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All Journal Journal of Electrical, Electronic, Information, and Communication Technology (JEEICT)
Muhammad Dhafier Mu'afa
Universitas Sebelas Maret
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Design of Smart Medical Mask Trash Can For Public Places Muhammad Dhafier Mu'afa; Refansyah Basu Dewa; Muhammad Raflie Pangestu; Muhammad Fiqih Al Faishal; Hari Maghfiroh
Journal of Electrical, Electronic, Information, and Communication Technology Vol 3, No 2 (2021): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.3.2.55186

Abstract

The Covid-19 pandemic mainly caused the sudden rise of medical mask waste. There are some steps that can be taken to reduce and manage the waste, including dissolving the mask so it cannot be use again, reduce the risk of disease transmission, and assist the workers in managing the waste of medical mask. Therefore, this paper proposes a device that can solve all the problem, which is the “Smart Medical Mask Trash Can”. This device can be used to dissolve and disinfect the mask, as well as manage the mask waste with an easy way in accordance with health protocol. The outcome show that this device can monitor the waste with an application program on a real time that can notify and organize a schedule for automatic disinfection. This tool is suitable to be placed in public places because of its high mobility and there is a lot of medical mask's waste.
Fire Detection Based on Image Using MATLAB GUI Programme Muhammad Dhafier Mu'afa; Mark Reindhard Joyakin Silalahi; Hanif Wisti Julitama; Joko Hariyono
Journal of Electrical, Electronic, Information, and Communication Technology Vol 5, No 1 (2023): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.5.1.69091

Abstract

Computer vision-based fire detection systems overcome this limitation in that they do not identify flammability on a product-by-product basis. In this study, fire detection was carried out using the YCbCr, RGB, and HSV map approach. The offered system uses color segmentation as a component of fire detection analysis. These three colors space segments will then be extracted to determine the presence of fire in the image used. A rule which consists of five rules based on color space condition had been constructed for classification of a pixel classified as fire. If a pixel satisfies these five rules, the pixels belong to fire class.This paper consists of 6 steps, including image acquisition, image pre-processing, image segmentation, feature extraction, image classification, and GUI creation. GUI provides a visual interface that is intuitive and easy for the user to understand the proposed system. By using button and another visual elements, users can interact with the system efficiently. Based on the tests carried out, the proposed system can detect images of fire in dark and light conditions. Performance testing is done by collecting a set of fire images on the internet. Performance is judged based on how many errors are generated when detecting fire. Performance is categorized into five types, including very good, good, fair, poor, and very poor.
Co-Authors Hanif Wisti Julitama Hari Maghfiroh Joko Hariyono Mark Reindhard Joyakin Silalahi Muhammad Fiqih Al Faishal Muhammad Raflie Pangestu Refansyah Basu Dewa