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Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)
Published by Universitas Ahmad Dahlan
ISSN : 23383070     EISSN : 23383062     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
JITEKI (Jurnal Ilmiah Teknik Elektro Komputer dan Informatika) is a peer-reviewed, scientific journal published by Universitas Ahmad Dahlan (UAD) in collaboration with Institute of Advanced Engineering and Science (IAES). The aim of this journal scope is 1) Control and Automation, 2) Electrical (power), 3) Signal Processing, 4) Computing and Informatics, generally or on specific issues, etc.
Arjuna Subject : -
Articles 17 Documents
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Search results for , issue "Vol 7, No 2 (2021): August" : 17 Documents clear
Realtime IoT based Harmonics Monitoring System Review with Potential Low-Cost Devices with Experimental Case Study Purnomo Purnomo; Aripriharta Aripriharta; Anik Nur Handayani; Rini Nur Hasanah; Norzanah Rosmin; Gwo-Jiun Horng
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21166

Abstract

This paper presents a harmonic analyzer that used IoT and smart apps for low-cost and portable solutions. We contribute a short review of harmonics measurement methods and experimental approaches for monitoring harmonics using an IoT-based system. The proposed device was built from a current sensor, a voltage sensor, and a microcontroller with an IoT transmitter which is integrated with Matlab© cloud and smart apps (android). In specific, we experimented with testing and validated our proposal using the standard instrument under a fair treatment. The measurement scenario was taken on the point of comment coupling in the building campus for 5 to 10 minutes of each comparable instrument. Based on experimental results, the proposed device could monitor the harmonics profile drawn by the loads in the building campus. The trade-off between cost and performance is founded as the truth that it takes about 1 minute to update the harmonics data. Furthermore, the average error of THDV is 5.7%, and THDI is 4.7% which is higher than the expensive instrument. These values are acceptable based on IEEE standards.  Besides, it could monitor harmonics in real-time through an android application which is easy to use and portable. In addition, the cost of making the proposed device is cheap compared to the price of the standard instruments in the market.
Analysis of Random Forest, Multiple Regression, and Backpropagation Methods in Predicting Apartment Price Index in Indonesia I NYM Yoga Saputra; Siti Saadah; Prasti Eko Yunanto
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.20997

Abstract

This study focuses on predicting the apartment price index in Indonesia using property survey data from Bank Indonesia. In the era of the Covid-19 pandemic, accurately predicting the sale and purchase price of apartments is essential to minimize the impact of losses, thus making apartment prices attractive to predict. The machine learning approach used to predict the apartment price index are the Random Forest method, the Multiple Regression method, and the Backpropagation method. This study aims to determine which method is more effective in predicting small amounts of data accuracy. The data used is apartment price index data from 2012 to 2019 in the JABODEBEK area. The research will produce prediction accuracy that will determine the effectiveness of the application of the method. The Random Forest method with parameters n_estimators=100 and max_features=”log2” produces an R2 accuracy of 0.977. The Multiple Regression method with a correlation between the selling price and rental price variables is 0.746, and the rental inflation variable is 0.042 produces an R2 accuracy of 0.559. The Backpropagation method with a 1000-4000-1 hidden scheme and 20000 iterations produces an R2 accuracy of 0.996. Therefore, the Backpropagation method is more suitable in this study compared to the other two methods. The Backpropagation method is suitable because it gets almost perfect accuracy, so this method will minimize losses in investing in buying and selling apartments in the Covid-19 pandemic era.
Performance Comparison Modeling Between Single-phase Cycloconverters and Three-phase Cycloconverters Using Matlab Simulink Tools Setiyono Setiyono; Bambang Dwinanto
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.20225

Abstract

This paper presents a performance comparison of a single-phase AC to AC converter (cycloconverter) and a three-phase converter circuit which divides the input wave frequency (fin) into a variable frequency with the frequency value of the AC output voltage waveform (alternating current) (f, fin/2, fin/3, fin/4, fin/5, fin/6, fin/7, fin/8, fin/9, fin/10. Cycloconvertor switches are built using a diode and a thyristor device. This research was conducted by modeling each cycloconverter circuit using Matlab Simulink tools. Modeling simulation parameters to be analyzed include the output waveform RMS (root mean square) value, frequency value, and Total Harmonic Distortion (THD) index for each wave. The output frequency voltage waveform of cycloconverter is affected by the variation of the trigger signal of the P-side (positive) converter and the N (negative) converter side switch. Simulation results show that adjusting the firing pulse width of the P converter and the N converter will produce an output voltage wave that has an index value of THD, Vrms, and form factor for each diode and thyristor cycloconverter circuit.
Development of Laboratory Equipment Inventory System Using Radio Frequency and Internet of Things Mochamad Fajar Wicaksono; Syahrul Syahrul; Myrna Dwi Rahmatya
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21114

