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INDONESIA
JURNAL NASIONAL TEKNIK ELEKTRO
Published by Universitas Andalas
ISSN : 23022949     EISSN : 24077267     DOI : -
Core Subject : 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.
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Articles 610 Documents
Intelligent System for Fall Prediction Based on Accelerometer and Gyroscope of Fatal Injury in Geriatric Amiroh, Khodijah; Rahmawati, Dewi; Wicaksono, Ardian Yusuf
JURNAL NASIONAL TEKNIK ELEKTRO Vol 10, No 3: November 2021
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (373.135 KB) | DOI: 10.25077/jnte.v10n3.936.2021

Abstract

Methods of prevention and equipment to reduce the risk of falls based on accelerometer and gyroscope sensor have developed rapidly because its operations are cheaper than video cameras. Improved accuracy of detection and fall prediction based on accelerometer and gyroscope sensor is carried out by utilizing Artificial Intelligence (AI) to predict falling patterns. However, the existing fall prediction system is less responsive and also has a low level of accuracy, sensitivity and specificity. The current system does not have a notification system to care givers or doctors in the hospital. To overcome the above problems, this study proposes the development of smart fall prediction system based on accelerometer and gyroscope for the prevention of fractures in geriatric populations (JaPiGi) which are accurate and have high sensitivity and specificity. This study uses Fuzzy Mamdani to recognize movements falling forward, falling sideways, sitting, sleeping, squatting and praying. The total data tested was 100 data from 10 participants. The introduction of this movement is based on 6 input variables from data of accelerometer and gyroscope sensor. To calculate the accuracy, precision, sensitivity and specificity in this study using the equation Receiver Operating Characteristic (ROC). Motion recognition is carried out 3 times with an average accuracy of 90%.
Calculate The Conductivity of Some Composites of Cellulose Bacteria Mixed with Polypyrol Yunus, Syukri; Abrar, Hairul; Akbar, Auliya
JURNAL NASIONAL TEKNIK ELEKTRO Vol 10, No 3: November 2021
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (361.891 KB) | DOI: 10.25077/jnte.v10n3.927.2021

Abstract

The manufacture of composites that have good electrical properties is to use a conductive polymer matrix. A conductive polymer is a polymer compound that has a stable bond that allows the polymer to act as a good conductor of electricity. This study aims to determine the highest conductivity value of composite materials that have been coated with polypyrrole, namely bacterial cellulose with polypyrrole (bio composite 1), tempo bacteria cellulose with polypyrrole (bio composite 2), and Gambier bacteria cellulose with polypyrrole (bio composite 3). In this study, there were four samples consisting of nata de coco (cellulosic bacteria), 2, 2, 6, 6-tetramethylpiperidine 1-oxyl (TEMPO), Gambier extract, and polypyrrole. Measurement of resistance value using the two point probe method. The results of this study obtained that the resistance and conductivity values of bio composite 1,  bio composite 2, and bio composite 3 were 29.742 kΩ and 1.178×10-3 S/cm, 20.338 kΩ and 1.692×10-3 S/cm, 34,572 kΩ and 0.9807×10-3 S/cm. The measurement results show that the highest conductivity value is bio composite 2.
Online Tuning Diagnosis of Proportional Integral Derivative Controller based on IEC 61499 Function Blocks Nindyasari, Florentina Vela; Wardana, Awang Noor Indra; Arif, Agus
JURNAL NASIONAL TEKNIK ELEKTRO Vol 10, No 3: November 2021
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (425.741 KB) | DOI: 10.25077/jnte.v10n3.940.2021

Abstract

Controller performance is a crucial aspect of industrial processes; hence, it is critical to maintaining optimal controller performance conditions. Bad controller performance can be caused by poor proportional integral derivative (PID) controller tuning those results in aggressive and sluggish controllers’ behavior. Correct diagnosis of poor controller tuning becomes vital so that it can adequately handle the controller. This study designs several function blocks for online diagnosis of poor PID controller tuning based on the IEC 61499 standard. The design of the function blocks began with design the method used for diagnosing a poor controller tuning. The procedure was based on autocorrelation function (ACF), comparison of signal to noise ratio (SNR) estimation, and idle index. The function blocks were validated with first order plus delay time (FOPDT) processes, which had aggressive, sluggish, or well-tuned behavior. The function blocks were implemented on a Fluid Catalytic Cracking (FCC) plant and industrial data with various process faults to evaluate its capability to diagnose a poor controller tuning. The developed function block can precisely analyze a poor controller tuning on FCC plant and 8 of 10 industrial data. It showed that the function blocks could diagnose a poor controller tuning correctly if the oscillation were regular.
Electrocardiogram Abnormal Classification Based on Abnormality Signal Feature Purnama, Sevia Indah; Afandi, Mas Aly
JURNAL NASIONAL TEKNIK ELEKTRO Vol 10, No 3: November 2021
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (984.315 KB) | DOI: 10.25077/jnte.v10n3.829.2021

