Jurnal Rekayasa elektrika
The journal publishes original papers in the field of electrical, computer and informatics engineering which covers, but not limited to, the following scope: Electronics: Electronic Materials, Microelectronic System, Design and Implementation of Application Specific Integrated Circuits (ASIC), VLSI Design, System-on-a-Chip (SoC) and Electronic Instrumentation Using CAD Tools, digital signal & data Processing, , Biomedical Transducers and instrumentation, Medical Imaging Equipment and Techniques, Biomedical Imaging and Image Processing, Biomechanics and Rehabilitation Engineering, Biomaterials and Drug Delivery Systems; Electrical: Electrical Engineering Materials, Electric Power Generation, Transmission and Distribution, Power Electronics, Power Quality, Power Economic, FACTS, Renewable Energy, Electric Traction, Electromagnetic Compatibility, High Voltage Insulation Technologies, High Voltage Apparatuses, Lightning Detection and Protection, Power System Analysis, SCADA, Electrical Measurements; Telecommunication: Modulation and Signal Processing for Telecommunication, Information Theory and Coding, Antenna and Wave Propagation, Wireless and Mobile Communications, Radio Communication, Communication Electronics and Microwave, Radar Imaging, Distributed Platform, Communication Network and Systems, Telematics Services and Security Network; Control: Optimal, Robust and Adaptive Controls, Non Linear and Stochastic Controls, Modeling and Identification, Robotics, Image Based Control, Hybrid and Switching Control, Process Optimization and Scheduling, Control and Intelligent Systems, Artificial Intelligent and Expert System, Fuzzy Logic and Neural Network, Complex Adaptive Systems; Computer and Informatics: Computer Architecture, Parallel and Distributed Computer, Pervasive Computing, Computer Network, Embedded System, Human—Computer Interaction, Virtual/Augmented Reality, Computer Security, Software Engineering (Software: Lifecycle, Management, Engineering Process, Engineering Tools and Methods), Programming (Programming Methodology and Paradigm), Data Engineering (Data and Knowledge level Modeling, Information Management (DB) practices, Knowledge Based Management System, Knowledge Discovery in Data), Network Traffic Modeling, Performance Modeling, Dependable Computing, High Performance Computing, Computer Security, Human-Machine Interface, Stochastic Systems, Information Theory, Intelligent Systems, IT Governance, Networking Technology, Optical Communication Technology, Next Generation Media, Robotic Instrumentation, Information Search Engine, Multimedia Security, Computer Vision, Information Retrieval, Intelligent System, Distributed Computing System, Mobile Processing, Next Network Generation, Computer Network Security, Natural Language Processing, Business Process, Cognitive Systems. Signal and System: Detection, estimation and prediction for signals and systems, Pattern recognition and classification, Artificial intelligence and data analytics, Machine learning, Deep learning, Audio and speech signal processing, Image, video, and multimedia signal processing, Sensor signal processing, Biomedical signal processing and systems, Bio-inspired systems, Coding and compression, Cryptography, and information hiding
Articles
600 Documents
<![CDATA[Wireless Photoplethysmography (PPG) Measurement with Pulse Wave Velocity (PWV) Method for Arterial Stiffness Evaluation ]]>
<![CDATA[Dewi, Ervin Masita]]>;
<![CDATA[Rahmawati, Dini]]>;
<![CDATA[Kirana, Nurista Wahyu]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 1 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i1.33486
<![CDATA[Indications of symptoms of cardiovascular disease can be seen from the level of elasticity of the arteries. The Pulse Wave Velocity (PWV) method using PPG signal analysis is used to determine the level of arterial stiffness based on the time difference between pulse waves of Photoplethysmography (PPG) signal measurements. PWV measurements use a non-invasive technique using pulse sensors on the fingers and toes, the measurement data is sent wirelessly using the ESP-NOW protocol. Analysis of the measured PPG signal is used as an approach to calculating the PWV value. Realization and testing can be used to measure the pulse in BPM and classify the index of arterial stiffness using the PWV method. The results of testing on 15 test volunteers from 3 age groups showed the results of an arterial stiffness index with indications of normal, stiff and very stiff arteries. The PWV value for the 20 year old group was 4.30-6.77 cm/s, normal arterial conditions. The age group of 30-40 years has a PWV value ranging from 5.11-8.77 cm/s, normal arterial conditions. The age group of 50-60 years had PWV values in the range of 10.69-18.43 cm/s, stiff and very stiff arterial conditions. Increasing age linearly affects the increase in PWV value. An increased PWV value may indicate an increase in arterial stiffness.]]>
<![CDATA[Robust Stochastic Model Predictive Control for Autonomous Vehicle Motion Planning ]]>
<![CDATA[Subiyanto, Subiyanto]]>;
<![CDATA[Hangga, Arimaz]]>;
<![CDATA[Bahatmaka, Aldias]]>;
