Implemantasi Pengenalan Wajah Dengan Metode Eigenface Pada Sistem Password Laptop

Zihan Noor Abdillah (Fakultas Industri Kreatif & Telematika, Prodi Teknik Informatika, Universitas Trilogi, Jakarta Selatan, Indonesia)

JURIKOM (Jurnal Riset Komputer)
Vol 5, No 3 (2018): Juni 2018

System development technology encourages the development of current technology with home systems using facial recognition system. The study was conducted for homes in occupied homes secured by people who were not their owners. This stage uses the eigenface method. Eigenface to reduce the dimensional vector into a simpler vector (eigenvector). The introduction of this facial synt is much to use with Eigenface method, because for Eigenface method can provide a good level of accuracy, System that is able to achieve success rate of 84.6% with FAR (Incorrect Acceptance Rate) = 16.2%, FRR (Rejection Rate False) = 20% and EER (Mistake Rate) = 0.3. The Benefits of Using the System to Produce Others from Unfamiliar Persons To Know Our Home or Outside That We Limit, In This Method The Image of Face is posted in a significant feature significantly. Eigenface is a significant feature, since the feature is a major component of managing face images for training. The Eigenface method will point the spike point on the resulting image that matches the face in the database that makes them differentiated.