International Journal of Electrical, Computer, and Biomedical Engineering (IJECBE)
The International Journal of Electrical, Computer, and Biomedical Engineering (IJECBE) is an international journal that is the bridge for publishing research results in electrical, computer, and biomedical engineering. The journal is published bi-annually by the Electrical Engineering Department, Faculty of Engineering, Universitas Indonesia. All papers will be blind-reviewed. Accepted papers will be available online (free access) The journal publishes original papers which cover but is not limited to Electronics and Nanoelectronicsc Nanoelectronics and nanophotonic devices; Nano and microelectromechanical systems (NEMS/MEMS); Nanomaterials; Quantum information and computation; Electronics circuits, systems on chips, RF electronics, and RFID; Imaging and sensing technologies; Innovative teaching and learning mechanism in nanotechnology education; Nanotechnologies for medical applications. Electrical Engineering Antennas, microwave, terahertz wave, photonics systems, and free-space optical communications; Broadband communications: RF wireless and fiber optics; Telecommunication Engineering; Power and energy, power electronics, renewable energy source, and system; Intelligent Robotics, autonomous vehicles systems, and advanced control systems; Computational Engineering. Computer Engineering Architecture, Compiler Optimization, and Embedded Systems; Networks, Distributed Systems, and Security; High-performance Computing; Human-Computer Interaction (HCI); Robotics and Artificial Intelligence; Software Engineering and Programming Language; Signal and Image Processing. Biomedical Engineering Cell and Tissue Engineering; Biomaterial; Biomedical Instrumentation; Medical Imaging.
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<![CDATA[Pitch Control of Variable Speed Wind Turbine with Permanent Magnet Synchronous Generator (PMSG) Using Single-Neuron PI Controller ]]>
<![CDATA[Rohadatul ‘Aisya]]>;
<![CDATA[Faiz Husnayain]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.165
<![CDATA[Variable-speed wind turbines with Permanent Magnet Synchronous Generator (PMSG) offer high efficiency in converting wind energy into electrical power. However, under wind conditions exceeding the rated speed, a pitch angle control mechanism is required to maintain output power stability and protect the system from overloading. Pitch angle control is commonly implemented using conventional PI controllers. This study aims to implement a single-neuron PI controller as an adaptive solution for regulating the pitch angle in a PMSG-based wind turbine system. The proposed control method combines the basic structure of a PI controller with adaptive learning based on a single neuron, enabling real-time adjustment of the controller weights based on output power error. The simulation and modeling of the wind energy conversion system are carried out using MATLAB/Simulink, including the modeling of the wind turbine, PMSG, conventional PI-based pitch control, and single-neuron PI-based pitch control. Simulation results demonstrate that the single-neuron PI controller effectively maintains the output power close to the reference value, with minimal deviation and high stability across various wind speeds exceeding the rated condition. Compared to the conventional PI controller, this method offers superior adaptability to system parameter variations and dynamic wind speed changes.]]>
<![CDATA[The Efficiency of Voltage Stabilizer Installation in Addressing Power Quality Issues through Analysis Using an Injection Power Analyzer in the Manufacturing Industry of PT XYZ ]]>
<![CDATA[Varin Pasaribu]]>;
<![CDATA[Faiz Husnayain]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.173
<![CDATA[In today's modern era, electrical energy has become a vital secondary need for society and serves as a key foundation for economic development. Along with the rapid advancement of complex electronic devices, various power quality disturbances have emerged, negatively impacting industrial equipment such as active line modules and motor drivers, potentially disrupting production processes. A similar issue occurred at PT XYZ, prompting real-time power quality monitoring using a power analyzer installed on the LVMDB panel. This device can record and analyze power quality trends visually. Based on the data, PT XYZ took corrective actions, including adjusting the tap changer position from 3 to 1 and installing a voltage stabilizer, which effectively stabilized the voltage supplied to production machines. Furthermore, a harmonic analysis simulation showed a Total Harmonic Distortion of 8,35% for current and 7,92% for voltage. After applying a power filter design in ETAP, these values significantly decreased to 1.98% (current) and 2.08% (voltage). Based on these findings, it is recommended that PT XYZ proceed with the installation of a power filter to comprehensively improve power quality.]]>
