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[Comparison of Neural Network Methods for Classification of Banana Varieties (Musa paradiasaca) ]]>
<![CDATA[Zilvanhisna Emka Fitri]]>;
<![CDATA[Wildan Bakti Nugroho]]>;
<![CDATA[Abdul Madjid]]>;
<![CDATA[Arizal Mujibtamala Nanda Imron]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 17, No 2 (2021) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v17i2.20806
<![CDATA[Every region in Indonesia has a very large diversity of banana species, but no system records information about the characteristics of banana varieties. The purpose of this research is to make an encyclopedia of banana types that can be used for learning by classifying banana varieties using banana images. This banana variety classification system uses image processing techniques and artificial neural network methods as classification methods.The varieties of bananas used are pisang merah, pisang pisang mas kirana, pisang klutuk, pisang raja and pisang cavendis. The parameters used are color features (Red, Green, and Blue) and shape features (area, perimeter, diameter, and length of fruit). The intelligent system used is the Backpropagation method and the Radial Basis Function Neural Network. The results showed that both methods were able to classify banana varieties with an accuracy rate of 98% for Backpropagation and 100% for the Radial Basis Function Neural Network.]]>
<![CDATA[Auskultasi Jarak Jauh untuk Pengukuran dan Perekaman Sinyal Suara Jantung ]]>
<![CDATA[Eka Sari Oktarina]]>;
<![CDATA[Ira Puspasari]]>;
<![CDATA[Jusak Jusak]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 14, No 3 (2018) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v14i3.12013
<![CDATA[In 2014, the Sample Registration System (SRS) released a survey showing that heart diseases can be categorized as the second highest non-communicable disease in Indonesia. The percentage is 12.9%. In this work, a tele-auscultation system for heart sound signals was built to transmit the signal over the global Internet networks and store them in a Cloud storage. Thus, the system allows measurement of heart sound signal for the rural area where the presence of expert is very scarce and helps the expert doctors to perform clinical analysis anywhere. Our examination showed that the system exhibited the average transmission delay of 5.68 second and data lost of only less than 1% for transmission of 1 heart sound signal. On the other hand, examination using two heart sound signals transmitted simultaneously showed that it displayed a smaller average of transmission delay. It may be caused by the measurement of the transmission delay as well as data lost that is depended on the traffic in the internet networks. Moreover, correlation of the heart sound signals before and after transmission showed a strong correlation where the correlation value is very close to 1 at, indicating that there is a strong similarity between the two signals.]]>
<![CDATA[Identification of Power Quality Disturbances Based on Fast Fourier Transform and Artificial Neural Network ]]>
<![CDATA[Dimas Okky Anggriawan]]>;
<![CDATA[Endro Wahjono]]>;
<![CDATA[Indhana Sudiharto]]>;
<![CDATA[Anang Budikarso]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 19, No 1 (2023) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v19i1.27120
<![CDATA[This paper presents the proposed algorithms for the identification of Short Duration RMS Variations and Long Duration RMS Variations combined with harmonic. The proposed algorithms are Fast Fourier Transform (FFT) and Artificial Neural Network (ANN). The Algorithms identify nine types of Power Quality (PQ) disturbances such as normal signal, voltage sag, voltage swell, under voltage, over voltage, voltage sag combined harmonic, voltage swell combined harmonic, undervoltage combined harmonic, and over voltage combined harmonic. FFT is used to obtain the frequency spectrum of each PQ disturbance with frequency sampling of 1000 Hz, data length of 200. Output FFT is used to input data for ANN. Output ANN is a type of nine PQ disturbances. The result shows that proposed algorithms (FFT combined ANN) are effective for identification, which ANN with 20 neurons in the hidden layer has an accuracy of approximately 99.95 %]]>
<![CDATA[Peningkatan Kinerja MPPT Menggunakan Kontrol PWM Fuzzy dengan Tuning PID ]]>
<![CDATA[Adhi Kusmantoro]]>;
<![CDATA[Margono Margono]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 16, No 2 (2020) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v16i2.16220
