cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Yudhi Ardiyanto
Contact Email
yudhi.ardiyanto@umy.ac.id
Phone
-
Journal Mail Official
ramadoni@umy.ac.id
Editorial Address
-
Location
Kab. bantul,
Daerah istimewa yogyakarta
INDONESIA
Journal of Electrical Technology UMY
Published by Universitas Muhammadiyah Yogyakarta
ISSN : 25501186     EISSN : 25806823     DOI : 10.18196/jet
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Library & Information Science
The Journal of Electrical Technology UMY (JET-UMY) is a peer-reviewed journal that publishes original theoretical and applied papers on all aspects of Electrical, Electronics, and Computer Engineering.
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol 6, No 1 (2022): June" : 6 Documents clear
3D Orientation Estimation Using Inertial Sensors Lu Bai
Journal of Electrical Technology UMY Vol 6, No 1 (2022): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v6i1.14638

Abstract

Recently, inertial sensors have been widely used in the measurement of 3D orientations because of their small size and relative low cost. One of the useful applications in the area of Neurorehabilitation is to assess the upper limb motion for patients who are under neurorehabilitation. In this paper, the computation of the 3D orientation is discussed utilising the outputs from accelerometers, gyroscopes and magnetometers. Different 3D orientation representations are discussed to give recommendations for different use scenarios. Based on the results form the 3D orientation, 2D and 3D position tracking techniques are also calculated by considering the joint links and kinematics constraints from the upper limb segments. The results showed that the performance using complementary filter can make good estimation of the orientation. 
Exploration of Generator Noise Cancelling Using Least Mean Square Algorithm Sri Arttini Dwi Prasetyowati; Bustanul Arifin; Agus Adhi Nugroho; Muhammad Khosyi’in
Journal of Electrical Technology UMY Vol 6, No 1 (2022): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v6i1.14826

Abstract

Generator noise can be categorized as monotonous noise, which is very annoying and needs to be eliminated. However, noise-cancelling is not easy to do because the algorithm used is not necessarily suitable for each noise. In this study, generator noise was obtained by recording near the generator (outdoor signal) and from the room (indoor signal). Noise generator exploration is carried out to determine whether the noise signal can be removed using the Adaptive LMS method. Exploration was carried out by analyzing statistical signals, spectrum with Fast Fourier Transform (FFT) and Inverse FFT (IFFT), and analyzing the frequency distribution of the remaining noise. The results showed that the correlation coefficients were close to each other. Outdoor and indoor signals are at low frequency. The behavior of FFT and IFFT if described in two dimensions, namely real and imaginary axes, formed a circle with a zero center and has parts that come out of the circle. It confirms that noise-cancelling with adaptive LMS can be realized well even though some noise is still left. The residual noise has formed an impulse that showed normally distributed with mean=-0.0000735 and standard deviation =0.000735. This indicates that the residual noise was no longer disturbing.
PDC Control for Mobile Robot Formations with Virtual Reference Based on Separation-Bearing Mamat Septyan
Journal of Electrical Technology UMY Vol 6, No 1 (2022): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v6i1.14425

Abstract

This paper presents a development of leader-follower formation control using separation-bearing control (SBC) and Parallel Distribution Compensation (PDC) control. The formation control involves tracking of each desired trajectory by leader and follower robots. The follower trajectory is generated using SBC approach with respect to predefined trajectory of the leader. This design is used to improve formation control when initial error is given to leader. In order to maintain the formation and avoid internal collision, the error tracking of each robot must be kept near zero. Each robot is controlled by kinematic and dynamics controller which is designed using PDC and PID. The velocity reference for dynamic robots is limited. The simulation result shows the tracking errors for position and orientation with initial lateral error set at 0.5 m are less than 0.5 m and 1.2 rad which then converges to the desired value. Thus, the good trajectory formation tracking is achieved.
Voice Recognition Security Reliability Analysis Using Deep Learning Convolutional Neural Network Algorithm Wahyu Ibrahim; Henry Candra; Haris Isyanto
Journal of Electrical Technology UMY Vol 6, No 1 (2022): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v6i1.14281

