Rancang Bangun Pendeteksi Wajah Bermasker Dan Tidak Bermasker Dalam Absensi Di Masa Pandemi COVID-19 Menggunakan Convolutional Neural Network
DOI:
https://doi.org/10.22441/jte.2021.v12i2.006Keywords:
Coronav, Deep Learning, Coronavirus, Convolutional Neural NetworkAbstract
Pada awal tahun 2020 dunia dikejutkan dengan Penemuan virus baru yaitu Coronavirus yang dapat mengakibatkan kematian. Penyebaran virus tersebut ialah dengan kontak lansung antara individu, batuk, dan flu. Oleh sebab itu pencegahaan ialah agar menggunakan masker apabila beraktivitas diluar rumah maupun di keramaian. Oleh sebab itu teknologi ikut peran dalam mengatasi penyebarannya dengan sebuah pendeteksian terhadap orang yang menggunakan masker dan tidak menggunakan masker yang menggunakan sebuah kamera. Pendeteksian dalam menggunakan sebuah kamera banyak diterapkan menggunakan konsep dari Deep learing. Deep learing (DL) merupakan bagian dari ilmu komputer yang mempelajari bagaimana menjadikan mesin (komputer) dapat melakukan pekerjaan seperti dan sebaik yang dilakukan manusia, bahkan bisa lebih baik. Pada penelitian ini menggunakan salah satu dari Deep Learning yaitu Convolutional Neural Network yang dirancang menggunakan filter pertama 32 dengan Kernel 3x3 berikutnya menggunakan filter 64 dengan kernel yang 3x3. Berdasarkan hasil pengujian training menggunakan model Convolutional Neural Network memiliki akurasi 95% pada testing menghasilkan akurasi 91% dalam hal ini Convolutional Neural Network mempunyai potensi untuk mendeteksi wajah dengan performa yang optimal dalam mengklasifikasi Wajah bermasker dan Tidak BermaskerDownloads
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