<![CDATA[Utilization of sunlight using solar panels as power plants began to be developed to reduce the use of fossil fuels. The purpose of this study is to design an MPPT model with PV sources. The PID controller is used to improve MPPT performance in regulating the boost converter, while the PID value is set with fuzzy logic. Research methods include simulation design, hardware, load capacity calculation, and fuzzy logic design. The trial was conducted using an electric load in the house. The results of previous studies, using PID control generated 88.77% efficiency. The results of the study using PID control that is regulated by fuzzy logic produces 95.79% efficiency. This method is also able to improve the output of the boost converter voltage, so that with this method the boost converter output voltage is better when compared to other methods. ]]>
<![CDATA[Kajian Awal Penentuan Daerah Prospek Panas Bumi di Gunung Bur Ni Telong berdasarkan Analisis Data DEM SRTM dan Citra Landsat 8 ]]>
<![CDATA[Lukmanul Hakim]]>;
<![CDATA[Nazli Ismail]]>;
<![CDATA[Faisal Faisal]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 13, No 3 (2017) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v13i3.8332
<![CDATA[Research for a preliminary study of Bur Ni Telong, geothermal area, Bener Meriah district using remote sensing techniques has been done. The aims of the research were to determine the morphological condition based on the fault and fracture (FFD) map from the interpreted digital elevation model (DEM) shuttle radar topography mission (SRTM) and to know the vegetation density and surface temperature distribution using Landsat 8 image. The DEM SRTM data were analyzed using the lineament pattern which related to faults and fractures. The vegetation density was calculated using normalized difference vegetation index (NDVI) transformation. The estimated surface temperature was used to locate temperature anomaly. Referring to the geographical map, the dense class area include Silih Nara-Ketol-Peulimbang to Peudada, Juli to Sawang, and Bandar area. The fault and fracture dominantly have directions in East-West and Northwest-Southeast. While based on NDVI map we conclude that the area is covered by dense vegetation, dominated by intermediate to dense of vegetation. The LST map shows the location of maximum surface temperature values are in agreement with residential areas and uncovered areas, as in the areas of Simpang Tiga Redelong and Takengon. Some geothermal manifestations are located in sparse to intermediate vegetation areas with high temperature.]]>
<![CDATA[Analisis dan Simulasi Video Watermarking Menggunakan Metode Dual Tree Complex Wavelet Transform (DT-CWT) dan Singular Value Decomposition (SVD) ]]>
<![CDATA[Arina Fadhilah]]>;
<![CDATA[Bambang Hidayat]]>;
<![CDATA[Ratri Dwi Atmaja]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 12, No 2 (2016) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v12i2.3993
<![CDATA[Video piracy is the act of obtaining, copying, and selling or distributing videos that already had the copyright without the consent of the copyright owner. Watermarking is a process which embeds an additional information in the host video signal so that the embedded watermark cannot be seen and difficult to be erased or altered. Video watermarking in this journal used a mp4 format video and two different watermark images. Host video frames are divided into two equal lots, some of the frames are embedded by watermark image 1, and the others are embedded by watermark images 2. The methods used are Dual-Tree Complex Wavelet Transform (DTCWT) and Singular Value Decomposition (SVD). The two watermarks are embedded and extracted in each subband at a depth level 1 to level 4 DTCWT - SVD with the aim of seeking the best subband and the best level for embedding and extracting. In the extraction testing, watermarked video is given several attacks before extraction process. Based on the MOS and PSNR value the DTCWT-SVD level for embedding process is level 4, and based on the MOS and MSE value, the best extraction images are produced from the level 3. The best subband for embedding watermark are the subbands with three parts such as {1,5}{1,1}{1,2} and {1,5}{1,2}{1,2}.]]>
<![CDATA[Fine Tuning CNN Pre-trained Model Based on Thermal Imaging for Obesity Early Detection ]]>
<![CDATA[Hendrik Leo]]>;
<![CDATA[Fitri Arnia]]>;
<![CDATA[Khairul Munadi]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 18, No 1 (2022) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v18i1.25100
