Sistem Identifikasi Absensi Berbasis Telapak Tangan (Palm Print)

Aktub Sugianto, Linna Oktaviana Sari

Abstract


Biometrics is an automatic method of getting to know someone based on physical characteristics such as iris, fingerprints, palms and other organs. The palm is one of the human organs that is commonly used as identification because it is unique. The palms also can’t change for decades, so they can be used in identification systems. In this study the application of palm-based identification systems will be designed using 2 PCA (Principal Component Analysis) and Back Propagation Neural Network (BPNN) methods. The principle method of PCA aims to simplify the variables to be observed by reducing the size of the dimensions. Furthermore, the Back Propagation Neural Network (BPNN) method is one of the machine learning methods that is suitable for qualitative data analysis (binary data). This BPNN is used to obtain high accuracy from the results of the analysis. This study using Matlab R2016a software for making palm recognition system applications. Matlab is used because of the image processing toolbox which has many complete tools and functions for processing and analyzing images. Conclution of this study have a 90% success rate on the PCA and BPNN methods with different palm samples. Keywoards : Identification, Matlab R2016a, Palm Print, Recognition, and Attendance.

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