<![CDATA[Development of Prompting Techniques to Trigger Proactive Dialogues in Large Language Models ]]>
<![CDATA[Muhammad Firdaus Syawaludin Lubis]]>;
<![CDATA[Cecilia Inez Reva Manurung Manurung]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.187
<![CDATA[The rise of Artificial Intelligence (AI) challenges the integrity of traditional educational assessments, positioning the oral examination as a robust method for verifying authentic understanding. However, its large-scale implementation is hindered by significant logistical challenges, including time, resources, and evaluation consistency. This research addresses a foundational limitation for using Large Language Models (LLMs) in automated oral exams: their inherent passivity and failure to handle ambiguity, which are critical for effective assessment. To address this critical gap, we established an experimental framework and created two specialized datasets to systematically evaluate prompting techniques designed to elicit proactivity. Using the GPT-4o model, our comparative analysis reveals that the optimal strategy is highly task-dependent: for ambiguity detection (CNP), a Proactive Chain-of-Thought (PCoT) zero-shot approach achieved a near-perfect 0.99 F1-Score; for generating clarification questions (CQG), the PCoT few-shot variant was most effective; and in target-guided scenarios, a simpler proactive prompt proved superior. These findings provide foundational insights for developing automated oral examiners capable of nuanced, human-like dialogue, thereby addressing the scalability issues of traditional assessment methods.]]>
<![CDATA[Evaluation Of the Legality and Requirements of Starlink in Indonesia Using a Regulatory Impact Analysis Approach ]]>
<![CDATA[Ficco Clivano Ikhsan]]>;
<![CDATA[Gunawan Wibisono]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.210
<![CDATA[Indonesia has a territory and large population. Indonesia is one of the largest countries in the world, with an internet penetration rate of around 79% of the total population as of 2024. This has prompted Indonesia to improve its network and other telecommunications-related issues. This study evaluates the feasibility of utilizing Starlink satellites to equalize telecommunications access in Indonesia. Based on Law No. 36 of 1999 concerning Telecommunications, which mandates the provision of services to all regions, this study aims to evaluate the role of Starlink while identifying legal and regulatory obstacles related to this new technology. It also analyzes the legality of this technology and explains the sovereignty issues raised by Starlink. By applying the Regulatory Impact Analysis method, which uses the main stages of problem definition, policy identification, impact and policy evaluation, stakeholder consultation, and selection of alternative policies through interviews and framework. It began with the first option, which was a policy where the government permanently revokes Starlink's operational licenses to prioritize national sovereignty and data security. Option 2 approaches the issue with a temporary suspension and a comprehensive technical audit of the Network Operation Center (NOC) and Lawful Interception capabilities, and option 3 focuses more on giving Starlink more time to fully comply with regulations. Option 2 is the best choice because of its highest PMI score and its ability to balance the interests of regulators, operators, and the public. However, it temporarily disrupts service access for potential users, particularly in remote regions.]]>
<![CDATA[Design and Experimental Validation of an SDR-Based Private LTE Network for Flood Monitoring ]]>
<![CDATA[Bambang Candra Wibawa]]>;
<![CDATA[Gunawan Wibisono]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.213
