cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Alfian Maarif
Contact Email
alfianmaarif@ee.uad.ac.id
Phone
-
Journal Mail Official
biste@ee.uad.ac.id
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
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.
Arjuna Subject : -
Articles 295 Documents
 21   22   23   24   25 
Overload Monitoring and Warning System for 3-Phase Electric Motorcycle based on IoT Adhimanata, Yogi; Sulistiyowati, Indah; Wisaksono, Arief; Ayuni, Shazana Dhiya; Nasar, Muhammad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 1 (2025): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i1.12262

Abstract

This research aims to develop and test a Telegram-based monitoring and overload warning system for three-phase motors, utilizing the PZEM-004T sensor and ESP8266 WiFi microcontroller, which is able to measure electrical parameters such as current, voltage, and power in real-time. The method used is a quantitative approach with an experimental method, where this system provides automatic notifications via the Telegram application in the event of an overload with a current limit of 20A, and is able to automatically cut off electricity to prevent more serious damage. Given the risk of overload that can cause production damage and costly downtime to the industry, the results show the effectiveness of the system in recording data and detecting overload conditions, although there are power measurement discrepancies that indicate the need for further calibration. Recommendations from this research include developments to improve measurement accuracy, standardization of procedures, and integration with relevant industry standards, as well as additional trials with different load variations to validate the system's performance in various scenarios.
Dielectric Characterization of Breast Cancer Cells using Split-Rectangular Ring Resonator Sensor Jabire, Adamu Halilu; Saminu, Sani; Adamu, Muhammed Jajere; Mohammed, Abubakar Saddiq; Aminu, Sha'awanatu; Sadiq, Abubakar Muhammad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 1 (2025): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i1.12680

Abstract

Exploring a universal method to enhance the performance of metamaterials by quantifying the impact of gap capacitance is an intriguing topic for many researchers. However, achieving this through conventional methods is extremely challenging. In this paper, we present a microwave sensor designed to characterize cancerous cells based on their electrical properties. The proposed design features a split rectangular ring resonator placed on a flame-retardant four (FR-4) substrate. The sensor aims to achieve high sensitivity and quality factors through the unique characteristics of the metamaterial structure in the GHz frequency range. Through simulations and experimental measurements, we demonstrate the sensor's effective capabilities in detecting cancer. The high sensitivity for both simulation and measurement, is estimated at 10 %. The simulations and validation confirm that this biosensor exhibits significant frequency shifts and high sensitivity. Our proposed configurations highlight the microwave sensor's potential for detecting six different breast cancer cell types: HSS-2, HS578-T_nm, MCF-2, MCF-10A_nm, T-47D, and T-47D_nm. Based on the existing literatures, the sensitivity of the proposed sensor is determined to be greater.
Discount Factor Parametrization for Deep Reinforcement Learning for Inverted Pendulum Swing-up Control Surriani, Atikah; Maghfiroh, Hari; Wahyunggoro, Oyas; Cahyadi, Adha Imam; Fajrin, Hanifah Rahmi
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 1 (2025): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i1.10268

Abstract

This study explores the application of deep reinforcement learning (DRL) to solve the control problem of a single swing-up inverted pendulum. The primary focus is on investigating the impact of discount factor parameterization within the DRL framework. Specifically, the Deep Deterministic Policy Gradient (DDPG) algorithm is employed due to its effectiveness in handling continuous action spaces. A range of discount factor values is tested to evaluate their influence on training performance and stability. The results indicate that a discount factor of 0.99 yields the best overall performance, enabling the DDPG agent to successfully learn a stable swing-up strategy and maximize cumulative rewards. These findings highlight the critical role of the discount factor in DRL-based control systems and offer insights for optimizing learning performance in similar nonlinear control problems.
DNA-based Cryptography for Internet of Things Security: Concepts, Methods, Applications, and Emerging Trends Ţălu, Mircea
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.12942

