The Authentication process is highly dependent on Face Detection and Face Recognition during learning activities. In addition, in the E-Learning learning system we must also provide accurate and accurate information. The research method used is literature study and analysis. Literature study was carried out on the face of face detection and recognition in real-Time conditions carried out by various previous studies. Furthermore, analysis was carried out in a literature study studio to find suitable methods for the E-Learning environment. From the results of existing literature studies we recommend face detection using Face Countour and the Adaboost Algorithm added to CNN (Convolutional Neural Network)to normalize the facial contour function and normalize lightning in the surrounding environment where a face detection is located. The process is carried out, we use the 3WPCA-MD(Three-Level Wavelet

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The ability to self-diagnose to build capacity as an entrepreneur is something that is important in order to bridge the development of self-competence needed in the industrial era 4.0. This ability is expected to bring up a condition in which a person has full active awareness of the awakening of the entrepreneurial spirit within himself to then produce a productive person called Entrepreneurial Mindfulness. This study aims to develop self-detection tools about Entrepreneurial Mindfulness through an artificial intelligence-based website for students and alumni who are entrepreneurs. The research method used is the Neuroresearch method for developing Entrepreneurial Mindfulness measurement tools and the waterfall method for developing Artificial Intelligence-based websites. The results of research in the form of an Artificial Intelligence-based website about Entrepreneurial Mindfulness where the website will be able to provide profiling based on diagnoses made related to the level of Entrepreneurial Mindfulness owned by students and alumni in implementing entrepreneurial practices.

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