<![CDATA[Rapid technological developments in the world have had a major impact on various fields, i.e. administration and data collection. One of the data collection systems that is often used is attendance. The attendance system initially only used an attendance sheet that was filled out manually, but there were shortcomings i.e. the possibility of forging signatures during attendance. Therefore, other methods are needed to overcome these problems. In this study, we propose to use facial features for attendance. The data used are 750 facial images consisting of 5 people with each person having 150 facial images with various expressions. The data is divided into two, namely 500 images as training data and 250 images as test data. The next stage is to find a facial features, we propose to use the Local Binary Patterns Histograms (LBPH) method. LBPH is a combination of the Local Binary Patterns (LBP) method with Histograms of Oriented Gradients (HOG). After that, we perform face recognition based on the features that have been obtained. Based on the research results obtained an accuracy rate of 86%]]>
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