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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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The Effect of Electricity Supply Interruptions on Small Business Productivity in West Sumatra Hamid, Muhammad Imran; Sulfandri; Afifah
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.v12n3.1092.2023

Abstract

This research examines the impact of interruptions in electricity supply on the production of small and medium enterprises in West Sumatra from 2014 to 2021. The data used in the research was obtained from the Ministry of Trade and Industry of West Sumatra, including the production variables, employment, investment, and other variables that influence the production activities. A regression equation connecting production factors and production levels is formulated. Furthermore, another regression equation is also formulated by considering the electricity interruption factor, namely the SAIDI index on production levels. The effect of electrical power interruptions is then evaluated by comparing the two equations. The research results show that the most significant production loss occurred in 2019, 16.07 hours/year, while the most negligible loss occurred in 2015, 6.53 hours/year. Trend data collected during the research period regarding loss conditions and interruption parameters shows that electricity disturbances do not have a linear impact on production losses. The research also shows that electric power does not significantly impact the production activities of small and medium enterprises in West Sumatra.
Performance Process of Coil Winding Machine Based on Accuracy and Speed for Water Pump Motor Ilahi, Novita Asma; Musyafiq, Afrizal Abdi; Purwiyanto; Rahmat, Saepul; Prima Dewi, Riyani; Purnata, Hendi
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.v12n3.1101.2023

Abstract

A coil winding machine for water pumps using a monitoring system is a development of conventional winding tools. In regular coil winding tools, the coil winding process is done manually by rotating the handle as many times as the desired number of turns. The conventional winding tools have problems consisting of inconsistent working speed and operator-dependent winding continuity. Undesirable windings can occur with conventional winding tools, and the winding process requires close supervision. Therefore, the automatic coil winding machine was developed to optimize the coil winding process. The machine utilizes a DC motor to rotate the coil rolls, replacing the conventional roller handle function. This machining method uses an optocoupler sensor. The sensor serves to identify and evaluate the rotation of the roller. In addition, the ATmega8 microcontroller was applied to develop a system that can work automatically. Data collection involves varying the number of wire turns and the wire diameter dimension. The variation is necessary because the number of windings and wire diameter affect pump efficiency and performance. The data testing showed a machine accuracy rate of 98%, with a maximum difference of 1 coil winding in the results. This data confirms that the coil winding machine meets the tool's accuracy standards.
Studi Autoencoder Deep Learning pada Sinyal EKG Mochamad Reza, Dandi; Satria Mandala; Zaki, Salim M.; Ming, Eileen Su Lee
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.v12n3.1117.2023

Abstract

Arrhythmia refers to an irregular heart rhythm resulting from disruptions in the heart's electrical activity. To identify arrhythmias, an electrocardiogram (ECG) is commonly employed, as it can record the heart's electrical signals. However, ECGs may encounter interference from sources like electromagnetic waves and electrode motion. Several researchers have investigated the denoising of electrocardiogram signals for arrhythmia detection using deep autoencoder models. Unfortunately, these studies have yielded suboptimal results, indicated by low Signal-to-Noise Ratio (SNR) values and relatively large Root Mean Square Error (RMSE). This study addresses these limitations by proposing the utilization of a Deep LSTM Autoencoder to effectively denoise ECG signals for arrhythmia detection. The model's denoising performance is evaluated based on achieved SNR and RMSE values. The results of the denoising evaluations using the Deep LSTM Autoencoder on the AFDB dataset show SNR and RMSE values of 56.16 and 0.00037, respectively. Meanwhile, for the MITDB dataset, the corresponding values are 65.22 and 0.00018. These findings demonstrate significant improvement compared to previous research. However, it's important to note a limitation in this study—the restricted availability of arrhythmia datasets from MITDB and AFDB. Future researchers are encouraged to explore and acquire a more extensive collection of arrhythmia data to further enhance denoising performance.
Solar Panel Efficiency Improvement through Dual-Axis Solar Tracking with Fuzzy Logic and Water Treatment Techniques Halim, Levin; Gun, Sin Euy; Wahab, Faisal
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.v12n3.1120.2023

