<![CDATA[This study aims to apply facial pattern recognition digitally. Technology was developed with the hope of simplifying human work systems. First, as a biometric recognition system (can be combined with other biometric features such as fingerprint and voice). Second, as a search and indexing system for digital image/video databases. Third, as a security system for limited area access control, video conferencing, and human-computer interaction. The face is the central organ for human expression, recognition and communication. The face consists of four very important sense organs, namely the nose, eyes, ears and tongue. Currently face recognition is one of the major forms of research in the area of computer vision. Face pattern recognition is not only intended for science but is applied to several other practical applications. As for the application of applications such as identity authentication, surveillance and security, human computer intelligent interaction and film. The eigenface method is used to calculate eigenvalues and eigenvectors that will be used as features in the introduction. The Euclidean distance method is used to find the distance with the feature data that has been obtained, while the smallest distance is the result.. Keywords: Image processing, eigenface, euclidean]]>
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