Design and Build Web and API on “Absenplus” with Face Recognition using Deep Learning Method - Afada Wafri Arugia; Eko Junirianto; Eny Maria (Politeknik Pertanian Negeri Samarinda, 2022)
This research has background cause have not maximum yet of attendance’s system for now. “Absenplus” is an application attendance android based which has two features of system such as face recognition and geolocation. With technology who can help for developing “Absenplus” with design and build web and API as a web server who belong to integration into “Absenplus”’s application. So therefore the author decides to named “Design and Build Web and API on “Absenplus” using Deep Learning’s methods” to give a integration database to “Absenplus” apps. This research will take advantages of computing library of deep learning named TensorFlow and Keras. Besides, this research uses MTCNN for detection face image, Facenet Model to help model gets the extraction feature, and SVM for classification model image train and test. In geolocation’s system use geofence library to help development function geolocation’s system. This research also use Laravel framework in design and build web and API. Throughout this research give the results on “Absenplus” that user can use attendance online with face recognition and geolocation. In this result of face recognition, it can be conclude that average of predict probability is 67% with light room normally.