<![CDATA[Salim, Nur Azis]]>;
<![CDATA[Sutrisno, Deyndrawan]]>;
<![CDATA[Yunus, Elfandy]]>;
<![CDATA[Budi Arif Prabowo, Setya]]>;
<![CDATA[Hilmi Farras, Muhammad]]>;
<![CDATA[Sanggrahita, Diadora]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 3 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i3.39281
<![CDATA[This work presents a Robust Stochastic Model Predictive Control (RSMPC) framework for real-time motion planning autonomous vehicles, addressing the complex multi-modal vehicle interactions. The proposed framework involves adding expert policy from observations to the dataset and applying the Data Aggregation (DAgger) method to filter unsafe demonstrations and resolve expert conflicts. A Dual-Stage Attention-based Recurrent Neural Network (DA-RNN) model is integrated to predict dual class variables from the dataset, producing a set containing constraints collision-avoidance predicted to be active. The RSMPC framework enhances formulation optimization by eliminating irrelevant collision avoidance constraints, resulting in faster control signals. The framework is applied iteratively, continuously updating observations and solving the RSMPC optimization formulation in real-time. Evaluation of the DA-RNN model achieved a recall value of 0.97 and a high accuracy rate of 98.1% in predicting dual interactions, with a minimal false negative rate of 0.026, highlighting its effectiveness in capturing interaction intricacies. Validated through simulations of interactive traffic intersections, the proposed framework demonstrably excels, showing high feasibility of 99.84% and a 15-fold increase in response speed compared to the baseline. This approach ensures autonomous vehicles navigate safely and efficiently in complex traffic scenarios, paving the way for more reliable and scalable autonomous driving solutions.]]>
<![CDATA[Scalability of MIMO Antennas: Assessing Gain and HPBW for Different Antenna Element Configurations ]]>
<![CDATA[Salsabila, Salwa]]>;
<![CDATA[Ryanu, Harfan Hian]]>;
<![CDATA[Nur, Levy Olivia]]>;
<![CDATA[Nugroho, Bambang Setia]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 2 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i2.33177
<![CDATA[The design of Massive MIMO Antennas presents challenges due to their large size, which can impede the design process. Additionally, the arrangement of multiple antenna elements in Massive MIMO Antennas poses a challenge, as it surpasses the capabilities of simulation software and involves complex procedures. Therefore, to address these issues, a scalability technique utilizing array factor theory is employed to determine the relationship between the configuration of MIMO antennas and the corresponding values of gain and half-power beamwidth (HPBW). By utilizing a simpler MIMO Antenna array with incremental configurations, such as 2x2, 4x4, 8x8, and 16x16 MIMO element schemes, the array factor theory allows for the prediction of the gain and HPBW values for a Massive MIMO Antenna array with a specific configuration. This research aims to explore the scalability process and derive equations that relate the gain and HPBW values to the different MIMO configurations. The designed MIMO antenna arrangement is based on rectangular antennas with truncated corners and circular antennas with X slots, allowing for the investigation of various configurations operating at a frequency of 3.5 GHz.]]>
<![CDATA[Declining Cogging Torque Technique of an Integral Slot Number for Permanent Magnet Machines ]]>
<![CDATA[Herlina Herlina]]>;
<![CDATA[Tajuddin Nur]]>;
<![CDATA[Maria Angela Kartawidjaja]]>;
<![CDATA[Linda Wijayanti]]>;
<![CDATA[Kumala Indriati]]>;
<![CDATA[Sheila Tobing]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 19, No 4 (2023) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v19i4.30028
<![CDATA[The existence of cogging torque in electric equipment has been considered undesirable. This kind of friction in the air-gap impacts the alignment of flux and the stator slots, resulting in the observed outcome. Consequently, the imposition of restrictions on the rotation of the rotor is employed to generate electrical energy. This research endeavor primarily aims to mitigate the cogging torque of electrical machinery. The current utilization involves employing a total of 3 permanent magnet synchronous machines, often known as inset PMMs, which possess a slot count of 24 and a pole count of 8. The employed technique involves the integration of an optimal pole arc method in conjunction with the implementation of slots cut into the magnet's edge. The machine model under investigation has two fundamental variants, namely Models 1 and 2. These models are equipped with 1one-step slotted (OSS) and 2two-step slotted (TSS) edges on each magnet, in addition to pole arc optimization. The simulation was conducted using the Finite Element Method Magnetics (FEMM) 4.2 software together with LUA scripts, with a focus on rotor rotation ranges of 1 degree. Model 2 exhibited a decrease in cogging torque of 0.01 Nm, whereas Model 1 demonstrated a reduction of 0.015 Nm, and the basic model had a decrease of 0.02 Nm. When implementing a dual-layered cutting edge on a magnet and attempting to optimize its pole arc, it is imperative to consider that the cogging torque's peak magnitude becomes substantially diminished or entirely eliminated.]]>
