Face Recognition Application with Deep Neural Networks for Teacher Wellbeing Assessment

The progress of research and implementation of face recognition needs to be a concern, especially in the field of education. Technological progress does not necessarily have a significant impact on teachers. Teacher well-being is very important because it has an impact not only on teachers but also on students, institutions and stakeholders in the education sector. Therefore, an application based on face recognition was developed which is able to assess teacher wellbeing conditions. This application implements the concept of self-diagnosis so that teachers can apply intervention programs according to their profile and condition based on the test results on the application. The face recognition application, which is used for teacher wellbeing assessment, was developed using the Deep Neural Networks method. The research method used is the Neuroresearch method which consists of 3 stages, namely exploratory, explanatory and confirmatory research. The results of the research were carried out through three stages of the research method to produce a teacher standard instrument. The well-being research method used was the Neuroresearch method which consisted of 3 stages, namely exploratory, explanatory and confirmatory research. While the recognition application uses the core calculation of the Deep Learning algorithm type to find the best weight of the existing data so as to produce the input and output layer processes of the Deep Neural Network.