Abstract

DNA-based cryptography is an emerging field that combines molecular biology and computational security to develop novel encryption, secure data storage, and steganographic techniques. It offers a promising alternative to traditional cryptographic systems, addressing challenges like storage efficiency, robustness, and resistance to computational attacks. In the era of the Internet of Things (IoT), where massive networks of interconnected devices continuously generate and exchange sensitive data, ensuring secure communication and storage has become a critical challenge. DNA-based cryptography presents a unique opportunity to enhance IoT security by offering ultra-secure encryption methods that exploit DNA’s vast information density and inherent randomness. These encryption methods leverage the complexity of DNA encoding - such as nucleotide substitution, DNA strand pairing, and biological operations like splicing and amplification - to create security layers that are difficult to decipher using conventional computational techniques. Recent advancements in DNA synthesis, sequencing, and encoding methodologies have facilitated the development of encryption schemes tailored for IoT applications, enabling lightweight, high-capacity security solutions that outperform traditional cryptographic methods. Beyond IoT, DNA-based cryptography also holds potential in areas such as secure biomedical data storage, digital rights management, and archival of sensitive governmental or historical information, demonstrating its broader applicability across diverse domains. Future research should optimize DNA encoding, improve storage technologies, and harness artificial intelligence for real-time threat detection, automated encryption, and adaptive security in IoT systems. This review analyzes DNA-based cryptographic methods, including natural and pseudo-DNA encryption, DNA-based steganography, and hybrid models, while uniquely exploring their IoT applications, emerging trends, practical implementations, key advantages, challenges, and future research directions.
Improved Black Widow for Optimal Distributed Generation Placement in Radial Distribution Networks Egeruo, Sochima; Olatunde, Oladepo
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.12954

Abstract

Mitigating active and reactive power losses and improving voltage profiles in radial distribution networks remain critical challenges for system operators. While the introduction of Distributed Generation offers a promising solution, determining their optimal placement and sizing is a complex problem. Metaheuristic algorithms, though effective, have seen limited application in addressing issues specific to radial feeders, where traditional analytical methods dominate. This paper presents an Improved Black Widow Optimization Algorithm to improve Distributed Generation location and proper sizing in radial distribution networks. The Improved Black Widow Optimization Algorithm incorporates a non-linear inertia weight adjustment to enhance the balance between diverse exploration and focused exploitation, addressing a key limitation of the standard Black Widow Optimization. A backward-forward sweep algorithm is used to calculate the initial losses and voltage profile of the test systems, while the Improved Black Widow Optimization Algorithm determines optimal Distributed Generation parameters. The proposed method is tested on the IEEE 33-bus system and validated on a Nigerian 32-bus 11kV distribution feeder using MATLAB. Results demonstrate that the Improved Black Widow Optimization Algorithm reduces power losses by 49.49% and improves voltage profiles by 85.64% on the IEEE system, outperforming the standard Black Widow Optimization Algorithm (44.81% loss reduction, 84.64% voltage improvement). On the Nigerian network, the Improved Black Widow Optimization Algorithm achieves a 52.86% loss reduction and 92.22% voltage improvement, compared to 25.98% and 79.04% with the Black Widow Optimization Algorithm. These improvements translate to enhanced energy efficiency, reduced technical losses, and better voltage stability, confirming the superior performance of the Improved Black Widow Optimization Algorithm in addressing radial distribution network challenges.
Maintaining Empathy and Relational Integrity in Digitally Mediated Social Work: Practitioner Strategies for Artificial Intelligence Integration Chen, Yih-Chang; Lin, Chia-Ching
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13008