Abstract

The purpose of this research is to create a laboratory equipment inventory system. With this system, users, namely lecturers, lab assistants, and final project students, can find out the borrower's data, borrowing time, return time, and the tool availability status. The research method used is experimental. This system is based on IoT technology. The main brain from the hardware side uses the NodeMCU ESP8266. NodeMCU, apart from being a controller, can also function as a WiFi module. On the server-side, PHP and MySQL are used. When the user wants to borrow a tool, the user can use an RFID tag to open the cupboard. Furthermore, the NodeMCU will continue to scan for the presence of items in the cupboard using a radio frequency with RF433MHz. This information is sent to the server when the cupboard is closed and locked automatically. The server will receive the information and decipher the information. As a result, the testing process in this study proved that the system has been able to detect the presence of items in the cupboard and track anyone who borrows laboratory equipment with a 100% success percentage.
The Impact of Blockchain Technology in Higher Education Quality Improvement Riya Widayanti; Eka Purnama Harahap; Ninda Lutfiani; Fitra Putri Oganda; Ita Sari Perbina Manik
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.20677

Abstract

The times have made technology increasingly developed that there are innovations as new media to make it easier for humans in everyday life. Blockchain technology is an innovation that has been applied in various fields such as education, health, economy, and other areas. In this study, researchers want to see the impact that blockchain technology has had on universities in technology and information to improve universities' quality. The methodology used is by reviewing previous research papers related to the research. So that this research is expected to contribute, which can overcome the problems being faced, such as the application of blockchain in universities, namely how to use the blockchain system, what blockchain is, and how to change existing technology into disruptive technology. The experimental results state that by using data from the previous paper, the aim is to reveal the impact that blockchain technology has had on technology and information that is useful for improving the quality of universities in encouraging human potential and improving quality so that they can compete both domestically and abroad.
Usefulness of Augmented Reality as a Tool to Support Online Learning Ismail Ismail; Nur Iksan; Siva Kumar Subramaniam; Azmi Shawkat Abdulbaqie; Salini Krishna Pillai; Ismail Yusuf Panessai
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21133

Abstract

The global crisis following the outbreak of the Covid-19 epidemic has had an impact on the teaching and learning process (PdP). The main problem with PdP during the Covid-19 epidemic was the limitation in conducting face-to-face activities in the classroom. Therefore, a learning aid is needed to enable PdP to run optimally even though there is no face-to-face interaction between teachers and students. The research contribution is to highlight the application of Augmented Reality to support distance learning in the Covid-19 epidemic situation, specializing in Wood Carving Art for the subject of Visual Arts Education Form 4. The AR Wood Carving Art mobile application uses the ADDIE design model based on five phases, namely Analysis, Design, Development, Implementation, and Testing. The AR Wood Carving Art mobile application is evaluated based on its usefulness. The AR Wood Carving Art mobile application was evaluated among 27 students from 4 of SMK Pasir Gudang (Johor, Malaysia) and registered to Visual Arts. Based on the result, 80% of respondents strongly agree that the AR Wood Craving Art mobile application help respondents be more effective. It helps users to be more productive and giving ideas to users to be creative and innovative. One hundred percent of respondents strongly agree that the AR Wood Craving Art mobile application makes things that users want to achieve easier to do, and the AR Wood Craving Art mobile application does what users want. Eighty percent of respondents strongly agree that the AR Wood Craving Art application is useful and the application saves time when users use it. Therefore, the AR Wood Craving Art application is effectively used in learning which makes users more productive, creative, and innovative. In addition, the AR Wood Craving Art mobile application makes it easy for users to understand wood carving topics in visual arts subjects, and users can carry out educational and teaching activities like in a classroom.
The Detection System of Helipad for Unmanned Aerial Vehicle Landing Using YOLO Algorithm Bhakti Yudho Suprapto; A. Wahyudin; Hera Hikmarika; Suci Dwijayanti
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.20684