<![CDATA[Streamlining Deep Learning Network for Real-time Sea Turtle Detection ]]>
<![CDATA[Putro, Muhamad Dwisnanto]]>;
<![CDATA[Mose, Yuliana]]>;
<![CDATA[Andaria, Alex Copernikus]]>;
<![CDATA[Litouw, Jane]]>;
<![CDATA[Poekoel, Vecky Canisius]]>;
<![CDATA[Najoan, Xaverius]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 3 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i3.35236
<![CDATA[Monitoring turtle behavior is a conservation effort to preserve its habitat, and the detection process is a vital initial stage. On the other hand, robotics demands a deep learning network to automatically detect the presence of sea turtles that can operate in real-time. The need for increased model speed in the inference stage has led to many lightweight vision-based detectors. This work proposes a novel turtle detection to localize multiple sea turtles using a deep learning method. A lightweight primary extractor is applied to distinguish crucial features without producing a huge computational. An excited group attention is offered as an enhancement module that can capture essential turtle components in multi-level convolutional patches. A new turtle dataset is proposed that contains lighting, blur, occlusion, and complex background challenges. The evaluation results show that the proposed model performs higher accuracy than other lightweight object detection models. High-efficiency benefits models that can be implemented on low-end devices in terms of real-time data processing speed.]]>
<![CDATA[Real-Time Detection of Power Quality Disturbance Using Fast Fourier Transform and Adaptive Neuro-Fuzzy Inference System ]]>
<![CDATA[Syahrin, Ahmad Alvi]]>;
<![CDATA[Anggriawan, Dimas Okky]]>;
<![CDATA[Prasetyono, Eka]]>;
<![CDATA[Sunarno, Epyk]]>;
<![CDATA[Wahjono, Endro]]>;
<![CDATA[Sudiharto, Indhana]]>;
<![CDATA[Suhariningsih, Suhariningsih]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 1 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i1.33695
<![CDATA[Power quality disturbances cause equipment damage or financial losses. Therefore, the electric power system needs to identify and distinguish any power quality disturbances to reduce problems. This paper proposes hybrid methods combining FFT and ANFIS algorithm for detection of power quality disturbances. There are 11 types of power quality disturbances that can be detected, such as sag, swell, undervoltage, overvoltage, voltage flicker, voltage harmonic, sag + harmonic, swell + harmonic, undervoltage + harmonic, overvoltage + harmonic, and flicker + harmonic. The parameters used to detect disturbances are Vrms, Duration, THDv (Total Harmonic Distortion voltage), and Fluctuation-Count. The detection process starts by sensing voltage and calculating all the parameters, where THDv was obtained by Fast Fourier Transform. All the parameters such as Vrms, Duration, THDv, and Fluctuation-Count are processed by Adaptive Neuro-Fuzzy Inference System, and the result is the type of disturbance. Matlab simulations show that the suggested method performs outstandingly to identify 11 type of Power Quality Disturbances with 99.3% accuracy.]]>
<![CDATA[The Performance Comparison of Multiloop PID Controller on NCS Temperature Plant Based on UDP and TCP ]]>
<![CDATA[Feriyonika, Feriyonika]]>;
<![CDATA[Hong, Tjan Swi]]>;
<![CDATA[Fuadi, Miftah Hasan]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 2 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i2.33731
<![CDATA[Hardware implementations of networked control systems (NCS) are still rarely found in various research publications so that technical issues, such as how to measure random delay and substitute it into the control equation, still need to be studied further. This study is therefore aimed to compare the performance of NCS based on the used protocol in the ethernet network, i.e. user datagram protocol (UDP) or transmission control protocol (TCP), by applying it in room temperature plant. In this study, the controlled plant is influenced by the fan speed, heating, and window position plant. The heating plant is employed as the main control, while the others are set as sub-plants. The three plants use proportionalintegralderivative (PID) controller where they are regulated by fuzzy logic as the master control unit (MCU). The MCU and three PID controllers are located in the master terminal unit (MTU) while the actuators and sensors are located in the three different remote terminal units (RTU). The verification experiment shows that there is no overshoot on TCP-based NCS, while UDP has 0.725%. For the risetime, the response on UDP is faster than TCP (110.22 as compared to 138.18 s). The same thing also happened to the settling time, where the time with UDP was 101.86 s and 128.44 s for TCP.]]>
<![CDATA[Toddler Stunting Consulting Chatbot using Rasa Framework ]]>
<![CDATA[Wiwien Hadikurniawati]]>;
<![CDATA[Sutarto Wijono]]>;
<![CDATA[Danny Manongga]]>;
<![CDATA[Irwan Sembiring]]>;
