Comparison K-Nearest Neighbors (K-NN) and Artificial Neural Network (ANN) in Real Time Entrants Recognition

Face recognition is an identification system that uses face characteristics of each person to identify and differentiate a person from others. In utilizing the development of technology, face recognition has attracted much attention in the world of technology. It is used for many purposes, but most often for security and law enforcement purposes. For example, face recognition is used to prevent people from getting fake identification cards. Face recognition also can be used for entrants who will enter a particular place such as security post to help security in doing their job. However, security has limited ability to make sure that entrants are not a threat to others. In our working, face recognition is used in security post to prevent stranger people with no particular purpose come in. In this paper, we compare face recognition approach using the K-Nearest Neighbor (K-NN) algorithm and Artificial Neural Network (ANN) algorithm. K-NN and ANN serve to classify each different person in a database. The result presents K-NN has 44.101% of accuracy and ANN has 38.177% of accuracy.