<![CDATA[Obesity is a complex disease that causes serious impact health, such as diabetes mellitus, cardiovascular disease, cancer, and stroke. An early obesity diagnosis/ detection method is required to prevent the increasing number of obese people. This study aims to: (i) fine-tune the pre-trained Convolutional Neural Network (CNN) models to build an early detection of obesity and (ii) evaluate the model performance in terms of classifying performance, computation speed, and learning performance. The thermal images acquisition procedure was conducted with 18 normal subjects and 15 obese subjects to build a thermal images dataset of obesity. Pre-trained CNN models: VGG19, MobileNet, ResNet152V, and DenseNet201 were modified and trained using the acquired dataset as the input. The training results show that the DenseNet201 model outperformed other models regarding classifying accuracy: 83.33 % and learning performances. At the same time, the MobileNet model outperformed other models in terms of computation speed with training elapsed time: 12 seconds/epoch. The proposed DenseNet201 model was suitable for implementation as an early screening system of obesity for health workers or physicians. Meanwhile, the proposed MobileNet model was suitable for mobile applications' early detection/diagnosis of obesity.]]>
<![CDATA[Prototipe Pengukuran Kadar Gula dalam Tubuh Manusia Melalui Urin ]]>
<![CDATA[Mohammad Hafiz Hersyah]]>;
<![CDATA[Budi Rahmadya]]>;
<![CDATA[Gentha Wijaya]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 15, No 2 (2019) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v15i2.13034
<![CDATA[In this research, we propose a prototype to measure glucose index in human body after applying benedict reagen into urine samples. This system divides into two main components that are identification device and android smartphone. The identification device consists of TCS3200 colour sensor and a raspberry pi. The TCS3200 colour sensor's function is to predict the alteration of urine sample and determine the colour category according to the benedict rule and to measure the glucose in the sample. The Raspberry pi function is to process the data that acquired from the colour sensor. By optimizing with Tsukamoto Fuzzy Logic Control, the research successfully identifies the glucose by achieving 100% and the result of fuzzy logic control on Raspberry Pi as decision making by urine in 90% and by conflicting minimum error in 5.6%.]]>
<![CDATA[FPGA Implementation of Uniform Random Number based on Residue Method ]]>
<![CDATA[Z Zulfikar]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 11, No 1 (2014) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v11i1.1990
<![CDATA[This paper presents the implementation and comparisons of uniform random number on Field Programable Gate Array (FPGA). Uniform random numbers are generated based on residue method. The circuit of generating uniform random number is presented in general view. The circuit is constructed from a multiplexer, a multiplier, buffers and some basic gates. FPGA implementation of the designed circuit has been done into various Xilinx chips. Simulation results are viewed clearly in the paper. Random numbers are generated based on different parameters. Comparisons upon occupied area and maximum frequency from different Xilinx chip are examined. Virtex 7 is the fastest chip and Virtex 4 is the best choice in terms of occupied area. Finally, Uniform random numbers have been generated successfully on FPGA using residue method.Keywords: FPGA implementation, random number, uniform random number, residue method, Xilinx chips]]>
<![CDATA[Pemanfaatan Citra Satelit Google Earth untuk Penilaian Progres Pemulihan Lahan Pasca 15 Tahun Tsunami Aceh di Kecamatan Lhoong, Aceh Besar ]]>
<![CDATA[Ismiatul Ramadhian Nur]]>;
<![CDATA[Syamsidik Syamsidik]]>;
<![CDATA[Saumi Syahreza]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 17, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v17i1.19402
<![CDATA[The 2004 Indian Ocean Tsunami has changed the land cover of the affected areas. Sixteenth years after the tsunami, studies pertinent to land restoration progress are becoming crucial as one of the needs in assessing the progress of the long-term disaster recovery process. Spatio-temporal land change assessment in a disaster-affected area can be conducted using time-series satellite imagery. One of them is The Google Earth satellite image which has an adequate prior data record. Although it has a single band, the Google Earth satellite imagery has many other advantages: easy access, free of charge, and decent resolution for detailed mapping. This research aims to assess the progress of land restoration by utilizing Google Earth satellite imagery. The applied method is visual observation and on-screen digitization process by Google Earth Pro and QGIS. This study provides outcomes of the trend of land transformation after the tsunami, which shows that the rice fields and ponds have not recovered to the condition before the tsunami. Meanwhile, the length of the road and building area have exceeded the pre-tsunami time. The entire land uses show an increasing trend with varying percentages from 2010 to 2020. This research is essential to carry out as an initial assessment of the long-term recovery process, especially related to the livelihood conditions of survivors after the 15 years of the tsunami, which is monitored through land cover. ]]>
