Utilizing Face Recognition With CNN For Online Ticket Validation Using Flutter Application

Reynaldi, Daf Akwal (2022) Utilizing Face Recognition With CNN For Online Ticket Validation Using Flutter Application. Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

Purchasing e-tickets is an online ticket purchase system. This method is considered adequate because there is no need to come to a place and buy it directly. This e-ticket purchase also has a secure validation system. However, it is not completely safe because the e-ticket validation system still uses a QR code scan like in a cinema. The main purpose of this study is to obtain data with various conditions with Face Recognition. The method used is the Convolutional Neural Network (CNN) method. The research begins with taking datasets obtained from the surrounding community. The face dataset is taken, and facial image processing is carried out based on several criteria, namely the face facing the front, right, and left. There are also head accessories such as hats and glasses when the dataset is taken. The result of this research is the Validation system with a high level of training accuracy that is 96% for 40 classes and 97% for ten classes, and for Testing Accuracy is 55%. Keywords: Face Recognition, CNN, E-ticket, Validation, Face Matching

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