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JURNAL NASIONAL TEKNIK ELEKTRO
Published by Universitas Andalas
ISSN : 23022949     EISSN : 24077267     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Jurnal Nasional Teknik Elektro (JNTE) adalah jurnal ilmiah peer-reviewed yang diterbitkan oleh Jurusan Teknik Elektro Universitas Andalas dengan versi cetak (p-ISSN:2302-2949) dan versi elektronik (e-ISSN:2407-7267). JNTE terbit dua kali dalam setahun untuk naskah hasil/bagian penelitian yang berkaitan dengan elektrik, elektronik, telekomunikasi dan informatika.
Arjuna Subject : -
Articles 610 Documents
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Short-Term EV Charging Demand Forecast with Feedforward Artificial Neural Network Francis Boafo Effah; Daniel Kwegyir; Daniel Opoku; Peter Asigri; Emmanuel Asuming Frimpong
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1094.2023

Abstract

The global increase in greenhouse gas emissions from automobiles has brought about the manufacture and usage of large quantities of electric vehicles (EVs). However, to ensure proper integration of EVs into the grid, there is a need to forecast the charging demand of EVs accurately. This paper presents a short-term electric vehicle charging demand forecast using a feedforward artificial neural network optimized with a modified local leader phase spider monkey optimization (MLLP-SMO) algorithm, a proposed variant of spider monkey optimization. A proportionate fitness selection is employed to improve the update process of the local leader phase of the spider monkey optimization. The proposed algorithm trains a feedforward neural network to forecast electric vehicle charging demand. The effectiveness of the proposed forecasting model was tested and validated with electric vehicle public charging data from the United Kingdom Power Networks Low Carbon London Project. The model's performance was compared to a feedforward neural network trained with particle swarm optimization, genetic algorithm, classical spider monkey optimization, and two conventional forecasting models, multi-linear regression and Monte Carlo simulation. The performance of the proposed forecasting model was assessed using the mean absolute percentage error of forecast and forecasting accuracy. The model produced a forecast accuracy and mean absolute percentage error of 99.88% and 3.384%, respectively. The results show that MLLP-SMO as a trainer predicted better than the other forecasting models and met industry standard forecast accuracy.
Hyperbolic Tangent - Based Adaptive Inertia Weight Particle Swarm Optimization Yaw Opoku Mensah Sekyere; Francis Boafo Effah; Philip Yaw Okyere
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1095.2023

Abstract

This paper presents a study on using adaptive inertia weight (AIW) in particle swarm optimization (PSO) for solving optimization problems. An AIW function based on the hyperbolic tangent function was proposed, with the function parameters adaptively tuned based on the particle best and global best values. The performance of the proposed AIW-PSO was compared with standard PSO and other PSO variations using seven benchmark functions. The results showed that the proposed AIW-PSO outperformed the other variations in terms of minimum cost and mean cost while reducing the standard deviation of cost. The performance of the different PSO variations was also analysed by plotting the best cost against iteration, with the proposed AIW-PSO showing a faster convergence rate. Overall, the study demonstrates the effectiveness of using an adaptive inertia weight function in PSO for optimizing problems.
Perancangan Kendali Operasi Otomatis Terowongan Angin ILST Berbasis HMI Franky Surya Parulian; Munawar Agus Riyadi; Ivransa Zuhdi Pane; Muhamad Muflih
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1098.2023

Abstract

In the application of the Indonesian Low-Speed Tunnel (ILST), the control of wind tunnel operations can determine the validity of the data and the number of tests achieved daily. The current operation control mechanism is still done manually and separately with one series of measurements for one test model configuration, inefficient human resources, acquisition of data that can be different, and the cost of using electric power is quite expensive. Therefore, this research and development activity proposes a wind tunnel automatic operation control system that integrates several plant facilities and ILST data acquisition based on Human Machine Interface (HMI) with the Waterfall method, using SCADA software and PLC. This aims to improve wind tunnel operation in one measurement series for multiple test model configurations with high data acquisition accuracy, faster and easier operation to reduce operating costs. This automatic operation control can increase operation time two times faster and 61% cheaper than manual operation. The design results will be used at the implementation stage in aerodynamic model testing.
Innovative Personal Assistance: Speech Recognition and NLP-Driven Robot Prototype Michelle Valerie; Irma Salamah; Lindawati
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1105.2023

