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[Analisis Kinerja MySQL Cluster Menggunakan Metode Load Balancing ]]>
<![CDATA[Taufiq Abdul Gani]]>;
<![CDATA[Aulia Arafat]]>;
<![CDATA[. Melinda]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 11, No 4 (2015) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v11i4.2358
<![CDATA[Information system and data is a very important thing nowadays. An information system especially a database is designed with a high data availability. One of the database systems is MySQL cluster. Sometimes, its performance decreased because of the system’s incapablity to handle the data. To overcome this problem, the research of load balancing systems for MySQL cluster is needed. This research is intended to analyze the effect of load balancing clustering methods on MySQL cluster which by default has been set as failover clustering. The analysis is done through data collection and database transactions test to get the number of Transactions per second (TPS) and response time parameter using SysBench. The test is divided into two main scenarios, the simple and complex-mode that running on 4 computers. The tests were conducted by giving workloads from 8 up to 128 threads respectively to the server through a client on default conditions and load balancing. The test results showed the number of TPS at MySQL cluster default is 536.61. In contrast, number of TPS at load balancing is better at 2261.22. Likewise, the response time at MySQL cluster load balancing is 147.55 ms faster than that of the default one at 335.00 ms.]]>
<![CDATA[Dynamic Bandwidth Allocation for Internet of Things System Using Elastic Wireless Local Area Network ]]>
<![CDATA[I Putu Sudharma Yoga]]>;
<![CDATA[Gede Sukadarmika]]>;
<![CDATA[Linawati Linawati]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 17, No 3 (2021) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v17i3.21087
<![CDATA[Rapid technological development, triggering various applications development that are increasingly innovative. One of them is the Internet of Things (IoT) system that makes human works easier and more effective. Along with sensor technology development in monitoring and controlling through IoT systems, a mechanism is needed to manage bandwidth so that IoT system can function optimally, especially in buildings designated as public areas. Smart building supported by various integrated sensors to maintain safety and comfort in the area. This study proposes the application of Elastic WLAN as a model for dynamic bandwidth management in IoT systems. In this model, IoT bandwidth changes automatically according to the number of traffic measurements for each IoT connected to the network As an effort to determine the performance of the elastic WLAN mechanism, this study succeeded in developing a prototype IoT device that implements Elastic WLAN on an Access-Point Raspberry Pi by using two temperature sensors placed in separate locations. The system successfully allocates bandwidth to each IoT according to the amount of data input from each temperature sensor installed. The higher the amount of data captured by the sensor, the system will automatically allocate the higher bandwidth to the sensor system, and vice versa.]]>
<![CDATA[Sistem Portable Dashboard Berbasis Android untuk Mobil Listrik ]]>
<![CDATA[Bambang Sumantri]]>;
<![CDATA[Anggita Abimayu]]>;
<![CDATA[Ni’am Tamami]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 14, No 3 (2018) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v14i3.11826
<![CDATA[In the development of an electric car, many things should be considered for making it an environmentally friendly vehicle and therefore it is suitable for public use, one of them is the dashboard system. A dashboard is an interface device that connects the driver with the electrical and mechanical systems of the vehicle. In this study a dashboard system was developed to display information about electrical aspects of electric cars. The dashboard system is packaged in an Android-based smartphone that is placed on the steering wheel of the car using Bluetooth transmission. The system that is made is portable and universal on all Android smartphones so that with this system the driver can monitor the electrical condition easily and conveniently. The parameters displayed are battery voltage and capacity, current consumption, BLDC motor rotational speed, motor temperature, battery temperature, car speed and energy consumption. This system creates a reading value for each parameter that corresponds to the ratio of the standardized measuring instrument with an average error of 0.38% for the voltage sensor, 1.06% for the current sensor, 1.21% and 2.98% for the temperature sensor, 0.07% for the speed sensor and the use of the coulomb counting method for reading the state of charge (SoC) value produces an average error of 1.57%. By comparing the value of energy consumption reading with a standard wattmeter, we obtained an average difference of 1.69%.]]>
