@thesis{thesis,
		author={Luqman  Luqman and Palupiningsih  Pritasari and Rahmah  Tita Khurnelia},
		title ={Perancangan Aplikasi Kehadiran
Guru menggunakan Pengenalan Wajah dengan Algoritma Multi-Task Cascaded Convolutional Network (Studi Kasus : SMKN 5 Telkom Banda Aceh)},
		year={2020},
		url={http://156.67.221.169/4152/},
		abstract={Attendance is important in the teaching and learning process. The attendance system that runs must support the formation of discipline towards teachers or students. However, the attendance system that runs manually is not effective in
supporting discipline, especially for teachers who have a big role in the teachinglearning process. There are many problems caused by the attendance system that runs manually, one of which is that there is no back-up of attendance report data if the attendance report data book is damaged or attendance data can be replaced easily. That is why it is important to modernize the teacher attendance
system that runs manually. In this study, the authors built a teacher attendance application using biometric techniques. The biometric technique that I use is facial recognition, for the algorithm that is applied to the output in the form of facial
recognition, namely the Multi-task cascaded convolutional network (MTCNN). Applications built based on the desktop using the JavaScript programming language. Application trials were carried out on 11 images from 7 individuals
whose similarities were sought with 24 training data images from 8 individuals. Trials were also carried out with distance parameters of 50.70 and 100cm. The results of the application test tests carried out produce 100% accuracy, which means that MTCNN can recognize faces well.}
		}