Abstract

This study discusses the reliability analysis of voice recognition security using the deep learning convolutional neural network (CNN) algorithm. The CNN algorithm has learning advantages in that it is safer, faster, and more accurate. CNN also can solve user identification problems in large amounts of data. The measured voice input is ten types of user's voice with the number of iterations of 6000, 12000, and 15000 sound files. Furthermore, voice extraction features are performed to recognize conversations and retain information that is very much needed. After that, the voice file iteration data is trained to register the user's voice so that a trained model is obtained. These results measure performance (confusion matrix) to analyze the actual value compared to the predicted value in the CNN algorithm. The results obtained are that the best accuracy is obtained at 15000 sound file iterations, 96.87%, 12000 sound file iterations get 96.30%, and 6000 sound file iterations get 95.77%. CNN's performance data shows that 15000 iterations of voice files produce high accuracy. Voice recognition security helps provide high security and maintain the privacy of one's identity.
Hybrid Energy Storage Performance Evaluation of Fuel Cell Injection on Standalone Photovoltaic System Indah Sulistiyowati; Jamaaluddin Jamaaluddin; Izza Anshory
Journal of Electrical Technology UMY Vol 6, No 1 (2022): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v6i1.14841

Abstract

In this research, some performance evaluations of battery as the main storageand supercapacitor as the supporting storage in a hybrid energy storage system werecarried out to determine the recommendations of whether fuel cells could be integratedinto a standalone photovoltaic system. In previous studies, the fuel cell circuit was judgedto be quite different by integration with a standalone photovoltaic system, and in thisstudy, observations were made on aspects of power quality such as voltage, current, andpower for the two energy storage systems. The research method is using simulation as themedium with several self-definition aspects on photovoltaic, fuel cell, battery, andsupercapacitor, also with their parameters. The result shows that on the battery, the fuelcell integration has no particular effect since the battery is the main storage, and thevoltage and current had minor perturbation. While in a supercapacitor, majorperturbation from the system had been absorbed due to the fuel cell integrationcharacteristic of giving major perturbation to the system. The main recommendation is bychoosing supporting storage instead of using both supercapacitors and fuel cells.
An Inventory Tool for Receiving Practicum Report Based on IoT by Using ESP32-CAM and UV Sterilizer: A Case Study at Muhammadiyah University of Sidoarjo Shinta Carolin Stevi Yanti; Indah Sulistiyowati
Journal of Electrical Technology UMY Vol 6, No 1 (2022): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v6i1.14607

Abstract

Currently, there are several problems related to practicum report collection inthe electrical engineering laboratory at the Muhammadiyah University of Sidoarjo. The firstproblem is the presence of crowds during practicum report collection that have theirdangers, specifically during the Covid-19 pandemic. Another problem is the absence oflaboratory assistants in the electrical engineering laboratory when there are students whowill collect reports. A tool that can receive practicum reports was made from these problems,and it can be monitored remotely by a laboratory assistant. By putting an RFID card to theRFID sensor on the box so that the solenoid can open the box door and the student can putthe report into the box. At the same time, ESP32-CAM takes pictures of students collectingthe report. Then, notification in the form of photos and student information will be sent tothe laboratory assistant through the Telegram application. After the report is placed into thebox, the UV Sterilizer will turn on to disinfect the report. The expectation of making this toolis to facilitate the collecting report process of practicum results and reduce the crowd in thelaboratory.

Page 1 of 1 | Total Record : 6

 1 

Filter by Year

2022 2022


Reset
Filter By Issues
All Issue Vol. 8 No. 2 (2024): December Vol 8, No 1 (2024): June Vol 7, No 2 (2023): December Vol 7, No 1 (2023): June Vol 6, No 2 (2022): December Vol 6, No 1 (2022): June Vol 5, No 2 (2021): December Vol 5, No 1 (2021): June Vol 4, No 2 (2020): December Vol 4, No 1 (2020): June Vol 3, No 4 (2019): December Vol 3, No 3 (2019): September Vol 3, No 2 (2019): June Vol 3, No 1 (2019): March Vol 2, No 4 (2018) Vol 2, No 3 (2018) Vol 2, No 2 (2018) Vol 2, No 1 (2018) Vol 1, No 4 (2017) Vol 1, No 3 (2017) Vol 1, No 2 (2017) Vol 1, No 1 (2017) More Issue