Analisis Metode Ekstraksi Fitur Dalam Sistem Pengenalan Wajah Menggunakan Masker
DOI:
https://doi.org/10.22441/jte.2022.v13i1.001Keywords:
Face Recognition, LDA, Matlab, PCA, MaskerAbstract
Wabah coronavirus disease 19 atau covid-19 menyerang diberbagai belahan dunia. Yang mana pencegahannya adalah dengan mencuci tangan dan memakai masker. Memakai masker adalah salah satu halangan ketika seseorang akan membuka kunci layar smartphone atau bahkan fitur absensi karyawan, yang mana ini menggunakan teknologi face recognition. Sehingga, sistem absensi atau kunci layar kesulitan untuk mengenali wajah manusia tersebut ketika memakai masker. Dua dari metode yang dipakai ialah Principal Component Analysis (PCA) dan Linear Discriminant Analysis (LDA). Berdasarkan hasil percobaan pada sistem yang telah dibuat, informasi berupa hasil pengenalan gambar wajah yang diproses dari metode Principal Component Analysis mempunyai persentase rata-rata sebesar 91,3% untuk mengenali wajah manusia dengan menggunakan masker, sedangkan metode Linear discriminant Analysis mempunyai persentase rata-rata sebesar 20,67% untuk mengenali wajah manusia dengan menggunakan masker. Kemudian dengan metode pre-processing Gaussian Smoothing Filter dan metode PCA mempunyai persentase rata-rata sebesar 92,67% dan dengan metode LDA mempunyai persentase rata-rata sebesar 25,33%. Dari hasil persentase matematis, dapat disimpulkan bahwa metode Principal Component Analysis lebih unggul dalam mengenali wajah dengan memakai masker dibandingkan metode Linear discriminant Analysis baik dengan menggunakan metode pra-processing ataupun tidak menggunakan metode pra-processingDownloads
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