Crowd Face Detection with Naive Bayes in Attendance System Using Raspberry Pi

Abstract

PT. Restu Agung Narogong is a company with a total of 176 employees, queues often occur in the attendance process, both incoming and outgoing attendance. The employee needs to register their attendance. It is time consuming during the shift change. Therefore, a biometric system is needed to support the attendance system to identify employee without registering themselves. One of the alternative biometric systems is face recognition by using a computer vision. The purpose is to implement a crowd face detection with Raspberry Pi using the Naïve Bayes classifier. This system uses an algorithm to extract facial characteristics into mathematical data. Then the data is compared with data from other facial characteristics collected in the database. This device uses Python as a programming language with some of the scientific Python libraries. The testing of the Naïve Bayes method was conducted using a sample of dataset of 370 augmented facial imagery. The accuracy of this implementation is 76.31%, the precision is 78.25% and recall 81.25%. The background and lighting of the captured image affect the accuracy of this device.