JURNAL NASIONAL TEKNIK ELEKTRO
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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<![CDATA[An Automatic Wind Turbine Braking System on PLTH Bayu Baru through a Fuzzy Logic Controller ]]>
<![CDATA[Tole Sutikno]]>;
<![CDATA[Syahid Hikmatul Wahid]]>;
<![CDATA[Rizky Ajie Aprilianto]]>;
<![CDATA[Arsyad Cahya Subrata]]>;
<![CDATA[Auzani Jidin]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.887.2022
<![CDATA[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.]]>
<![CDATA[Comparison of Classification for Grading Red Dragon Fruit (Hylocereus Costaricensis) ]]>
<![CDATA[Zilvanhisna Emka Fitri]]>;
<![CDATA[Ari Baskara]]>;
<![CDATA[Abdul Madjid]]>;
<![CDATA[Arizal Mujibtamala Nanda Imron]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.899.2022
<![CDATA[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%.]]>
<![CDATA[Infaq Sterilization Box with UV and Ozone (BIUZ) ]]>
<![CDATA[Arifin, Zaenal]]>;
<![CDATA[Tamamy, Aries Jehan]]>;
<![CDATA[Pamungkas, Hery]]>;
<![CDATA[Mayasari, Dita Ayu]]>;
<![CDATA[Heryanto, M Ary]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.937.2022
<![CDATA[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.]]>
<![CDATA[Automatic Feeder for Laying Hens Based on Noise Amplitude ]]>
<![CDATA[Rian Ferdian]]>;
<![CDATA[Zaki Minango Dasman]]>;
<![CDATA[Yan Heriyandi]]>;
<![CDATA[Mohammad Hafiz Hersyah]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.944.2022
<![CDATA[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.]]>
<![CDATA[Model Design of The Image Recognition of Lung CT Scan for COVID-19 Detection Using Artificial Neural Network ]]>
<![CDATA[Maulana Akbar Dwijaya]]>;
<![CDATA[Umar Ali Ahmad]]>;
<![CDATA[Rudi Purwo Wijayanto]]>;
<![CDATA[Ratna Astuti Nugrahaeni]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.984.2022
<![CDATA[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.]]>
<![CDATA[Techno-Economic Simulation of On-grid PV System at a New Grand Mosque in Bukittinggi using HOMER ]]>
<![CDATA[Pinto Anugrah]]>;
<![CDATA[Rizki Wahyu Pratama]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.985.2022
<![CDATA[Mosque is an important building for Muslims worldwide for doing religious activities, such as daily prayers, weekly discourses, and annual celebrations. In many places, mosques are considered appropriate buildings for rooftop solar photovoltaics (PV) installation. This study provides a techno-economic analysis of an on-grid PV system in a great mosque. As a case study, Masjid Tablighiyah Garegeh in Bukittinggi is chosen, which is currently under construction with an expected capacity of up to 1,400 people. This study uses HOMER software as a tool to assess optimum configuration for an on-grid PV system. There are four options that is considered in this study: PV-grid, PV-battery-grid, battery-grid, and grid only system . Optimization results showed that both configurations with PV have promising performance; however, an on-grid PV system without battery system is the most optimum configuration. A 40 kWp PV equipped with a 27 kW converter has the least net present cost with USD 6,902, while the cost of energy when implementing the system is only about USD 4.8 cent per kWh. By implementing the system, 57.2 MWh of electricity will be produced from the PV.]]>
<![CDATA[Classification Of Alcohol Type Using Gas Sensor And K-Nearest Neighbor ]]>
<![CDATA[Munaf Ismail]]>;
<![CDATA[Sri Arttini Dwi Prasetyowati]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.989.2022
<![CDATA[Ethanol, isopropyl and methanol belong to the same alcohol group. The latter is commonly used as an industrial solvent, not for personal consumption. Many traditional alcoholic drink sellers often mix alcoholic beverages, which are commonly called as “oplosan”, this mixed drink is very dangerous for human if it contains methanol. Based on this problem, it is necessary to make a measuring device for the alcohol content in the liquid to classify the alcohol type. The design of this gas sensor-based alcohol classification system and method consists of a series of hardware and software applications. The block diagram of the alcohol classification system measures the ethanol and methanol substances in each alcoholic drink using the MQ3 gas sensor and WeMos as a data acquisition device and microcontroller. The computer was used to process the acquisition data from the gas sensor being used then calculates the K-Nearest Neighbor (K-NN) to obtain the prediction results. The K-NN system testing consists of testing the effect of the K value and testing its accuracy. The result of testing the effect of the K value produces 100% optimum accuracy at the values namely K=1, K=3, K=5, K=10 and 55% on K=20.]]>
