Pengenalan Setengah Wajah menggunakan Arsitektur Xception pada Metode Convolutional Neural Network
DOI:
https://doi.org/10.26418/jp.v10i2.73447Keywords:
Pengenalan Wajah, Setengah Wajah, Xception, Convolutional Neural Network (CNN)Abstract
Penggunaan teknologi pengenalan wajah merupakan cara untuk mengidentifikasi seseorang berdasarkan ciri-ciri wajah. Penelitian ini berfokus pada pengenalan setengah wajah bagian atas dalam kondisi dimana hanya setengah wajah tersebut yang dapat diakses atau terlihat. Menggunakan metode yang melibatkan arsitektur Xception pada Convolutional Neural Network (CNN) untuk mengekstraksi fitur kompleks dari setengah wajah, termasuk dahi, alis dan mata. Data yang digunakan berasal dari absensi karyawan, termasuk 1020 dataset wajah tidak menggunakan masker dan 114 dataset wajah yang menggunakan masker. Penelitan ini menggunakan skenario pembagian data latih dan data uji dengan rasio 95:5, 90:10, 85:15, dan 80:20. Hasil penelitian menunjukkan nilai accuracy, precission, recall, dan f1-score terbaik terdapat pada pembagian data 95:15 yang masing-masing bernilai 95%, 96%, 96%, dan 95%. Hasil ini dapat digunakan untuk kontribusi pengembangan model pengenalan wajah dengan akurasi yang tinggi terutama dalam situasi di mana hanya informasi sebagian wajah yang dapat diakses.References
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