<![CDATA[Kristoko Dwi Hartomo]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 19, No 4 (2023) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v19i4.33014
<![CDATA[Chatbots are artificial intelligence software that can communicate with users to assist them in certain tasks or provide information. They can reduce the need for human interaction and make processes more efficient. However, when it comes to more specific tasks related to handling the problem of stunting in toddlers these services are usually unable to provide an appropriate response. Chatbots were created with the help of the Rasa framework, which was designed to adapt the various components of natural language understanding (NLU). This adjustment allows him to understand more complex questions from respondents such as those related to healthy feeding of toddlers. This research explained the use of the Rasa framework to enhance their capabilities, describe the testing and evaluation process, and present the performance results of the chatbot model in addressing the issue of stunting in toddlers. The model is then tested using a confusion matrix, precision, accuracy, and F1 score, which measures how accurate the chatbot's responses are to the user's input. The model had a precision, accuracy, and F1 score of 0.928, 0.932 and 0.930, respectively.]]>
<![CDATA[The Effect of Partial Shadings on the Output Power of the Photovoltaic Modules Connected with Different Current and Voltage Characteristics ]]>
<![CDATA[Sara, Ira Devi]]>;
<![CDATA[Aqsa SH, Aidil]]>;
<![CDATA[Tarmizi, Tarmizi]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 3 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i3.33755
<![CDATA[A mismatch in the output power of photovoltaic (PV) modules in a PV array can occur due to partial shading or a module replacement. Substitution of a module in a PV array with a new one might lead to different current and voltage characteristics between the new and existing modules and result in power losses. The amount of power loss might be increased more if the PV array experiences partial shading. For this reason, this study aims to investigate the effect of partial shadings on the power output of photovoltaic arrays with different current and voltage characteristics. The PV array under test consists of 25 units of solar modules with a total cross-tied (TCT) configuration. There are five shading conditions applied to the test PV array, i.e., the short narrow (ShN), the short wide (ShW), the long narrow (LnN), the long wide (LnW), and the diagonal. A magic square method is applied to reduce the power loss when the PV modules experience partial shading conditions. The results show that the power loss due to partial shadings, either on all identical modules or partially identical, is the same. The most significant power loss occurs in the long comprehensive shading scenario, where 80% of the modules experience shading, which is 41.30%.]]>
<![CDATA[Augmentation of Additional Arabic Dataset for Jawi Writing and Classification Using Deep Learning ]]>
<![CDATA[Razali, Safrizal]]>;
<![CDATA[Muchtar, Kahlil]]>;
<![CDATA[Rinaldi, Muhammad Hafiz]]>;
<![CDATA[Nurdin, Yudha]]>;
<![CDATA[Rahman, Aulia]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 1 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i1.33722
<![CDATA[This research aims to create an additional dataset containing Arabic characters for writing Jawi script and to train classification models using deep learning architectures such as InceptionV3 and ResNet34. The initial stage of the study involves digital image processing to obtain the additional Arabic character dataset from several sources, including HMBD, AHAWP, and HUCD, encompassing various connected and disconnected forms of Jawi script. Image processing includes steps such as preprocessing to enhance image quality, segmentation to separate Arabic characters from the background, and augmentation to increase dataset variability. Once the dataset is formed, we train the models using appropriate training data for each InceptionV3 and ResNet34 architecture. The classification evaluation results indicate that the model with ResNet34 architecture achieved the best performance with an accuracy of 96%. This model successfully recognizes Jawi script accurately and consistently, even for classes with similar shapes. The main contribution of this research is the availability of the additional Arabic character dataset that can be utilized for Jawi script recognition and performance assessment of various deep learning models. The study also emphasizes the importance of selecting the appropriate architecture for specific character recognition tasks. The research findings affirm that the model with ResNet34 architecture has excellent capability in recognizing the additional Arabic characters for writing Jawi. The results of this research have the potential to support further developments in Jawi character recognition applications and provide valuable insights for researchers in the field of character recognition sourced from Arabic characters. Dataset augmentation results can be accessed at https://singkat.usk.ac.id/g/En0skCKGAR]]>