Abstract

Indonesia's heavy reliance on non-renewable energy sources, such as fossil fuels and other resources obtained from mining, poses sustainability challenges. Solar panels, which are environmentally friendly and renewable energy alternatives, are designed to convert solar energy into electricity, and they have shown room for improvement in their efficiency. One method to enhance its efficiency is the utilization of dual-axis solar tracking, employing linear actuators for control over both horizontal and vertical panel movements. In addition, solar panels frequently experience efficiency losses as a result of high working temperatures when exposed to sunlight. The use of water treatment techniques may help address this problem. In this research, the two-axis solar tracking approach with water treatment methods were combined to achieve greater efficiency and boost energy production. A notable increase in solar panel efficiency was seen subsequent to the design, implementation, and testing of the proposed system, resulting in a notable rise in power output. Combining the two-axis solar tracking approach with water treatment methods produced solar panels with a 7.46% efficiency and a 17.77% power increment. Dual-axis solar tracking and combined with water treatment could significantly increase solar panel efficiency, which will ultimately lead to environtmentally clean renewable energy production increment.
Klasifikasi Multikelas Infark Miokard Berdasarkan Sinyal Phonokardiogram dengan Ensemble Learning Nia Madu Marliana; Satria Mandala; Hau, Yuan Wen; Yafooz, Wael M.S.
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.v12n3.1121.2023

Abstract

Myocardial infarction (MI) is a serious cardiovascular disease with a high mortality rate worldwide. Early detection and consistent treatment can significantly reduce mortality from cardiovascular diseases. However, there is a need for efficient models that can enable the early detection of heart disease without relying on trained clinical experts. MI studies using phonocardiogram (PCG) signals and implementing ensemble learning models are still relatively scarce, often resulting in poor accuracy and low detection rates. This study aims to implement an ensemble learning model for the classification of MI using PCG signals into different classes. In this stage of research, several classification algorithms, including Random Forest and Logistic Regression, serve as basic models for ensemble learning, utilizing features extracted from audio signals. Evaluation of the model's performance reveals that the stacking model achieves an accuracy of 96%. These results demonstrate that our system can appropriately and accurately classify MI within PCG data. We believe that the findings of this study will enhance the diagnosis and treatment of heart attacks, making them more effective and accurate.
Electromedical Device And Expert System for Early Detection of Hyperemesis Gravidarum Fitrilina, Fitrilina; Ganesha; Handayani, Yanolanda Suzantry; Surapati, Alex; Untari, Rahayu Trisetyowati; Laksono, Heru Dibyo; Latif, Melda
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.v12n3.1130.2023

Abstract

Hyperemesis Gravidarum (HG) is a pregnancy complication that is often overlooked as it is typically considered normal. If HG is not properly treated, nutrition will not be fulfilled which can negatively affect maternal and fetal health and even maternal and fetal death. The exact cause of HG is not identified, so there are no effective preventive methods. However early detection can help for prompt and appropriate treatment. Therefore, a monitoring system for pregnancy conditions was designed for HG early detection. This system employs the MPX5050 DP pressure sensor for measuring blood pressure, the MAX30100 for assessing maternal heart rate and oxygen saturation, the MAX4466 sensor for monitoring fetal heart rate, and an expert system using the certainty factor method to diagnose the probability of hyperemesis gravidarum. The expert system achieves an accuracy of 93.33%. In comparison to the aneroid sphygmomanometer, the designed sphygmomanometer reveals a mean difference of 3.5 mmHg for diastolic pressure, with a standard deviation below 8 mmHg for both systolic and diastolic pressures. The measurement of heart rate and oxygen saturation has a deviation of 1.8 % and 1.02 % respectively. These deviations align with the standards specified by the Ministry of Health for medical devices. For the fetal heart rate, the mean deviation is 3.4 bpm, and the measurement error is 2.38%. Thus, this system can be utilized to monitor pregnancy conditions, enabling the early detection of hyperemesis gravidarum
Shrimp Pond Monitoring System using Cooperative Wireless Sensor Network Multi-Hop Technique based on Internet of Things Zickri, Zickri; Novandri, Andri; Adriman, Ramzi; Nasaruddin
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.v12n3.1133.2023

Abstract

Water quality is a crucial factor in maintaining the survival and growth of shrimp. Manual water quality monitoring in shrimp ponds is no longer effective due to the need for periodic monitoring to maintain stable water quality. Therefore, online monitoring using various sensors installed in each pond is necessary. However, there are several challenges to overcome, such as the large expanse of the shrimp ponds, which may lead to data loss due to signal disruptions, and limited energy to power the sensors. To address these issues, this paper proposes the cooperative Wireless Sensor Network (WSN) technique with a multi-hop method for communication in the monitoring process. The system consists of five sensor nodes: temperature sensor, pH sensor, water level sensor, intake water flow sensor, and drain water flow sensor. The cooperative WSN multi-hop technique helps reduce energy consumption in the sensor nodes during measurement and data transmission, while also preventing data packet loss. This is achieved through the use of relay nodes that strengthen signals and forward data to the sink node. As a result, the battery life is extended, and energy usage in the monitoring process can be optimized. The system enables real-time online monitoring and can be accessed through a smartphone application. The results of this study show that the total energy consumption for data transmission in the sensor nodes is 9.64 J, while the total energy consumption for data forwarding in the relay nodes is 9.15 J. The total energy consumption in the transmit and receive processes is 18.79 J or 5.2 mWh. Therefore, it can be concluded that the energy savings of the proposed system is 4.3 mWh or approximately 45%, and is more efficient than the previous system.
Comparing MPPT Algorithms for Improved Partial-Shaded PV Power Generations Basalamah, Abdullah; Pakka, Hariani; Eren, Halit; Alghamdi , Ahmed Saed; Syarifuddin, Andi; Kamil, Kusno; Salmiah; Hartono, Sriwijanaka Yudi
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.v12n3.1134.2023