Abstract

Heart rate abnormalities can lead to many cardiovascular diseases such as heart arrythmia, heart failure, heart valve disease and many more. Some cardiovascular disease can cause death. Abnormalities signal feature can be seen using electrocardiogram. Electrocardiogram is an electric signal record from heart activity. Normal heart and abnormal heart have a different electrocardiogram signal pattern. This research is aim to detect abnormality from heart rate using electrocardiogram abnormality signal feature.  Abnormality signal pattern can be used to classify normal and abnormal heart rate. Abnormality feature consists of P signal condition, R signal condition, P – R interval rate, and double R interval. Electrocardiogram data that used in this study is obtain from MIT-BIH Arrythmia database. 20 electrocardiogram data have been used to see detection and classification performance while classifying normal and abnormal heart rate. Research result shows that feature based has 90.00% in accuracy, 90.00%in precision, and 90.00% in sensitivity while classify normal and abnormal heart rate. Research result can conclude that abnormality feature can be used to classify normal and abnormal heart rate. This method can be used for embedded system device that has limitation in memory and size.
Microcontroller-based Artificial Lighting to Help Growth the Seedling Pakcoy Afandi, Mas Aly; Hikmah, Irmayatul; Agustinah, Chandra
JURNAL NASIONAL TEKNIK ELEKTRO Vol 10, No 3: November 2021
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (481.061 KB) | DOI: 10.25077/jnte.v10n3.943.2021

Abstract

Improving efficiency and quality in farming activities is important reason of developing technology to support agriculture. Technology in agriculture such as image processing, Internet of Things (IoT), Artificial Intelligence, Big Data, and Artificial Lighting gives increasing trends. Artificial lighting technology has high impact to support agriculture in an area that has low sun light intensity such as in rainy season. Farmer has a difficulty to cultivating plant especially in early stage in rainy season. This problem happen because of the intensity of sun light is very minimum. Artificial lighting is a technology to solve early stage cultivating problem in rainy season. This technology can support agriculture for cultivating plant with minimum sun light. Artificial lighting contains light emitting diode (LED) that is laid out as an array. This research goal is to make an artificial lighting prototype to support early stage cultivating. Pakcoy is a plant that used to observe artificial lighting impact for early stage Pakcoy cultivation. This research shows Pakcoy plant placed in the prototype gives significant growth compared with a plant which placed in low light room. Pakcoy plant in artificial lighting gives 2 – 4 leaves, the height is 1.5 – 5cm, and from 18 seeds 10 is grow. This research can conclude that artificial lighting prototype can support early stage Pakcoy cultivation.
An Automatic Wind Turbine Braking System on PLTH Bayu Baru through a Fuzzy Logic Controller Tole Sutikno; Syahid Hikmatul Wahid; Rizky Ajie Aprilianto; Arsyad Cahya Subrata; Auzani Jidin
JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (505.447 KB) | DOI: 10.25077/jnte.v11n1.887.2022

Abstract

PLTH Bayu Baru is one of the hybrid power plants (HPP) located in Baru beach, Pandansimo, Bantul, Yogyakarta, Indonesia. It generates electrical energy from two sources, wind and solar energy. However, a problem is encountered regarding wind turbine mechanics due to using a manual switch for braking during periods of excessive wind speed. This study proposes an automatic wind turbine braking system through a utilized fuzzy logic controller (FLC) for the PLTH Bayu Baru application. The Mamdani type FLC without complex mathematical models is applied to the Arduino Uno development board to realize the proposed systems. The error (Error_V) and delta error (dError_V) values from the generator voltage sensor become the input of the proposed systems, while the pulse width modulation (PWM) becomes the output for controlling the on/off period of the MOSFET as switching devices. The proposed systems have been tested on a micro-scale wind turbine with PMSG 12V/400W type. From the testing results, the proposed system successfully braked automatically at the point wherein the generator voltage exceeds the setpoint value. Also, the proposed system keeps the generator voltage less than 13.8V, so the problem caused by excessive speed can be resolved.
Comparison of Classification for Grading Red Dragon Fruit (Hylocereus Costaricensis) Zilvanhisna Emka Fitri; Ari Baskara; Abdul Madjid; Arizal Mujibtamala Nanda Imron
JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (517.489 KB) | DOI: 10.25077/jnte.v11n1.899.2022