Abstract

This study addresses the critical challenge of preserving relational integrity in social work practice within artificial intelligence (AI)-enhanced environments. While AI technologies promise operational efficiency, their impact on empathy and human connection in social work is not fully understood. This research aims to explore how social workers maintain relational integrity when interacting with clients through AI tools, providing practical strategies and theoretical insights. The research contributes to the field by proposing a relational framework for AI integration in social work practice, emphasizing human-centered principles. The study utilizes a qualitative phenomenological approach, drawing on 24 licensed social workers from diverse sectors (e.g., child welfare, elder care, and mental health) in three urban areas known for AI adoption. Data collection involved semi-structured interviews and artifact analysis, including AI interface screenshots and decision-making protocols, to capture practitioner experiences. Findings reveal three key themes: reframing empathy in digital interactions, AI as a dual partner and adversary, and ethical tensions. Results indicate that video calls and visual aids are crucial for preserving empathy, while social workers employ proactive strategies to manage AI’s limitations. The study highlights the need for clear guidelines, interdisciplinary collaboration, and training to ensure AI supports relational practices rather than replacing them. These findings have significant policy and practice implications, offering a foundation for future research and AI tool development in social services.
Optimal Controller Design of Crowbar System for DFIG-based WT: Applications of Gravitational Search Algorithm Ahmed, Amany Fayz Ali; Elzein, I. M.; Mahmoud, Mohamed Metwally; Ardjoun, Sid Ahmed El Mehdi; Ewias, Ahmed M.; Khaled, Usama
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13027

Abstract

The optimal output and efficacy of a doubly fed induction wind generator (DFIG) are dependent on a multitude of uncontrollable components, necessitating the use of an adequate control system. The crowbar system is essential to the system during abnormal events; thus, it requires appropriate control algorithms and enough control settings. This work suggests the gravitational search algorithm (GSA) to construct the crowbar controller. A synopsis of wind energy and a conversation about the pertinent DFIG component and its methodology. The outcomes acquired with the suggested optimized crowbar system are contrasted with those obtained with a traditional crowbar and without protection. The outcomes confirmed the higher performance of the suggested strategy. The DFIG system responds marginally improved to active and reactive (P&Q) power, DC-Link voltage (DCLV), and machine rotation when a GSA-based PI controller is used. Finally, it can be said that by maintaining the DCLV below the allowable value, which permits the high penetration possibilities of wind energy, the suggested technique assures fault ride-through capacity (FRTC).
Comparative Analysis of PID Tuning Methods for Speed Control in Mecanum-Wheel Electric Wheelchairs Thongpance, Nuntachai; Chotikunnan, Phichitphon; Wongkamhang, Anantasak; Chotikunnan, Rawiphon; Imura, Pariwat; Khotakham, Wanida; Nirapai, Anuchit; Roongprasert, Kittipan
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13046

Abstract

This study compares two PID controller tuning methods, particle swarm optimization (PSO) and Cohen-Coon, employed for speed control of an omnidirectional Mecanum-wheel electric wheelchair. Mecanum wheels improve maneuverability on powered mobility platforms; yet, controlling these systems is difficult due to nonlinearities and directional coupling effects. This work investigates the effectiveness of PSO as a sophisticated alternative to traditional PID tuning methods, effectively tackling this issue. This study evaluates P, PI, PD, and PID controllers tuned by both Cohen-Coon and PSO methods, applied to a DC motor system simulating real-world wheelchair actuation. Step response-based system identification models the motor using MATLAB/Simulink. Simulations of a 12V DC motor are examined using controlled-step time-domain inputs. Every controller configuration is subjected to evaluation for overshoot, root mean square error (RMSE), rise time, and settling time. The PSO-tuned PID controller exhibited enhanced performance, characterized by a rise time of 2.06 s, a settling time of 2.37 s, an overshoot of 0.78%, and an RMSE of 4.59, far surpassing the Cohen-Coon variant, which had a settling time of 6.12 s and an overshoot of 20.14%. The results indicate that PSO enhances both transient and steady-state performance in intricate and disturbance-sensitive systems, including Mecanum wheelchairs. Despite PSO's increased computing complexity during offline tuning and the necessity for meticulous parameter selection, its advantages can be precomputed and effectively utilized in real-time embedded systems. This study highlights the importance of safety, dependability, and responsiveness, illustrating that PSO is a scalable and efficient method for improving assistive robotic systems.
Transformer Models in Deep Learning: Foundations, Advances, Challenges and Future Directions Mangkunegara, Iis Setiawan; Purwono, Purwono; Ma’arif, Alfian; Basil, Noorulden; Marhoon, Hamzah M.; Sharkawy, Abdel-Nasser
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13053

