The Effect of Facial Attributes in Identifying Gender Using Facial Recognition

Facial Recognition technology has become part of people's daily lives. This technology can be used in various ways such as face filter applications, mobile lock screens, to security cameras. This study aims to experiment in making models that use facial recognition attributes to identify gender by using five types of classification analysis methods. Based on the research that we conducted using several methods and measuring it based on the evaluation parameters, it can be seen that the model that uses Random Forest method has the highest level of accuracy among other methods, with an accuracy of 97.502%. Therefore, the Random Forest is the best model in determining the gender of the sample that we studied.