Abstract

This paper presents the development and evaluation of a personal assistant robot prototype with advanced speech recognition and natural language processing (NLP) capabilities. Powered by a Raspberry Pi microprocessor, it is the core component of the robot's hardware. It is designed to receive commands and promptly respond by performing the requested actions, utilizing integrated speech recognition and NLP technologies. The prototype aims to enhance meeting efficiency and productivity through audio-to-text conversion and high-quality image capture. Results show excellent performance, with accuracy rates of 100% in Indonesian and 99% in English. The efficient processing speed, averaging 9.07 seconds per minute in Indonesian and 15.3 seconds per minute in English, further enhances the robot's functionality. Additionally, integrating a high-resolution webcam enables high-quality image capture at 1280 x 720 pixels. Real-time integration with Google Drive ensures secure storage and seamless data management. The findings highlight the prototype's effectiveness in facilitating smooth interactions and effective communication, leveraging NLP for intelligent language understanding. Integrating NLP-based speech recognition, visual documentation, and data transfer provides a comprehensive platform for managing audio, text, and image data. The personal assistant robot prototype presented in this research represents a significant advancement in human-robot interaction, particularly in meeting and collaborative work settings. Further refinements in NLP can enhance efficiency and foster seamless human-robot interaction experiences.
Model Berbasis Transfer Learning untuk Deteksi Tumor Otak pada Citra MRI Faiz Rofi Hencya; Satria Mandala; Tong Boon Tang; Mohd Soperi Mohd Zahid
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1123.2023

Abstract

Brain tumors are life-threatening medical conditions characterized by abnormal cell proliferation in or near the brain. Early detection is crucial for successful treatment. However, the scarcity of labelled brain tumor datasets and the tendency of convolutional neural networks (CNNs) to overfit on small datasets have made it challenging to train accurate deep learning models for brain tumor detection. Transfer learning is a machine learning technique that allows a model trained on one task to be reused for a different task. This approach is effective in brain tumor detection as it allows CNNs to be trained on larger datasets and generalize better to new data. In this research, we propose a transfer learning approach using the Xception model to detect four types of brain tumors: meningioma, pituitary, glioma, and no tumor (healthy brain). The performance of our model was evaluated on two datasets, demonstrating a sensitivity of 98.07%, specificity of 97.83%, accuracy of 98.15%, precision of 98.07%, and f1-score of 98.07%. Additionally, we developed a user-friendly prototype application for easy access to the Xception model for brain tumor detection. The prototype was evaluated on a separate dataset, and the results showed a sensitivity of 95.30%, specificity of 96.07%, accuracy of 95.30%, precision of 95.31%, and f1-score of 95.27%. These results suggest that the Xception model is a promising approach for brain tumor detection. The prototype application provides a convenient and easy-to-use way for clinical practitioners and radiologists to access the model. We believe the model and prototype generated from this research will be valuable tools for diagnosing, quantifying, and monitoring brain tumors.
Performance Enhancement of Elephant Herding Optimization Algorithm Using Modified Update Operators Abdul-Fatawu Seini Yussif; Elvis Twumasi; Emmanuel Asuming Frimpong
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1124.2023

Abstract

This research paper presents a modified version of the Elephant Herding Optimization (EHO) algorithm, referred to as the Modified Elephant Herding Optimization (MEHO) algorithm, to enhance its global performance. The focus of this study lies in improving the balance between exploration and exploitation within the algorithm through the modification of two key operators: the matriarch updating operator and the separation updating operator. By reframing the equations governing these operators, the proposed modifications aim to enhance the algorithm’s ability to discover optimal global solutions. The MEHO algorithm is implemented in the MATLAB environment, utilizing MATLAB R2019a. To assess its efficacy, the algorithm is subjected to rigorous testing on various standard benchmark functions. Comparative evaluations are conducted against the original EHO algorithm, as well as other established optimization algorithms, namely the Improved Elephant Herding Optimization (IEHO) algorithm, Particle Swarm Optimization (PSO) algorithm, and Biogeography-Based Optimization (BBO) algorithm. The evaluation metrics primarily focus on the algorithms’ capacity to produce the best global solution for the tested functions. The proposed MEHO algorithm outperformed the other algorithms on 75% of the tested functions, and 62.5% under two specific test scenarios. The findings highlight the effectiveness of the proposed modification in enhancing the global performance of the Elephant Herding Optimization algorithm. Overall, this work contributes to the field of optimization algorithms by presenting a refined version of the EHO algorithm that exhibits improved global search capabilities.
Methyl Ester-Mineral Oil Mixture under Thermal Aging Rajab, Abdul; Alfaradhi, Panglima Ibnu; Putra, Rizky Kencana; Nofendra, Riko
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 3: November 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n3.1029.2023