Abstract

Transformer models have significantly advanced deep learning by introducing parallel processing and enabling the modeling of long-range dependencies. Despite their performance gains, their high computational and memory demands hinder deployment in resource-constrained environments such as edge devices or real-time systems. This review aims to analyze and compare Transformer architectures by categorizing them into encoder-only, decoder-only, and encoder-decoder variants and examining their applications in natural language processing (NLP), computer vision (CV), and multimodal tasks. Representative models BERT, GPT, T5, ViT, and MobileViT are selected based on architectural diversity and relevance across domains. Core components including self-attention mechanisms, positional encoding schemes, and feed-forward networks are dissected using a systematic review methodology, supported by a visual framework to improve clarity and reproducibility. Performance comparisons are discussed using standard evaluation metrics such as accuracy, F1-score, and Intersection over Union (IoU), with particular attention to trade-offs between computational cost and model effectiveness. Lightweight models like DistilBERT and MobileViT are analyzed for their deployment feasibility. Major challenges including quadratic attention complexity, hardware constraints, and limited generalization are explored alongside solutions such as sparse attention mechanisms, model distillation, and hardware accelerators. Additionally, ethical aspects including fairness, interpretability, and sustainability are critically reviewed in relation to Transformer adoption across sensitive domains. This study offers a domain-spanning overview and proposes practical directions for future research aimed at building scalable, efficient, and ethically aligned. Transformer-based systems suited for mobile, embedded, and healthcare applications.
An Analysis of UAV Security and Privacy Concerns of Communication Systems Hassan, Farah Alaa A.; Almamoori, Hiba Rashid; Al-Msarhed, Nuha Kareem Hameed
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13057

Abstract

Wireless communication is one of the fastest-growing research fields, with Unmanned Aerial Vehicles (UAVs) increasingly deployed as mobile router points in high-traffic areas such as bus stations, metro stations, and airport terminals to address connectivity challenges. However, despite their utility, UAVs face significant security and privacy risks. This paper presents a comprehensive analysis of these vulnerabilities through a systematic four-level classification: sensor, communication, software, and hardware. For each level, we examine (1) common weaknesses exploitable by malicious actors, (2) potential threats to civilian UAV applications, (3) active and passive attacks compromising security and privacy, and (4) possible countermeasures to mitigate such risks. Additionally, we summarize key findings on UAV security and privacy issues and highlight critical unresolved challenges. Finally, we propose future research directions, including the use of fuzzy logic to optimize drone routing by dynamically relocating UAVs to low-activity zones based on fuzzy rule-based decisions.

Page 23 of 30 | Total Record : 295

 21   22   23   24   25 

Filter by Year

2019 2026


Reset
Filter By Issues
All Issue Vol. 8 No. 1 (2026): February Vol. 7 No. 4 (2025): December Vol. 7 No. 3 (2025): September Vol. 7 No. 2 (2025): June Vol. 7 No. 1 (2025): March Vol. 6 No. 4 (2024): December Vol. 6 No. 3 (2024): September Vol. 6 No. 2 (2024): June Vol. 6 No. 1 (2024): March Vol. 5 No. 4 (2023): December Vol. 5 No. 3 (2023): September Vol. 5 No. 2 (2023): June Vol. 5 No. 1 (2023): March Vol. 4 No. 3 (2022): December Vol. 4 No. 2 (2022): Agustus Vol. 4 No. 1 (2022): April Vol. 3 No. 3 (2021): Desember Vol 3, No 2 (2021): Agustus Vol. 3 No. 2 (2021): Agustus Vol 3, No 1 (2021): April Vol. 3 No. 1 (2021): April Vol. 2 No. 3 (2020): Desember Vol 2, No 3 (2020): Desember Vol 2, No 2 (2020): Agustus Vol. 2 No. 2 (2020): Agustus Vol. 2 No. 1 (2020): April Vol 2, No 1 (2020): April Vol 1, No 3 (2019): Desember Vol. 1 No. 3 (2019): Desember Vol 1, No 2 (2019): Agustus Vol. 1 No. 2 (2019): Agustus Vol 1, No 1 (2019): April Vol. 1 No. 1 (2019): April More Issue