<![CDATA[This research aims to enhance the efficiency and security of the identity verification process for cadets at API Banyuwangi through the implementation of facial recognition technology using the Haar Cascade algorithm. In this study, experimental methods and statistical analysis were used to analyze the data obtained from a series of processing stages, including RGB to grayscale conversion, image resizing, and cropping. Data were collected through facial image acquisition using a webcam and processed to train the model and test the success of the verification system. Statistical analysis shows that preprocessing techniques have a significant impact on verification success, while facial recognition methods are also relevant. However, the data are not normally distributed, indicating the need for alternative analytical approaches. Thus, this research provides valuable insights into the potential of facial recognition technology in enhancing efficiency and security in identity management at educational institutions, while also highlighting the need for further research for the development of methods and deeper understanding.]]>
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