<![CDATA[Face recognition is a biometric technology that is widely used in the era of the industrial revolution 4.0 such as smart home, security and presence. In the application of face recognition, a method is needed that can perform facial recognition quickly andwith a high level of accuracy. This study aims to determine the level of accuracy and computation time of the Haar Cascade Classifier Algorithm and Convolutional Neural Network in Face Recognition with the mechine learning method. Determining the level ofaccuracy is done by calculating the amount of facial data that can be recognized from the overall face data. Calculating the computational time is done by calculating the time required during the facial recognition process by the computational process. The process of determining the level and time of computing is carried out by the python computing program using the numpy and tensorflow libraries. Based on the analysis carried out by the face detection process using the Haar Cascade Algorithm and Convolutional Neural Network, the program accuracy is 98.84% and the average time needed to recognize faces is 0.05s]]>
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