<![CDATA[Pemodelan Robot Beroda Menggunakan Umpan Balik Giroskop ]]>
<![CDATA[Aulia Rahman]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 12, No 2 (2016) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.13170/aijst.%v.%i.4903
<![CDATA[Modeling of a system is an important step for designing a good controller for a wheeled mobile robot. There are several techniques can be used gaining a model. One is deriving an analytical model mathematically. Another technique is by using system identification where the robot is given an input test signal and then measured the output signal. This technique, in general, is simpler compared to the analytic one. This paper described the modeling of a wheel mobile robot and used a gyroscope sensor as a feedback.The transfer function model of the robot is a second order system.]]>
<![CDATA[Substraksi Latar Menggunakan Nilai Mean Untuk Klasifikasi Kendaraan Bergerak Berbasis Deep Learning ]]>
<![CDATA[Ilal Mahdi]]>;
<![CDATA[Kahlil Muchtar]]>;
<![CDATA[Fitri Arnia]]>;
<![CDATA[Tia Ernita]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 18, No 2 (2022) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v18i2.25224
<![CDATA[Moving object detection systems have been widely used in everyday life. Currently, research in the field of background subtraction is still being carried out to achieve maximum accuracy results. This study aims to model the background subtraction of an image using the mean value with the concept of non-overlapping block. Furthermore, the background abstraction results will be used in deep learning-based moving object detection. Specifically, the input image will be divided into several blocks, then the mean value of each block will be calculated to later produce a binary block (binary map). The binary blocks that have been generated will be used as input for background modeling. The background model aims to separate moving objects from the background in the input image. The resulting moving object (object localization) will be sent to the object classification stage using deep learning. The dataset used in this study is CDNet 2014. The results of the study were able to produce a more accurate moving object detection system. Quantitative tests carried out resulted in an accuracy of above 90%.]]>
<![CDATA[IEEE 802.11ac sebagai Standar Pertama untuk Gigabit Wireless LAN ]]>
<![CDATA[Afdhal Afdhal]]>;
<![CDATA[Elizar Elizar]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 11, No 1 (2014) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v11i1.1994
<![CDATA[WLAN is a technology that currently has been used widely. This technology is considered as a data transferring media technology within the LAN/MAN. To ensure that WLAN technology can be used widely in the whole world, the IEEE has set a standard known as 802.11 to be an international standard for the WLAN technology. This standard was appeared in 1997, and has been revised and improved for several times. This improvement is done to anticipate the rapidly grown WLAN market as well as to keep this technology remains effective, efficient, and reliable at any time. At the beginning of 2014, the IEEE has set 802.11ac-2013 as a new standard for WLANs that operate below 6 GHz to achieve a data rate for up to 7 Gbps. The purpose of this article is to describe comprehensively the IEEE 802.11ac standard as a result of recent changes to the regulatory for WLAN technology which is known as the first standard issued by the IEEE for the gigabit WLANs. This article discusses the goals and objectives to be achieved by 802.11ac standard as well as the parts that have been enhanced significantly both in its PHY and MAC layers. This article will also contrast the differences between the 802.11ac standard and previous WLAN standards. Finally it will also explain the level of compatibility and interoperability of 802.11ac standards with some of previous WLAN standard.Keywords: IEEE, 802.11, 802.11ac, Gigabit WLAN]]>
<![CDATA[Pengenalan Pola Berbasis OCR untuk Pengambilan Data Bursa Saham ]]>
<![CDATA[M. Dyovan Uidy Okta]]>;
<![CDATA[Suci Aulia]]>;
