Abstract
Facial skin is skin that protects the inside of the face such as the eyes, nose, mouth, and others. Facial skin consists of several types, including normal skin, oily skin, dry skin, and combination skin. This is a problem for women because it is difficult to recognize and distinguish their skin types this is what causes some women to find it difficult to determine the right make-up and care products for their skin types. In this study, the Convolutional Neural Network (CNN) method is the right method for classifying women's skin types from the age of 20-30 years by following several stages using Python 3.5 programming with a depth of three layers and the results of this research using the CNN method get the results of the accuracy value good at 67%
Highlights
Most people, especially women pay attention to good appearance in terms of fashion, lifestyle, and the most concern is face
Research Methods Convolutional Neural Network The method used in this research is Deep Learning Convolutional Neural Network (CNN)
Convolutional layer is used to extract data features that will be used for training, the pooling layer is used to create new filters based on the desired rules, and the fully connected layer is MLP (Multilayer Perceptron) which is part of an artificial neural network and consists of a number of neurons linked by connecting weights [6]
Summary
Especially women pay attention to good appearance in terms of fashion, lifestyle, and the most concern is face. Every woman has a different face shape, color, and texture depending on heredity, conditions in the body, and different climates. The most visible thing on the face from the naked eye is on the skin. Facial skin is skin that protects the inside of the face such as the eyes, nose, mouth, and others. Many people are willing to spend a lot of money to maintain the health of their skin. Facial skin classified into several types including normal, combination, oil, dry, and sensitive skin [1]
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