University State of Surabaya, Indonesia
BibTex Citation Data :
@article{JMASIF9281, author = {Riskyana Intan P and Elly Imah}, title = {Studi Komparasi Ekstraksi Fitur pada Pengenalan Wajah Menggunakan Principal Component Analysis (PCA) dan Wavelet Daubechies}, journal = {Jurnal Masyarakat Informatika}, volume = {6}, number = {12}, year = {2015}, keywords = {ekstraksi fitur; PCA; pengenalan wajah; Random Forest Classifier;Wavelet Daubechies}, abstract = { Paper ini membahas perbandingan ekstraksi fitur untuk pengenalan wajah menggunakan metode Principal Component Analysis (PCA) dan Wavelet Daubechies untuk pengenalan wajah . Basis wavelet daubechies yang digunakan adalah wavelet db2, db4, dan db8 . Setiap dekomposisi dilakukan hingga level ke-3 yang kemudian diambil fitur aproksimasi wavelet dan fitur statistik wavelet. Variasi nilai komponen utama dimulai dari nilai komponen ke-1 hingga nilai komponen ke-100 dari 4096 nilai eigen. Nilai komponen ke-1 memiliki presentase sebesar 62% sedangkan nilai komponen ke-100 memiliki presentase sebesar 99% dari total nilai eigen,. Pengujian sistem menggunakan 216 citra wajah yang diambil dari dataset The Japanese Female Facial Expression (JAFFE) yang terdiri dari 10 individu dengan masing-masing sekitar 20 wajah per- individu. Pemilihan data train dan data tes menggunakan cross validation dengan rata-rata akurasi 94.42%. Dari hasil percobaan menggunakan Random Forest Classifier diperoleh tingkat pengenalan tertinggi untuk ekstraksi menggunakan PCA sebesar 100% pada variasi data 95% ,sedangkan tingkat pengenalan tertinggi untuk ekstraksi menggunakan Wavelet Daubechies sebesar 98.611% pada wavelet db2 menggunakan fitur aproksimasi wavelet. }, issn = {2777-0648}, pages = {46--54} doi = {10.14710/jmasif.6.12.9281}, url = {https://ejournal.undip.ac.id/index.php/jmasif/article/view/9281} }
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