<![CDATA[The widespread impact of hydrometeorological disasters, such as floods, necessitated a reliable and rapidly deployable communication infrastructure to support real-time monitoring and early warning systems. During such events, conventional public cellular networks frequently collapsed, hindering critical information exchange. To address this vulnerability, the study presented the design and performance validation of a private LTE network based on software-defined radio SDR USRP B210 and open-source software, intended as a resilient backbone for an IoT-based flood monitoring system. The system was tested to assess its signal quality and user experience metrics across varying radial distances. Signal analysis confirmed severe channel degradation, with the SINR dropping from the “Excellent” category at 3 m to the “Fair” and “Poor” category at 9 m. This SINR decline directly caused the downlink throughput to fall drastically from 27 Mbps to a low of 2.8 Mbps and significantly inflated the maximum latency to 87 ms due to frequent HARQ retransmissions. Despite these constraints, the network supported low-bandwidth IoT RSRP logging for modem consistency verification and sustained high-demand services including real-time data communication and voice and video calls. Overall, the results validated the system’s ability to establish resilient and self-sustained connectivity to support disaster mitigation and response operations.]]>
<![CDATA[Experimental Characterization of a Tri-Axial FBG Accelerometer for Underwater Thruster-Induced Vibration Detection ]]>
<![CDATA[Muhammad Alif Rahman Sukapraja]]>;
<![CDATA[Retno Wigajatri Purnamaningsih]]>;
<![CDATA[Sasono Rahardjo]]>;
<![CDATA[Maristya Rahmadiansyah]]>;
<![CDATA[Tinova Pramudya]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.226
<![CDATA[This paper presents an experimental engineering validation of a tri-axial Fiber Bragg Grating (FBG) accelerometer for detecting thruster-induced vibrations in submerged environments. The sensor integrates three orthogonally arranged FBG elements within a compact, waterproof housing, enabling vibration measurements along three spatial directions. Experiments were conducted using a DC thruster as a repeatable vibration source under both free-air and underwater conditions. Comparative results show a marked increase in Bragg wavelength shift (ΔλB) when submerged, with peak-to-peak variations reaching approximately 0.0267 nm on non-primary axes and up to 0.1005 nm on the axis aligned with the excitation, compared to approximately 0.0044 nm in free air. Sensor sensitivity, repeatability, and hysteresis were evaluated through cyclic loading-unloading tests. The maximum hysteresis observed was 0.0053 nm, corresponding to approximately 5% of the full-scale wavelength shift, indicating stable and predominantly elastic behavior.]]>
<![CDATA[Energy Consumption Optimization for Flexible Job-Shop Scheduling in Manufacturing Industry Using Multi-Agent Reinforcement Learning ]]>
<![CDATA[Satwika Bintang Bahana]]>;
<![CDATA[Naufan Raharya]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.227
<![CDATA[Modern manufacturing industries are increasingly demanding production systems that are both flexible and efficient in handling dynamic operational conditions. Traditional scheduling approaches, such as the job-shop scheduling Problem (JSSP), are limited by the constraint that each operation must be executed on a predefined machine. To address this limitation, the flexible job-shop scheduling Problem (FJSSP) was introduced, allowing alternative machine options for each operation and thereby enhancing system flexibility. This study proposes a scheduling optimization approach based on Multi-Agent Reinforcement Learning (MARL), to support decision-making in complex production environments. Experimental results demonstrate that the proposed method reduces energy consumption by up to 40.62% compared to the First Come First Serve (FCFS) method and by 35.23% compared to the Fastest Available Agent (FAA) method. Moreover, the model shows superior performance in controlling theworst-case makespan and achieves significantly higher success rates in satisfying various production constraints compared to all tested rule-based methods.]]>
<![CDATA[Delivery-Aware Hybrid Throughput Forecasting for Targeted Capacity Planning and Proactive Congestion Avoidance in Microwave Transmission Networks ]]>
<![CDATA[Gede Deny Marthafani Gede]]>;
<![CDATA[Catur Apriono]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.239
