%0 Thesis
%9 Skripsi
%A Azki Hidayatulloh Alfain, NIM. 17106050045
%B FAKULTAS SIANS DAN TEKNOLOGI
%D 2021
%F digilib:47034
%I UIN SUNAN KALIJAGA YOGYAKARTA
%K Face Detection, MTCNN, Waterfall, Computer-Based Test
%P 75
%T PENGEMBANGAN FITUR DETEKSI WAJAH OTOMATIS  PADA SISTEM PENGAWASAN COMPUTER BASED TEST  DI ADMISI UIN SUNAN KALIJAGA
%U https://digilib.uin-suka.ac.id/id/eprint/47034/
%X Due to the COVID-19 pandemic caused a change in the selection pattern at Sunan Kalijaga State Islamic University into an online Computer-Based Test exam. Supervision is carried out by sending photos of participants to the proctoring system. On its way, it is often found photos that do not contain the faces of the participants or even more than one person is detected in the photo. For this reason, an automatic face detection system was created to make it easier for supervisors to oversee the exam.  This system uses the Multi-task Cascade Convolutional Neural Network method to perform face detection and is developed using the Waterfall development model. This model was chosen because its implementation is simple and is considered sufficient to meet the needs of this system development.  Based on the tests carried out, the developed system can be implemented properly. The developed face detection system has an accuracy value of 90%, a specificity value of 99%, a recall value of 81% and an average execution time of 0.761 seconds. In addition, the system can also handle 50 concurrent requests with an average response time of 0.82 seconds per request.
%Z Ir. Aulia Faqih Rifa’I, S.T, M.Kom