Deteksi Penggunaan Masker Dengan Menggunakan Metode Convolutional Neural Network

Pambudi, Wahyu Satrio (2022) Deteksi Penggunaan Masker Dengan Menggunakan Metode Convolutional Neural Network. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Coronavirus Disease 2019 (Covid-19) merupakan jenis penyakit baru yang sekarang telah menjadi pandemik di seluruh dunia. Penyebaran Covid-19 begitu cepat, sehingga penanganan yang tepat sulit dilakukan. Salah satu upaya Pemerintah dalam mencegah penularan virus ini adalah dengan mewajibkan masyarakat untuk menerapkan Protokol Kesehatan (Prokes) standar WHO, yakni Prokes 3M (memakai masker, menjaga jarak, dan mencuci tangan), terutama saat mereka beraktifitas di luar rumah. Salah satu ketidakpatuhan masyarakat di dalam menerapkan Prokes ini adalah adanya orang yang tidak memakai masker, sehingga menjadi kendala dalam pencegahan penularan Covid-19. Oleh karena itu dalam Tugas Akhir ini, penulis membuat sebuah program untuk deteksi penggunaan masker. Metode yang digunakan adalah metode berbasis Convolutional Neural Network (CNN). Dari hasil uji coba, didapat performa dari sistem yang berhasil melakukan deteksi penggunaan masker recall 99.01%, precision 98%, dan accuracy 98,42%.

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Coronavirus Disease 2019 (Covid-19) is a new type of virus that has now become a worldwide pandemic. The spread of Covid-19 is so fast, that proper handling is difficult. One of the Government's efforts to prevent the transmission of this virus is to
requires the public to apply the WHO standard Health Protocol (Prokes), namely the 3M Prokes (wearing masks, maintaining distance, and washing hands), especially when they are active outside the home. One of the people's disobedience in implementing this Prokes is the presence of people who do not wear masks, so that it becomes an obstacle in preventing the transmission of Covid-19. Therefore, to find out if there are people who do not use this mask, in this study, face detection will be carried out from mask users. The method used is Convolutional Neural Network (CNN). From the test result, the system successfully detects the use of mask with recall is 99.01%, precision is 98%, and accuracy 98.42%.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Convolutional Neural Network, Deteksi Masker
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Wahyu Satrio Pambudi
Date Deposited:	11 Feb 2022 02:11
Last Modified:	01 Nov 2022 04:02
URI:	http://repository.its.ac.id/id/eprint/93742

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