Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Journal of Engineering and Applied Technology
Muhammad Nurwidya Ardiansyah
Universitas Negeri Yogyakarta
Automotive Engineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering Mechanical Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Development of crowd detection warning system based on deep convolutional neural network using CCTV Muhammad Nurwidya Ardiansyah; Marifa Kurniasari; Muhammad Dzulfiqar Amien; Danang Wijaya; Pradana Setialana
Journal of Engineering and Applied Technology Vol 3, No 1 (2022): (March)
Publisher : Faculty of Engineering, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jeatech.v3i2.43771

Abstract

The 2019 corona virus (Covid-19) pandemic is a global problem for now. One way to deal with the spread of the corona virus is to maintain a distance of at least one meter and stay away from crowds. Therefore, a crowd detection warning system based on a deep convolutional neural network (deep CNN) was developed using CCTV. The development of this system was carried out using the NVIDIA Jetson Nano microcontroller as the computing hardware. Crowd object detection uses the OpenCV library, the YOLOv3-Tiny algorithm, and the euclidean distance method to calculate the distance between 'person' objects. Based on the tests carried out on function and performance, the results obtained that this crowd detection warning system can detect 'person' objects with an accuracy rate of 92.79. In addition, this system has also been able to detect several types of colors from objects so that warning messages can be given more specifically on the color of the clothes of the 'person' in the detected crowd.
Development and performance analysis of the Gunungkidul cultural potential application based on progressive web apps Pradana Setialana; Muhammad Nurwidya Ardiansyah; Nova Suparmanto
Journal of Engineering and Applied Technology Vol 2, No 1 (2021): (March)
Publisher : Faculty of Engineering, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jeatech.v2i1.39525

Abstract

Gunungkidul has various cultural potentials that make it a tourist destination. To make it easier for tourists to visit and get tourist destination information, several researchers developed a mobile application-based information system. However, mobile applications have several drawbacks as such as the user must install the application and can only be used on specific operating systems. The purpose of this research is to develop and analyze applications regarding the potential of Gunungkidul culture based on progressive web apps and which can be used without having to install applications and can run in all operating systems. The application development method uses Scrum and Ionic Framework as a framework for the application. The performance analysis method was tested on runtime performance (loading, scripting, rendering, painting, system) and memory usage (min JS Heap and max JS Heap) by using Chrome Developer Tools for 30 tests. The results of the development show that there are 7 features in the application, namely (1) Peta; (2) Geoheritage; (3) Daerah; (4) Cagar Budaya; (5) Kuliner; (6) Seni Adat Tradisi; (7) Agenda. Runtime performance and memory usage test results show the average value on aspects (1) Loading: 33.60 ms; (2) Scripting: 1069.20 ms; (3) Rendering: 84.90 ms; (4) Painting: 22.33; (5) System: 429.67 ms; (6) Min JS Heap: 8.05 MB; and (8) Max JS Heap: 19.51 MB.
Co-Authors Danang Wijaya Marifa Kurniasari Muhammad Dzulfiqar Amien Nova Suparmanto Setialana, Pradana