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All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Review Pendidikan dan Pengajaran (JRPP) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal JEETech Journal of Applied Data Sciences J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Ilmu Komputer dan Informatika Scientechno: Journal of Science and Technology Jurnal Ilmu Komputer dan Teknik Informatika
Rahmawati, Lailia
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

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Journal : Jurnal JEETech

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Pemanfaatan Teknologi Computer Vision Untuk Implementasi Deteksi Masker Menggunakan Metode Supervised Learning Rahmawati, Lailia; Rifki Arrosid, Muhammad; Gugus Azhari, Mohammad
Jurnal JEETech Vol. 4 No. 2 (2023): Nomor 2 November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (764.874 KB) | DOI: 10.32492/jeetech.v4i2.4201

Abstract

The use of masks is still very strict in public places, especially in hospitals, this is solely done to prevent the spread of the corona virus again. The purpose of this research is to assist examination workers or health protocol workers in supervising the use of masks in public places. Mask detection is a solution to this problem, by utilizing computer vision technology and applying supervised learning algorithms. For this mask detection classification method, this system uses the Naive Bayes method. The output of this mask detection system is planned to distinguish people wearing masks and not wearing masks, by giving red labels to people who are not wearing masks and green labeling to people wearing masks. The distance aspect is used in testing this mask detection system, the system is able to work well by getting an error rate presentation below 2% and getting the highest accuracy of 100% with an average percentage value of 98%. On the other hand, there are still weaknesses in this system, the use of brown masks that are in harmony with skin color can worsen the results of the classification system
Prototype Sistem Monitoring Kebakaran Berbasis IoT Menggunakan Node MCU Dengan Penyemprot Air Otomatis Rahmawati, Lailia; Yusuf Pratama, Yoga; Gugus Azhari, Muhammad
Jurnal JEETech Vol. 3 No. 1 (2022): Nomor 1 May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.48056/jeetech.v3i1.189

Abstract

Fires are very detrimental, ranging from loss of property to even loss of life. Fires can be detected when the fire has grown or smoke has billowed out of buildings. Urban areas have densely populated housing so that it has the potential to cause problems in the event of a fire. These fires can be caused by by factors of human negligence and natural factors. Such as the occurrence of short-circuited electricity, negligence in cooking, negligence in burning garbage, and others. Therefore, we need a tool that can detect the presence of an early source of fire so that it does not spread. The problem that often occurs is when a fire occurs, the fire department often arrives late, so there are many losses due to the fire. And the losses can be material and economic. Therefore we need a system that works to control the fire automatically and to extinguish the fire in every house. This study aims to design and build an efficient and affordable prototype. Which later can be applied to housing or warehouses. This prototype is designed using NodeMCU ESP8266 as the main controller, Flame sensor can respond to infrared light beams on the modulation spectrum from 5 to 30 cycles per second, Web Thinger.Io as a server, data storage on the internet of things , and notification of fire in the Blynk application. This system uses a flame sensor based on the Node MCU ESP8266 microcontroller and is equipped with a Buzzer for Alarm and a Mini Water Pump to automatically spray water if a fire is detected. This system utilizes the Blynk Application as an interface to provide notification information about a fire to find out notifications if a fire is detected. And if a fire is detected, it will automatically get a notification from the Blynk application on the "There is Fire" Smartphone and the buzzer will automatically sound and the mini water pump will automatically spray water. In this study, the tool can automatically send Safe and Fire notifications using the blynk application on a smartphone with a delay of < 3 seconds.
Co-Authors Ambulani, Nur Atmojo, Wahyu Tisno Budiman Budiman Cynthia, Dessy Nia Cynthia, Maulidania Mediawati Efendi, Iqbhal Rizky Eka Pandu Cynthia, Eka Pandu Erviana, Irma Fachruzzaki, Fachruzzaki Febrian , Wenny Desty Febrian, Wenny Desty Gugus Azhari, Mohammad Gugus Azhari, Muhammad I Putu Dody Suarnatha Izzatul Umami Khairunnisa Khairunnisa Kusant, Jani Lengam, Rino Muhammad Lukman Hakim, Muhammad Lukman Pamungkas, Kris Maulana Ratih Kusumastuti Rauza Sukma Rita Reviandari Widyatiningtyas, Reviandari Rifki Arrosid, Muhammad Sri Mardiyati Suharni Suharni Sukini, Sukini Suprihartini, Yayuk Suryati Suryati Sutriawan Sutriawan Syahputra, Hendri Winarti, W Yusuf Pratama, Yoga