Abstract

Replacement with natural esters (retrofilling) is an alternative solution to extend the life expectancy of an oil-filled transformer containing mineral oil. During the retro-filling process, some portions of the mineral oil remain inside the transformer's tank, forming a mixture between the used mineral oil and the new vegetable oil. In this investigation, methyl ester was mixed with a relatively low percentage of mineral oil to simulate the retro-filling process. The aim is to examine the characteristics of a mixture of mineral and vegetable oils under thermal aging. Thermal aging treatments were carried out at 120°C for 28 days and 140°C for 14 days. Kraft paper and copper wire were incorporated during the aging test. After thermal aging, the characteristics of the oil mixture were evaluated based on electrical, physical, and chemical characteristics. The result shows that physical and chemical characteristics are significantly influenced by the increase in mineral oil content and the temperature of thermal aging. However, the breakdown voltage increased after thermal aging, but at a higher temperature, the breakdown voltage dropped as the mineral oil content increased.
The Design of Soil Temperature and Humidity Monitoring Systems with IoT-Based LoRa Technology Baharuddin; Akbar Alhaqi Hidayat; Hanalde Andre; Rina Angraini
JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 3: November 2022
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v11n3.1074.2022

Abstract

Soil temperature and humidity are important factors in affecting the condition of agricultural sector, which has an impact on the quality and quantity of the production. Lack of information on the condition of agricultural soil is one of the causes in productivity deficiency in the process of agricultural cultivation. The application of technology in the field of agriculture is expected to be able to reduce various adverse effects of agricultural soil conditions. One of which is by periodic monitoring, such as the temperature and humidity of agricultural soil. This research aims to design LoRa technology to be used as a data transmission medium for monitoring soil temperature and humidity by applying a system that is based on the Blynk application, which will make the users easier to monitor the system remotely. The temperature sensor was able to acquire data with 98.37% accuracy and the soil humidity sensor was able to acquire data with 91.63% accuracy. The changes in LoRa transmission parameters for monitoring data have an effect on the quality of its performance. The experimental results with Bandwidth variation (BW) from 31.25 kHz, 62.50 kHz, 125 kHz, 250 kHz, and 500 kHz at a distance of 15m, the best SNR and RSSI values were obtained for BW 31.25 kHz with values of 5.42 dB and -104.90 dBm. Whereas, the best ToA is obtained with a BW of 500 kHz with a value of 27.50 ms. While, the experimental result with the variation of Coding Rate (CR) from CR 4/5, 4/6, 4/7, and 4/8 at a distance of 15m, the best SNR and RSSI values were obtained CR 4/8 with values of 4.10 dB and -106.40 dBm and he best ToA was obtained CR 4/5 with a value of 112.70 ms. In testing by using variation Spreading Factor (SF) from SF7, SF9, and SF12, the higher the SF value used, the wider the range of area data communication will be. Configuration SF7 and SF9 were only able to reach a distance of 25m, while SF12 was able to reach a distance of 35m.
The Effect of Using Array Technique on Semi-Circular Patch Microstrip Antenna with 2.4 GHz Frequency in Supporting Wireless Body Area Network Technology Baharuddin; Agung Bhaskara; Amirul Luthfi; Rina Angraini; Haniza Yazid
JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 3: November 2022
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v11n3.1075.2022

Abstract

This paper aims to design a semi-circular patch microstrip antenna that can work at a frequency of 2.4 GHz (band 2360 MHz - 2400 MHz) to support Wireless Body Area Network technology (WBAN). One of the devices connected to WBAN technology is a Holter monitor and medical data recorder that forms a medical network for post-operative or monitoring ICU patients (Intensive Care Unit). To support one of the WBAN technologies, an antenna is needed that has considerable gain and bandwidth characteristics. To increase the gain and bandwidth, the array method is used on antennas with inset feed unification. The antenna design was simulated using CST Studio Suite 2019. The use of array methods on microstrip antennas can increase the gain by 132.9%, which is 5.73 dB. The simulation results obtained a return loss of -17.223 dB with a bandwidth of 88.3 MHz in the frequency range of 2357.6 MHz - 2445.9 MHz
Optimization of Thermal Power Plant Operations Using Genetic Algorithms Sapto Nisworo; Hasibuan, Arnawan; Syafii, Syafii
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 3: November 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1090.2023

Abstract

Accurate scheduling of capacity and operating time for electricity generation is intended to be able to determine the start and end periods of electricity generation operations and produce power output that can meet load requirements. In this research, the goal to be achieved is to know the existence of power plants when to start operating and when to stop operations and to minimize operational costs by dividing the value of the power that will be generated at each power plant. Genetic algorithms are applied to thermal power plant data patterns to design a scheduling plan. The process involves combining the six power generating units to be tested into three different samples. It was found that the total power load and total cost for Sample 1 was 78,109 MW and IDR 200,285, 66.26, Sample 2 was 74,497 MW and IDR 149,774,156.41, and Sample 3 was 78,681 MW and IDR 156,297,893, respectively. 08. This shows that the cost of sample 1 compared to sample 2 decreased by 25.22%, then in sample 2 when compared to sample 3 it increased by 4.17%. The data also shows that a higher number of generations results in lower costs. Therefore, genetic algorithms produce better solutions from one generation to the next.

Page 56 of 61 | Total Record : 610

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