<![CDATA[Load Forecasting in the Context of Global Covid-19 Vaccination Using Facebook Prophet ]]>
<![CDATA[Barevan, Kevinaldo]]>;
<![CDATA[Halim, Abdul]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.992.2022
<![CDATA[Forecasting the electrical energy load is a very important initial stage in the operation of the electricity system so that the system works reliably, stably, and economically. The load forecasting process is carried out in the range of hours to years. This study focuses on short-term load forecasting (STLF) where in general the effects of weather conditions and human activities are very influential. In this study, we will study further the effects of the Covid-19 pandemic, namely the number of vaccines and the level of community mobility on changes in electrical loads. The study of the effect of the vaccine is the new point of this research. In electrical load forecasting, the revised Facebook Prophet method will be used. This revision is intended so that the effects of the pandemic can be included in the model. To test the effectiveness of the proposed model, a case study of the Pennsylvania electrical load data was carried out. In 2021 with the addition of the vaccination variable, the MAPE value is 15.26%. The amount of data used could possibly affect the forecasting process and MAPE results. So, the MAPE value is quite good when compared to other studies.]]>
<![CDATA[Feasibility Analysis of Distributed Power Control System for Cognitive Radio Networks ]]>
<![CDATA[Anggun Fitrian Isnawati]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.994.2022
<![CDATA[The need for an efficient transmit power is affected by the condition of user and power control methods used. User conditions that categorized in cognitive femtocell networks included in the category as distributed user, so it required a distributed power control (DPC). To be implemented in cognitive radio network (CRN) communication, the system must be feasible. The problem raised in this research regarding the feasibility of implementing the DPC system on the CR network To meet the feasible requirements, it is necessary to test the system's feasibility through testing the eigenvalues of the link gain matrix obtained and testing the non-negative power vector conditions. In this study, experiments were carried out on 2 schemes of the number of users, namely the scheme of 5 users and 10 users, to determine the power requirements of each user according to the channel distribution. The results obtained for both schemes show that the total eigenvalue of the link gain matrix for all channels is less than 1 and all users meet the non-negative power vector requirements. So it can be concluded that those two schemes are feasible to implement a distributed power control system. Furthermore, as more users use the channel and the closer the distance between users, the more power is consumed due to high interference, necessitating high power compensation in order to maintain the target of signal to interference and noise ratio (SINR).]]>
<![CDATA[Real-Time Accident Detection Using KNN Algorithm to Support IoT-based Smart City ]]>
<![CDATA[Khodijah Amiroh]]>;
<![CDATA[Bernadus Anggo Seno Aji]]>;
<![CDATA[Farah Zakiyah Rahmanti]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v11n1.999.2022
<![CDATA[Surabaya is a city with an area of 326.81 km2 and is the center of land transportation in the eastern part of Java Island. The construction of digital infrastructure in the Surabaya area will make it easier for the City Government to make efficient services. Traffic accidents that occurred in Surabaya until 2017 recorded 1,365 incidents. EVAN (Emergency Vehicle Automatic Notification) is a research topic that focuses on the field of transportation, especially in real-time traffic accidents which can be integrated with city information centers and hospitals for primary assistance in accidents. The purpose of this research is to make it easier for the Surabaya city government to provide first aid in the event of an accident. The design of the device on the user side is made using the Arduino, the accelerometer sensor and the gyroscope in the form of the MPU6050 sensor and the u-blox gps module. Crash detection on the system using the k-Nearest neighbors algorithm (KNN). On the operator side, the design is done on a web basis by utilizing the ReactJs framework which is integrated with the Google Maps APIs. The results of the accuracy of the accident detection system reached 97% and the detection of accident locations and the nearest hospital from the location reached 100%. Thus, real-time accident detection can be implemented in Surabaya city to support the smart city.]]>
