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
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Optimizing Technical Losses of the PLN Distribution Network with Changes in Operational Patterns in 2023 at PLN ULP Lhokseumawe
Arnawan Hasibuan;
Ari Afrizal;
Misbahul Jannah;
Sapto Nisworo;
Fajar Syahbakti Lukman;
I Made Ari Nrartha
Jurnal Rekayasa Elektrika Vol 19, No 4 (2023)
Publisher : Universitas Syiah Kuala
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DOI: 10.17529/jre.v19i4.33838
Technical shrinkage is shrinkage caused by impedance in generation equipment or transmission equipment to the distribution network so that there is energy loss. There are several technical shrinkage problems at PT. Perusahaan Listrik Negara (PLN) especially in Customer Service Unit (ULP) Lhokseumawe City and for now the cause is still unsolved, because this technical shrinkage problem will harm and have an impact on consumers and PLN itself. The purpose of the study was to optimize technical shrinkage in the distribution network to reduce energy losses that occurred during the electrical power distribution process in the distribution network of PT. PLN (Persero) ULP Lhokseumawe City. This study uses the help of Electrical Transient Analyzer Program (ETAP) software to simulate the power flow so that the depreciation value that occurs is obtained, then re-load adjustment is carried out to simulate again to determine the change in the depreciation value obtained after load adjustment. The results of the ETAP simulation show the depreciation value that occurred before the load adjustment was made by 76.7 kW after the depreciation load adjustment was adjusted to 59.6 kW. This means that this technical shrinkage can be suppressed by changing the feeder operation pattern and voltage drop value in accordance with the limitation provisions set in SPLN 72:1987.
Declining Cogging Torque Technique of an Integral Slot Number for Permanent Magnet Machines
Herlina Herlina;
Tajuddin Nur;
Maria Angela Kartawidjaja;
Linda Wijayanti;
Kumala Indriati;
Sheila Tobing
Jurnal Rekayasa Elektrika Vol 19, No 4 (2023)
Publisher : Universitas Syiah Kuala
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DOI: 10.17529/jre.v19i4.30028
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.
Toddler Stunting Consulting Chatbot using Rasa Framework
Wiwien Hadikurniawati;
Sutarto Wijono;
Danny Manongga;
Irwan Sembiring;
Kristoko Dwi Hartomo
Jurnal Rekayasa Elektrika Vol 19, No 4 (2023)
Publisher : Universitas Syiah Kuala
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DOI: 10.17529/jre.v19i4.33014
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.
Control System Design for Water Pump Activation in PLC-based Smart Hydroponic Design
Muhammad Edy Hidayat
Jurnal Rekayasa Elektrika Vol 19, No 4 (2023)
Publisher : Universitas Syiah Kuala
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DOI: 10.17529/jre.v19i4.33443
Food security is one of the issues that is one of the concerns to the country government, and one of the independent efforts made by community on their awareness to meet and achieve food needs on a domestic scale in their respective households is through hydroponic for cultivation of vegetables. Hydroponics works by using water as growing medium instead of soil, however, the use of water as a planting medium requires special treatment thus the plants is able to grow optimally. To ensure that the air content in the water used as a hydroponic growing medium is properly available, a water regulation process is needed. The process of water regulation in the hydroponic system uses regulation of the activation of the water pump motor so that water can be regulated and electrical energy efficiency can still be achieved. This study aims to design and test a PLC-based automation system for the purposes of setting the activation of a water pump in a hydroponic system based on the sunlight conditions in the hydroponic installation being built. By using a light sensor (LDR) to measure the intensity of sunlight in the hydroponic system being built, the activation of the pump motor can be controlled through the use of a PLC device that processes the information obtained from the sensor used. The results of the tests carried out provide information that the designed system has proven effective for use in hydroponic systems with pump water regulation time from 08:00 AM to 04:00 PM.
Power Consumption Predictive Analytics and Automatic Anomaly Detection Based on CNN-LSTM Neural Networks
Arif Irwansyah;
Effry Muhammad;
Firman Arifin;
Budi Nur Iman;
Hendhi Hermawan
Jurnal Rekayasa Elektrika Vol 19, No 4 (2023)
Publisher : Universitas Syiah Kuala
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DOI: 10.17529/jre.v19i4.31695
In this modern era, electrical energy plays a crucial role in human life, as it is essential for most household appliances. The number of appliances requiring electrical energy increases each year, meeting the growing needs of users. However, electricity consumers tend to forget this fact and only realize its importance when they receive a significantly increased monthly electricity bill or face problems caused by anomalies in electricity use. Such anomalies can lead to substantial losses, especially when electrical equipment is damaged or left switched on without awareness. To make better decisions in such situations, real-time and accurate information is necessary, which can be achieved through data analytics utilizing machine-learning and predictive analytics. The purpose of this paper is to introduce the CNN-LSTM method of data analytic modeling for power consumption data collected through an electric data logger, which can help predict future power usage and detect real-time anomalies in the power network. The proposed model was tested using hourly electricity consumption data, and the results showed that the CNNLSTM method outperformed the LSTM model. The CNN-LSTM model had a 29% smaller Mean Squared Error (MSE) score than the LSTM method.