PENGEMBANGAN SISTEM PROCTORING UJIAN ONLINE DENGAN FACE RECOGNITIONNITION MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (STUDI KASUS : UNIVERSITAS NUSA PUTRA)

Education is a critical foundation in the formation of human potential, and the shift towards online exams marks a major transformation in the way we assess and measure academic achievement. With the advancement of technology, the use of proctoring systems with head movement tracking technology is a progressive step towards maintaining exam integrity. However, the move to online exams also brings unique challenges, as cheating and lack of oversight can undermine confidence in exam results. In practice, Nusa Putra University is also taking part in the application of technology to exams, where this educational institution applies online exams. Therefore, the development of a reliable and effective proctoring system is essential to maintain academic standards. This research aims to design and develop an online exam proctoring system that utilizes face recognition technology. Online exam proctoring is necessary to ensure the validity and security of the exam. The proposed system applies a participant movement detection algorithm during the exam which is strengthened by the Convolutional Neural Network (CNN) algorithm to monitor behavior during the exam, and detect suspicious actions based on specified parameters with a limit of 30%. The results of this research are expected to contribute to improving the integrity of online exams, encouraging the adoption of proctoring technology, and providing effective solutions for educational institutions facing challenges related to online exam security. Where the system is built using PHP language with Laravel Framework and JavaScript for programming language and MySQL for its DBMS.

Keywords: Proctoring, Exam, Face Recognition, Security, Convolutional Neural Network