<![CDATA[Face is a part of the human body that is very influential in everyday life. Most humans recognize a person by face. From the uniqueness of the face, there are innovations about automatic presence using faces that are more efficient than manual presence which is prone to manipulation. However, in reality, automatic presence based on facial recognition has a disadvantage of high light intensity, which makes facial images look biased. This problem can be overcome by approaching the YCbCr color space which is able to overcome the high light intensity in the image. The essence of automatic presence is the process of detecting and recognizing human facial images. In this study, only focus on facial recognition with the YCbCr color space feature extraction method and the Principle Component Analysis method. The results from the PCA value will be calculated using the Eucledian Distance to determine the closeness between the training image and the test image. In this test using two scenarios, the first test scenario uses a test image without light that is able to get an accuracy of 84%. The second test scenario uses a test image with a light beam capable of obtaining an accuracy of 52%.]]>
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