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All Journal Jurnal ULTIMA Computing PELS (Procedia of Engineering and Life Science)
Achmad Fatchur Rochman, Achmad Fatchur
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Wiring Diagram For The Ventilation Panel : Gambar Wiring Pada Panel Ventilasi Rochman, Achmad Fatchur; Wisaksono, Arief
Procedia of Engineering and Life Science Vol. 5 (2024): Proceedings of the 7th Seminar Nasional Sains 2024
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/pels.v7i0.1475

Abstract

Wiring diagrams are an essential tool in the maintenance and repair of electrical systems, enabling quick identification of the source of the problem. Knowledge of electrical component symbols and their functions is important in reading wiring diagrams. Ventilation systems play a crucial role in closed environments such as chicken coops, maintaining air circulation and appropriate temperatures. Settings can be made automatically via the climate controller and control panel. Therefore, a basic understanding of the use of these devices is important for breeders. The research method used is descriptive qualitative with data collection in the field, especially at CV. Bintang Pratama Teknik, to study ventilation panels from wiring drawing in AutoCAD to assembly. The research results include an understanding of components such as electrical panels, AutoCAD, MCB, TOR, contractors, busbars, duct cables, and terminals. Drawing components using AutoCAD allows a better understanding of their design and functionality.
Development of Cavendish Banana Maturity Detection and Sorting System Using Open Source Computer Vision and Loadcell Sensor Rochman, Achmad Fatchur; Sulistiyowati, Indah; Jamaaluddin, Jamaaluddin; Anshory, Izza
Ultima Computing : Jurnal Sistem Komputer Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3869

Abstract

This research aims to develop a system of detecting the maturity and sorting of cavendish bananas using Open Source Computer Vision (OpenCV) and also assisted by a loadcell sensor. The problem experienced at this time is that fruit sorting is still manual which is less efficient and inaccurate in distinguishing banana maturity based on the color of the skin. This is because the human eye is sensitive to changes in lighting and fatigue. This designed system will use webcam for image processing and loadcell for fruit weight measurement, controlled by Arduino Uno microcontroller. While the algorithm used to determine the color of the ripeness of the banana fruit itself is HSV. The test results show an average weight error of 0.08% for ripe bananas, 0.71& for unripe bananas, while the color detection produces an accuracy of 47.34% on average in bright lighting conditions. In conclusion, this system is successful in improving sorting efficiency with adequate accuracy results, but further development is needed so that the accuracy level increases.
Development of Cavendish Banana Maturity Detection and Sorting System Using Open Source Computer Vision and Loadcell Sensor Rochman, Achmad Fatchur; Sulistiyowati, Indah; Jamaaluddin, Jamaaluddin; Anshory, Izza
ULTIMA Computing Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3869

Abstract

This research aims to develop a system of detecting the maturity and sorting of cavendish bananas using Open Source Computer Vision (OpenCV) and also assisted by a loadcell sensor. The problem experienced at this time is that fruit sorting is still manual which is less efficient and inaccurate in distinguishing banana maturity based on the color of the skin. This is because the human eye is sensitive to changes in lighting and fatigue. This designed system will use webcam for image processing and loadcell for fruit weight measurement, controlled by Arduino Uno microcontroller. While the algorithm used to determine the color of the ripeness of the banana fruit itself is HSV. The test results show an average weight error of 0.08% for ripe bananas, 0.71& for unripe bananas, while the color detection produces an accuracy of 47.34% on average in bright lighting conditions. In conclusion, this system is successful in improving sorting efficiency with adequate accuracy results, but further development is needed so that the accuracy level increases.
Co-Authors Arief Wisaksono Indah Sulistiyowati Izza Anshory Jamaaluddin