<![CDATA[Biometrics is an automatic method for recognizing someone based on physical characteristics or behavior, including Face Recognition. Generally used for identification and verification. Identification is the process of recognizing and matching of a it is person's biometric data in a database that contains a person's character record. Verification is the process of information determining whether someone is in accordance with his/her look. In this research, a biometric attendance system designed using a tool called Rasberry Pi 3 (Mini Computer) for taking user face images (photo grid) then planting is eigenface algorithms and artificial neural network. Rasberry Pi often abbreviated as Raspi is a single board computer whereas whereas the it’s size same as credit card that can be used to run official programs, computer games and media player for high resolution videos. The eigenface method is face recognition based on the Principal Component Analysis. On the eigenface method image is captured and stored in the database to become training data which compared to the sample data. ANN used because it has ability to learn from the data trained. With the design of this attendance system, it is expected to avoid negative things, for example, the loss of student attendance data because there are too many signatured papers in the attendence list for each subject. The results of testing face data used 3 hidden layers where the first layer has 32 neurons, the second layer has 18 neurons, and the third layer has 8 neurons, it concludes that the face recognition succed to recognize somebody’s face as his/her photograph is 100%.Keywords : Face Recognition, Raspberry Pi 3, Eigenface, Neural Network.]]>
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