Tjut Awaliyah Zuraiyah, Sufiatul Maryana, Asep Kohar

Judul	:	Automatic Door Acess Model Based on Face Recognition using Convolutional Neural Network
Abstrak	:	Automatic door access technology by utilizing biometrics such as fingerprints, retinas and face structures is constantly evolving. Face recognition and the use of masks are widely used to access doors automatically, so there is difficulty recognizing someone who is wearing a mask. The study aimed to create an automated door access model using convolutional Neural Network (CNN) algorithms and Amazon Rekognition as cloud-based software. The CNN algorithm is applied to classify faces wearing masks or not wearing masks. The CNN architecture model uses sequential, convolution2D, max polling 2D, flatten dan dense. The hardware includes the Raspberry Pi, USB Webcam, Relay, and Magnetic Doorlock. The test results were obtained from the results of the accuracy plot on the Convolutional Neural Network model with an accuracy rate of 99% at an epoch value of 8 with a learning time of 67 seconds
Tahun	:	2022	Media Publikasi	:	Jurnal Nasional Terakreditasi A
Kategori	:	Jurnal	No/Vol/Tahun	:	1 / 22 / 2022
ISSN/ISBN	:	2476-9843
PTN/S	:	Universitas Pakuan	Program Studi	:	ILMU KOMPUTER
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