<![CDATA[Microwave transmission networks operate under strict physical-layer capacity constraints, where excessive utilization may reduce service reliability and increase congestion risk. In practical operations, capacity expansion decisions are both time-sensitive and location-sensitive, requiring operators to determine not only when an upgrade should be executed, but also which links require intervention. However, many existing forecasting approaches remain focused on numerical prediction accuracy and do not explicitly support delivery-aware and targeted planning decisions. This study proposes a delivery-aware hybrid smoothing–residual forecasting framework for link-level microwave throughput prediction using hourly Network Management System (NMS) data from 110 links observed over a six-month period. The framework separates the throughput series into a smoothed structural component and a residual component, where primary forecasting is performed on the structural signal, and residual error is modeled using LightGBM. The final forecast is reconstructed by combining both components and evaluated across multiple horizons using WMAPE, MAE, and RMSE. Experimental results show that CatBoost with LightGBM residual correction provides the most consistent performance across all forecasting horizons. Beyond improving prediction accuracy, the proposed framework enables delivery-aware and targeted capacity planning by estimating threshold-crossing timing and identifying high-risk links. This supports proactive congestion avoidance, more efficient upgrade prioritization, and improved resource allocation in microwave transmission networks.]]>
<![CDATA[A Hybrid Endpoint-Network Correlation Framework for Ransomware-Oriented Analysis ]]>
<![CDATA[Clavincy Francis Yohanes Ngantung]]>;
<![CDATA[I Gde Dharma Nugraha]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.243
<![CDATA[Ransomware-oriented incidents often leave suspicious traces across both endpoint and network domains, yet these observations are still commonly examined in isolation. This makes incident interpretation difficult, since host-level and communication-level evidence may remain fragmented even when they originate from the same attack sequences. To address this problem, this paper presents a hybrid endpoint-network correlation framework built around three analytical stages: endpoint-side suspicious activity analysis, network-side suspicious activity analysis, and multi-log correlation. The framework combines rule-based indicators with machine-learning-based suspiciousness support to preserve relevant evidence and then links the resulting candidates through temporal proximity, entity consistency, and behavioral relevance. Experiments on public attack scenarios show that the framework retained 16 endpoint candidates and 3 network candidates in a successful Drupal exploitation case, 11 endpoint candidates and 3 network candidates in a Samba known-creds scenario, and preserved a network-only context in a reconnaissance-dominant case. These retained candidates then serve as the basis for identifying cross-log relations, allowing suspicious observations from different sources to be interpreted within the same incident context. These results suggest that the framework can construct incident-oriented context without forcing unsupported cross-source relations.]]>
<![CDATA[Implementation and Hardware-Level Validation of a 36 V BLDC Motor Drive Using Artix-7 FPGA ]]>
<![CDATA[Rafi Kamil Arief]]>;
<![CDATA[Fajar Rahino Triputra]]>;
<![CDATA[Arief Udhiarto]]>
<![CDATA[ International Journal of Electrical, Computer, and Biomedical Engineering Vol. 4 No. 1 (2026) ]]>
Publisher : <![CDATA[Universitas Indonesia ]]>
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DOI: 10.62146/ijecbe.v4i1.244
<![CDATA[This paper presents an Artix-7 FPGA-based implementation and validation of a 36 V BLDC motor drive for open-loop no-load operation. The proposed controller combines Hall-sensor sixstep commutation, counter-based PWM generation, bidirectional phase sequencing, and deadtime-protected gate output logic in programmable hardware. The study emphasizes hardwarelevel validation, including the consistency of Hall-sector decoding, PWM scaling, and inverter output behavior, rather than closed-loop speed regulation. The design was verified using Verilog simulation and experimentally tested with a three-phase inverter, a 20 kHz PWM carrier, and a 10 - bit duty cycle. The measurements confirmed the expected PWM-driven phase, low-side return path, and floating phase behavior for adjacent Hall states. No-load characterization was then performed in both clockwise and counterclockwise directions. The measured speed increased almost linearly with duty cycle and reached approximately 2425 r/min at full duty cycle, while the supply current increased to about 0.49 A. The minimum start duty was 2% in both directions, and the minimum sustain duty was 1.8% and 1.7% for clockwise and counterclockwise rotation, respectively.]]>