Abstract

Pitaya is another name for dragon fruit which is currently a popular fruit, especially in Indonesia. One of the problems related to determining the quality of dragon fruit is the postharvest sorting and grading process. In general, farmers determine the grading system by measuring the weight or just looking at the size of the fruit, of course, this raises differences in grading perceptions so that it is not by SNI. This research is a development of previous research, but we changed the type of dragon fruit from white dragon fruit (Hylocereus undatus) to red dragon fruit (Hylocereus costaricensis). We also adapted the image processing and classification methods in previous studies and then compared them with other classification methods. The number of images in the training data is 216, and the number of images in the testing data is 75. The comparison of the accuracy of the three classification methods is 84% for the KNN method, 85.33% for the Naive Bayes method, and 86.67% for the Backpropagation method. So that the backpropagation method is the best classification method in classifying the quality grading of red dragon fruit. The network architecture used is 4, 8, 3 with a learning rate of 0.3 so that the training accuracy is 98.61% and the testing accuracy is 86.67%.
Infaq Sterilization Box with UV and Ozone (BIUZ) Arifin, Zaenal; Tamamy, Aries Jehan; Pamungkas, Hery; Mayasari, Dita Ayu; Heryanto, M Ary
JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (421.797 KB) | DOI: 10.25077/jnte.v11n1.937.2022

Abstract

The COVID-19 pandemic that has occurred to date has resulted in the loss of many lives. This is due to the ease with which the COVID-19 virus spreads. According to the latest research published by the WHO, the virus can spread through the medium of objects, one of the easies object to spread virus is money. The spread of the COVID-19 virus can be done through money transactions that have previously been used by people infected by the virus. This is because COVID-19 virus can survive for more than 72 hours. To prevent this, it is necessary to sterilize so that the virus in the money can be neutralized. The technology that can be used for disinfection in this tool is Ultra Violet (UV) light and Ozone Generator. Many studies have shown that UV rays and ozone gas (O3) are able to kill viruses that are on the surface of objects. The ability of UV rays and ozone gas (O3) can kill viruses in money because UV rays and ozone gas (O3) have radiation that is quite harsh, so that if exposed to human skin continuously it can cause damage to skin tissue. In this study, to overcome this problem, a device that is automatically able to carry out the disinfection process in the room is made by utilizing UV light. Infaq Sterilization Box with UV and Ozone (BIUZ) can kill viruses in money, it is also easy to operate and safe. The size of the tool made is adjusted to the object or partner of the research activity, namely the Central Java Great Mosque Manager (PP MAJT). The need for partners is that the tool is able to carry out the sterilization process of infaq money provided by the congregation, both in the form of paper and coins effectively.
Automatic Feeder for Laying Hens Based on Noise Amplitude Rian Ferdian; Zaki Minango Dasman; Yan Heriyandi; Mohammad Hafiz Hersyah
JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (383.102 KB) | DOI: 10.25077/jnte.v11n1.944.2022

Abstract

Food is an essential aspect of the laying hens' cultivation process. The delay of the feeding time and the short amount of food can cause stress to the hens. Furthermore, an excessive amount of food can cause overweight and reduce hens' productivity. This paper provides a method to automate the feeder for laying hens using a device based on microcontroller technology. A tool that can detect chicken behavior when hungry and the temperature of the cage can provide an excellent feeding management system for the breeder. The automatic feeder can see chicken behavior, also the environmental condition around the cage. A specific noise amplitude caused by the hungry hens can trigger the feeder.  This feeder also design aims to provide the food in the right amount at the right time. Thus, the breeder can minimize the stress of laying hens, reduce food waste, and keep the hens ideal. Here the system can save the chicken’s food around 13.76% more efficient.
Model Design of The Image Recognition of Lung CT Scan for COVID-19 Detection Using Artificial Neural Network Maulana Akbar Dwijaya; Umar Ali Ahmad; Rudi Purwo Wijayanto; Ratna Astuti Nugrahaeni
JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (727.224 KB) | DOI: 10.25077/jnte.v11n1.984.2022

Abstract

COVID-19 has become a pandemic and is a big problem that needs to be checked out immediately. CT scan images can explain the lung conditions of COVID-19 patients and have the potential to be a clinical diagnostic tool. In this research, we classify COVID-19 by recognizing images on a computer tomography scan (CT scan) of the lungs using digital image processing and GLCM feature extraction techniques to obtain grayscale level values in CT images, followed by the creation of an artificial neural network model. So that the model can classify CT scan images, the results in this research obtained the most optimal model for COVID-19 classification performance with 90% accuracy, 88% precision, 91% recall, and 90% F1 score. This research can be a useful tool for clinical practitioners and radiologists to assist them in the diagnosis, quantification, and follow-up of COVID-19 cases.