<![CDATA[Burhanuddin Burhanuddin]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 17, No 2 (2021) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v17i2.19656
<![CDATA[The investor must be able to use instinct to evaluate when to sell and buy stocks. This is, of fact, a weakness for inexperienced investors, in addition to the decision's inaccuracy and the time it takes to evaluate a slew of ineffective results. So that, a support system is needed to help the investors make decisions in buying and selling shares. This support system creates an online analysis curve display through text data in the BEI stock price application. The data processing based on pattern recognition will be carried out so that a buying and selling decision can be made to calculate the profit and loss by investors. As the first step of the whole system, this research has built an image-to-text conversion system based on OCR (Optical Character Recognition) that can convert the non-editable text (.jpg) to be editable (.text) online. After obtaining this .text data, the will used the system in further research to analyze stock buying and selling decisions. According to research on eight companies, the OCR-based image to text conversion has a 96.8% accuracy rate. Meanwhile, using Droid serif, Takao PGhotic, and Waree fonts at 12pt font sizes, it has 100 percent accuracy in Libre Office. ]]>
<![CDATA[Analisis Kinerja Protokol Routing AODV, DSR, dan OLSR pada Mobile Ad hoc Network Berdasarkan Parameter Quality of Service ]]>
<![CDATA[Alamsyah Zakaria]]>;
<![CDATA[Eko Setijadi]]>;
<![CDATA[I Ketut Eddy Purnama]]>;
<![CDATA[Mauridhi Hery Purnomo]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 14, No 3 (2018) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v14i3.9798
<![CDATA[MANET is autonomous, self-configured, and applicable to emergency locations such as forest fires, earthquakes, floods, and health monitoring. However, challenges and difficulties faced by the mobile ad-hoc network (MANET) is a dynamically built network system, without the support of infrastructure in communicating between one node and other nodes, and limited energy sources. To overcome MANET problems and to obtain optimal network quality, the selections of routing protocols and quality of service (QoS) are significant in MANET design. This study aims to analyze the performance of routing protocols: dynamic source routing (DSR), ad-hoc on demand distance vector (AODV) and optimized link state routing (OLSR) based on QoS. The analyzed QoS parameters include packet delivery ratio (PDR), packet loss, throughput, and delay. Simulation results using network simulator version based on the number of node densities indicate that OLSR has better performance compared to AODV and DSR regarding PDR, packet loss, throughput, and delay.]]>
<![CDATA[Perancangan dan Implementasi Alat Pendeteksi Dini Penyakit Jantung Koroner ]]>
<![CDATA[Budi Nur Iman]]>;
<![CDATA[Raay Rafikasitha]]>;
<![CDATA[Kemalasari Kemalasari]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 18, No 4 (2022) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v18i4.27240
<![CDATA[Penyakit jantung koroner merupakan penyebab kematian tertinggi di Indonesia setelah stroke dengan persentase sebesar 12,9%. Penyakit jantung koroner terjadi akibat penumpukan plak yang disebabkan oleh tingginya kadar kolesterol serta meningkatnya tekanan darah dalam jangka panjang. Dibutuhkan sistem yang dapat memantau kesehatan jantung secara berkala. Pada penelitian ini menyajikan sistem yang mampu melakukan deteksi dini penyakit jantung koroner yang terdiri dari kategori risiko rendah, sedang, dan tinggi berdasarkan tiga parameter yaitu kolesterol, tekanan darah, dan detak jantung. Pengukuran kolesterol dilakukan secara non-invasif menggunakan LED sebagai transmitter dan photodioda sebagai receiver. Pengukuran tekanan darah menggunakan sensor MPX5100DP dengan metode osilometri, dan pengukuran detak jantung menggunakan sensor MAX30102. Data dari sensor dan informasi tambahan berupa jenis kelamin, usia, dan status perokok akan diolah dengan metode K-Nearest Neighbor untuk mengetahui hasil klasifkasi penyakit jantung koroner. Dari keseluruhan pengukuran, akurasi rata-rata untuk pengukuran kolesterol adalah 97,9%, pengukuran tekanan darah sistolik adalah 96,3%, tekanan darah diastolik 92,7%, dan pengukuran detak jantung adalah 98,8%. Klasifikasi penyakit jantung koroner pada 15 responden menggunakan metode K-Nearest Neighbor memiliki perbedaan sekitar 20% dengan perhitungan menggunakan tabel Framingham Risk Score yang dilakukan oleh dokter.]]>
