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Rismawan, Komang Diva
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Computer Science & IT

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Face Identification Based on K-Nearest Neighbor Wirdiani, Ni Kadek Ayu; Hridayami, Praba; Widiari, Ni Putu Ayu; Rismawan, Komang Diva; Candradinata, Putu Bagus; Jayantha, I Putu Deva
Scientific Journal of Informatics Vol 6, No 2 (2019): November 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i2.19503

Abstract

Face identification has been widely applied this time, such as security on gadgets, smart home security, and others. Face dominates as a biometric which is most increase in the next few years. Face is used for biometric identification which is considered successful among several other types of biometrics and accurate results. Face recognition utilizes facial features for security purposes. The classification method in this paper is K-nearest Neighbor (KNN). The K-Nearest Neighbor algorithm uses neighborhood classification as the predictive value of a good instance value. K-NN includes an instance-based learning group. This paper developed face identification using Principal Component Analysis (PCA) or eigenface extraction methods. The stages of face identification research using the KNN method are pre-processing in the input image. Preprocessing used in this research are contrass stretching, grayscale, and segmentation used haar cascade. This research is registered 30 people, each person had 3 images used for training and 2 images used for testing. The results obtained from several trials of k values are as follows. Experiments with a value of k=1 get the best accuracy, namely 81%, k=2 get 53% accuracy, and k=3 get 45% accuracy.
Co-Authors Ayu Wirdiani Candradinata, Putu Bagus Hridayami, Praba Jayantha, I Putu Deva Widiari, Ni Putu Ayu