Abstract

The challenge with using the Unmanned Aerial Vehicle (UAV) is when the UAV makes a landing. This problem can be overcome by developing a landing vision through helipad detection. This helipad detection can make it easier for UAVs to land accurately and precisely by detecting the helipad using a camera. Furthermore, image processing technology is used on the image produced by the camera. You Only Look Once (YOLO) is an image processing algorithm developed to detect objects in real-time, and it is the result of the development of one of the Convolutional Neural Network (CNN) algorithm methods. Therefore, in this study the YOLO method was used to detect a helipad in real-time. The models used in the YOLO algorithm were Mean-Shift and Tiny YOLO VOC. The Tiny YOLO VOC model performed better than the Mean-Shift method in detecting helipads. The test results obtained a confidence value of 91.1%, and the system processing speed reached 35 frames per second (fps) in bright conditions and 37 fps in dark conditions at an altitude of up to 20 meters.
Design of Real-Time Aquarium Monitoring System for Endemic Fish on the Smartphone Naufal Inas Fikri; Vito Louis Nathaniel; Muchamad Syahrul Gunawan; Tomy Abuzairi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21137

Abstract

The high rate of decreasing population of endemic fish species is becoming more severe over time. Therefore, it needed an effort to bring back the stability of the number. One of the reasons for the decreasing population is the changing environment due to climate change and the difficulty of treatment for this species. This research aims to design an aquarium monitoring system for endemic fish. The main components for this system are microcontroller ESP32 DOIT, Temperature Sensors DS18B20, DF Robot Analog pH Sensors, ESP32 Cam, UV Lamp, and Blynk server. The experiment was conducted by monitoring the aquarium environment using sensors and comparing it with the reference sensors. With a monitoring system, we can find out whether the current condition of the aquarium is in accordance with the fish's living environment or not. The monitoring results show that the average error for temperature is 0.14% and for pH is 0.67%. These results indicate that the prototype sensors are linear with reference sensors. Besides that, a real-time monitoring system is easy to use and more attractive because of smartphone utilization to monitor fish with a camera and lamp.
Comparative Study of VGG16 and MobileNetV2 for Masked Face Recognition Faisal Dharma Adhinata; Nia Annisa Ferani Tanjung; Widi Widayat; Gracia Rizka Pasfica; Fadlan Raka Satura
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.20758

Abstract

Indonesia is one of the countries affected by the coronavirus pandemic, which has taken too many lives. The coronavirus pandemic forces us to continue to wear masks daily, especially when working to break the chain of the spread of the coronavirus. Before the pandemic, face recognition for attendance used the entire face as input data, so the results were accurate. However, during this pandemic, all employees use masks, including attendance, which can reduce the level of accuracy when using masks. In this research, we use a deep learning technique to recognize masked faces. We propose using transfer learning pre-trained models to perform feature extraction and classification of masked face image data. The use of transfer learning techniques is due to the small amount of data used. We analyzed two transfer learning models, namely VGG16 and MobileNetV2. The parameters of batch size and number of epochs were used to evaluate each model. The best model is obtained with a batch size value of 32 and the number of epochs 50 in each model. The results showed that using the MobileNetV2 model was more accurate than VGG16, with an accuracy value of 95.42%. The results of this study can provide an overview of the use of transfer learning techniques for masked face recognition.
Design Prototype of Temperature and Humidity Control and Monitoring on Weaver Ant Cage based on Internet of Things Dzata Farahiyah; Bevrin Wendra Purnama
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21438

Abstract

Increasing market demand cannot meet the needs of the community, especially in the rainy season, because Kroto produced by weaver ants is of low quality and hard to find. Modern Kroto cultivation has many advantages compared to traditional searching in nature. The quality and quantity of Kroto lie in maintaining the temperature and humidity for weaver ants. The challenge is how to maintain the temperature and humidity inside the artificial nest of weaver ants. To help overcome the problems of modern weaver ant cultivation, we design and develop automated devices based on the Internet of Things (IoT) to control and monitor temperature and humidity for weaver ant culture. We chose the limitation of temperature is in between 25 oC – 31 oC, and the humidity range is on the level 65% - 85%. We used NodeMCU as the mainboard, DHT22 as temperature and humidity sensor, Cayenne webserver as IoT platform, and fan, humidifier, and heater for the tools to control the environment. We had conducted four tests scenario, which are sensor calibration, relay testing, actuator time testing, and delay testing. The result in temperature reading shows good accuracy while the humidity performs a huge gap of error. The humidity needs to be adjusted with the linear regression formula. Based on the relay testing, the device works perfectly fine to control the heater, the humidifier, and the fan. According to the actuator timing testing, the humidifier has the quickest time to make more humid and soothing conditions, around 5 – 15 minutes. In contrast, the heater actuator needs a longer time to heat up the room. Depends on the temperature, it needs around 5 – 31 minutes. The longest time was during the fan actuator to cool down the room, around 30 – 90 minutes. The average delay of the IoT system is 200,01 ms and is categorized as good performance based on standard TIPHON.

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