficiency on standalone headsets. Using a case study modeled on a sustainable energy environment, key performance metrics frames per second (FPS), triangle count, and draw calls were measured to assess the effect of object density, material transparency, and batching strategies. Experimental results show that configurations with 20 trees and 20 characters maintained 101 FPS, while denser scenes with 30 trees and 30 characters dropped to 79 FPS approaching the minimum usability threshold for VR. Transparent tree foliage with alpha-cutout materials imposed higher graphics processing unit (GPU) loads than high-triangle opaque character models, highlighting the performance cost of material complexity. These findings offer practical guidelines for optimizing asset configurations in immersive educational VR content. Future work may explore integration of artificial intelligence (AI) behavior and user interaction to assess broader system performance.
Hybrid DL and ML approach for MRI-based classification of bone marrow changes in lumbar vertebrae Shakir, Yasir Hussein; Kiong, Tiong Sieh; Chen, Chai Phing; Kumar, Sachin Sharma Ashok
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.10617

Abstract

Alterations in the bone marrow changes lumbar vertebrae (BMCLVB) are considered important markers of chronic low back pain severity, particularly among patients with coexisting conditions like osteoporosis or cancer. Realizing these associations informs healthcare and insurance frameworks but also supports early intrusion planning for high-risk populations. This study aims to classification (BMCLVB) as normal or abnormal used magnetic resonance imaging (MRI) with machine learning (ML) model. A novel dataset comprising 1,018 BMCLVB MRI images was utilized to extract deep features via a pre-trained ConvNeXt-XLarge model. These features were then classified using different types in individual and ensemble ML algorithms. To ensure a comprehensive performance evaluation, all models were tested using accuracy, precision, recall, and F1-score. The combination of ConvNeXt-XLarge and logistic regression (LR) achieved a classification accuracy 93.14%, precision 93.22%, recall 94.83%, and F1-score 94.02%. These results highlight that the proposed model provides a fast and cost-efficient solution supporting the diagnosis of BMCLVB and potential to significantly improve clinical decision-making and patient care outcomes.
An innovative design of a frequency-tunable UHF RFID antenna for identification applications Errachidi, Zakaria; Zbitou, Jamal; Chahboun, Noha; Oulhaj, Otman; Lakhssassi, Ahmed
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9535

Abstract

This paper introduces the design of a new frequency-reconfigurable ultra-high frequency radio frequency identification (UHF RFID) antenna, demonstrating an innovative approach that enables dynamic adjustment of its resonance frequency. The proposed antenna design features a central dipole structure, enhanced by two hexagonal split-ring resonators (H-SRR) at each end. A T-match network is integrated into the center of the dipole, which is essential for achieving impedance matching between the antenna and the Alien Gen2 H4 RFID microchip. The antenna is designed using a Rogers 4350B substrate, a high-performance dielectric material ideal for RFID applications. With dimensions of 68×32.6×1.524 mm3, the compact antenna maintains full UHF band (860 MHz to 930 MHz) coverage compliant with International Telecommunications Union (ITU) RFID standards. This ensures that the antenna can be used in different regions around the world, offering broad compatibility with various RFID systems. The antenna's frequency reconfigurability is achieved through the integration of localized capacitors with variable values, which plays a key role in enabling precise adjustments to the antenna's center frequency across the entire UHF band. Extensive simulation results validate the effectiveness of this reconfigurable design, demonstrating that the antenna can dynamically adjust its frequency while maintaining excellent performance metrics, including impedance matching, radiation efficiency, and bandwidth. This makes the proposed antenna an ideal choice for modern RFID applications.
Improvement on the handover technique for 5G network using fuzzy logic algorithm Hakkou, Samia; Mazri, Tomader; Hmina, Nabil
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9795

Abstract

Beyond 5G (B5G) networks require advanced handover algorithms to guarantee seamless connectivity and optimum quality of service. Traditional handover methods are not sufficient to meet the stringent latency and reliability requirements of next-generation networks. To meet these challenges, the integration of fuzzy logic into handover algorithms offers a viable solution. The proposed approach utilizes parameters such as reference signal received power (RSRP), reference signal received quality (RSRQ), signal-to-interference plus noise ratio (SINR), and user equipment (UE) speed as inputs, while dynamically adjusting the time-to-trigger (TTT) and handover margin (HOM) as outputs. To assess the effectiveness of this algorithm, handover latency (HOL) and handover interruption time (HIT) are evaluated and compared with existing algorithms in the literature. The results show better and more efficient performance in both terms of latency and interruption time.
Optimized weighted non-local mean filter for enhanced denoising and improved quality of medical images Senthilvel, Aiswarya; Marimuthu, Krishnaveni; Parthasarathy, Subashini
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9549