Abstract

olar energy, accepted as an alternative energy source, is attracting commercial interest and scholars and researchers for improving efficiency and lowering the losses within the system. One of these significant losses is due to partial and complex shading. This study concentrates on reducing losses to enhance the efficiency of solar systems. Maximum Power Point Tracking (MPTT) uses several alternative algorithms for efficient operations. We have selected four algorithms supporting MPPT, namely P&O, PSO, Adaptive cuckoo, and Dragonfly. These algorithms are applied on photovoltaic (PV) systems in four different scenarios: uniform irradiance, partial shading, complex partial shading, and multiple local maximum power points. According to this study, results show that the algorithms' performance vary significantly based on these scenarios. It has been shown that PSO has the longest tracking time compared to other but tracks the maximum power best when exposed to uniform irradiance. In contrast, DFO takes the shortest tracking time and performs best in I-V curves but do not have a maximum power point at the knee. Both adaptive cuckoo and PSO perform well in tracking the global maximum power point, particularly in partial shadings. The study provides insights into the strengths and weaknesses of each algorithm in different scenarios and can guide the selection of an appropriate algorithm for a given PV system.
Bahasa Inggris Wahyuni, Elvira Sukma; Alvita Widya Kustiawan Putri; Nisa Agustin Pratiwi Pelu; Firdaus; Idha Arfianti Wiraagni
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 1: March 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n1.1148.2024

Abstract

Wounds result from physical violence that damages the continuity of body tissues and are frequently observed in forensic medicine and medicolegal science. In forensic medicine and medicolegal science, wounds play a significant role in creating a medicolegal examination and report (VeR) for deceased individuals and living victims. However, research findings indicate that the quality of clinical forensic descriptive results in VeR needs to improve in several hospitals in Indonesia. Meanwhile, high-quality VeR results are crucial in determining penalties for perpetrators in court, and poor VeR results can hinder the legal process. The application of information technology in medicine has yielded numerous tools that can assist experts in carrying out their duties. Likewise, clinical forensics, a generally conservative forensic pathology practice, can be enhanced through image-processing techniques and machine learning. Digital technology support for forensic cases has been available previously, such as in forensic photography; however, its application still needs improvement, and further development is required. This study applied a Yolo V4-based machine learning and image processing algorithm to classify and detect types of wounds. This algorithm was chosen for its high speed and accuracy in classification and detection tasks. The research results showed that the learning model's performance, measured in accuracy, precision, recall, and average F1 score, reached 92%. Usability testing showed that the system performed well and could be helpful with minor improvements.
Development of DC Motor Speed Control Using PID Based on Arduino and Matlab For Laboratory Trainer Supriyono, Heru; Alanro, Fedrik Fajar; Supardi, Agus
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 1: March 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n1.1155.2024

Abstract

DC motors are widely used as propulsions, including in electric bicycles. The problem faced by students in the DC motor control laboratory working using software simulation is that they do not have practical learning experience using digital instruments. This article aims to develop a DC motor speed control that can be used to learn practical Proportional Integral Derivative (PID) control in the laboratory. The DC motor speed control was developed using a combination of Arduino UNO microcontroller and Matlab software. The PID method was used because it is still broadly studied and applied in industries. The test results showed that the developed trainer can work well with PID variable values that can be entered via the keypad, and DC motor transient responses can be displayed in Matlab. From the experimental results, it was found that the optimal PID variable values were Kp=0.04, Ki=0.05, and Kd=0.004, where the controller produced a low overshoot value, i.e., 0.73% of its set point and a settling time of 10.66 seconds. The test results of using the developed trainer in the Fundamental of Control Engineering laboratory work showed that the developed trainer gave students practical learning experience in designing PID control for DC motor speed by using digital equipment, i.e., microcontroller and actual DC motor as well as analyzing its corresponding transient response in Matlab software environment

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