Abstract

Image quality is significantly influenced by noise, light, and artifacts, particularly in medical images where precision is essential for accurate diagnosis. Denoising is a significant pre-processing for enhancing the overall quality of images to enable efficient classification, feature extraction, and segmentation. Conventional denoising filters smooth out boundaries and lose texture because they are ineffective to process color images. To address these limitations, a weighted factor-based non-local means (WF+NLM) filter is proposed as an improvement over the non-local means (NLM) filter, with an additional weight factor based on pixel similarity. This addition reduces blurring while maintaining fine details, resulting in improved quality. The proposed filter performs effectively in blood smear images, with a peak signal-to-noise ratio (PSNR) of 39.6904, SSIM of 0.9551, and gradient SSIM of 0.9889. Statistical tests indicates that the WF+NLM filter improves image quality in terms of structure, gradients, and feature similarity. Statistical inference for a one-tailed paired t-test validates statistical significance with the highest t value of 9.323829 with p-value 0.00037 by the wavelet-based non-local moment mean (W-NMM) filter asserts higher image restoration quality.
Agrivoltaic systems: a literature review Durán-Cabezas, Mariajosé; Gómez-Gaviria, Catalina; Henao-Céspedes, Vladimir
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9964

Abstract

Agrivoltaic systems integrate solar energy generation with agricultural production to achieve efficient land use and mitigate climate change. This study presents a bibliometric analysis of the scientific literature on this topic, published from 2013 to 2023, to identify key trends, research areas, and emerging topics. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology and data from the Scopus database, the analysis was conducted with the R package bibliometrix and VOSviewer software. The results show remarkable growth in scientific output since 2020, with the United States, China, and Germany as the leading countries. The findings reveal the benefits of agrivoltaic systems, such as increased crop productivity, water-use efficiency, and income diversification for farmers. Emerging topics include the optimization of panel configurations and socioeconomic implications. Despite these benefits, challenges like high initial costs, social acceptance, and the need for adaptable designs persist. The conclusions underscore the importance of specific policies and incentives to support the adoption of these technologies. This analysis provides a comprehensive overview of the state of agrivoltaic systems, offering valuable insights for researchers, policymakers, and other stakeholders.
Optimized electric vehicle charging: solar-driven wireless power transfer system D. Bondre, Vipin; V. Bondre, Shweta; Yadav, Uma; Dasarwar (Maidamwar), Priya; Sharma, Rashmi
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9831

Abstract

Wireless power transfer (WPT) is emerging as a transformative solution to overcome the limitations of conventional plug-in charging for electric vehicles (EVs). This study aims to design and implement an efficient and reliable wireless charging system using inductive coupling with low requirements on the primary circuit. The proposed system integrates an Arduino-controlled high-frequency converter along with sensors and relays to optimize power flow, ensure safety, and reduce energy wastage. The methodology involves experimental rearrangement of transformers and frequency elements to achieve maximum efficiency while maintaining compact circuit design. Results demonstrate that the system can achieve efficient energy transfer suitable for short charging intervals, particularly beneficial for shuttle buses at stations and rental taxis at parking hubs. The findings highlight that wireless charging not only reduces total charging time but also supports cost-effective battery sizing, enabling improved vehicle turnaround and operational efficiency. In conclusion, this work contributes a weather-resistant, safe, and economically viable charging approach that sets new standards for EV infrastructure. Its implications lie in redefining charging stations along predetermined routes and stops, ultimately advancing sustainable and user-friendly electric transportation.
Optimizing job scheduling on cloud resources using the first-come, first-served-SlotFree method Pujiyanta, Ardi; Noviyanto, Fiftin; Ismail, Taufiq
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9681

Abstract

Cloud computing environments encounter significant challenges in job scheduling, particularly due to excessive waiting times and inefficient resource utilization associated with conventional algorithms such as first-come, first-served (FCFS) and backfilling. This study introduces FCFS-SlotFree, a novel scheduling algorithm that enhances resource allocation efficiency by dynamically sorting jobs based on their arrival times and workloads, and subsequently assigning them to a fixed set of virtual machines (VMs) without relying on rigid time-slot constraints. This flexible scheduling approach facilitates better adaptation to heterogeneous workloads. Extensive experiments conducted under realistic cloud scenarios demonstrate that FCFS-SlotFree significantly reduces average waiting time (AWT) by approximately 32.78% compared to FCFS and by 9.68% compared to backfilling, while concurrently improving resource utilization by 3.58% and 1.27%, respectively. The results substantiate the algorithm’s effectiveness in optimizing scheduling performance and resource efficiency within complex cloud environments.

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