Sistem Pengenalan Wajah Menggunakan Algoritma Haarcascade dan Local Binary Pattern Histogram
Sistem Pengenalan Wajah Menggunakan Algoritma Haarcascade dan Local Binary Pattern Histogram
DOI:
https://doi.org/10.26594/teknologi.v13i2.3931Abstract
Kedisiplinan jam kerja setiap karyawan dapat mempengaruhi perkembangan bisnis. Namun, semakin banyaknya tindakan tidak disiplin yang dilakukan oleh karyawan berdampak pada penurunan produktivitas yang mengakibatkan kerugian bagi perusahaan. Untuk memantau dan mendata kehadiran karyawan dalam bekerja, maka dibuatlah sebuah sistem monitoring penyimpangan jam kerja karyawan dengan metode face detection dan face recognition menggunakan algoritma Haarcascade dan LBPH, sebagai solusi untuk mengatasi masalah penyimpangan jam kerja yang sering terjadi di beberapa perusahaan. Sebelum sistem dapat digunakan, akan dilakukan pengujian terhadap algoritma haarcascade dan LBPH, face recognition dan face detection. Data wajah terdiri dari 1900 sampel, dengan 1827 di antaranya telah terverifikasi. Data testing wajah berjumlah 372 sampel, dan memiliki tingkat akurasi sebesar 96,51%. Dengan menggunakan sistem monitoring pengenalan wajah karyawan ini, Pengujian deteksi wajah menghasilkan akurasi 75%.diharapkan sistem ini dapat digunakan sebagai sistem absensi di perusahaan, sekolah dll. Mengembangakn model kedalam bentuk yang compact seperti cctv, dan lain-lain. Membuat model terdeteksi dari sudut manapun dan dapat mengidentifikasi data wajah untuk membedakan wajah 3D dan 2D agar dapat menjadi sistm absensi untuk perusahaan dapat dengan mudah mengatur dan memantau kehadiran karyawan, serta memastikan karyawan tidak melakukan penyimpangan jam kerja. Selain itu, juga memudahkan proses pengelolaan data karyawan, sehingga dapat meningkatkan efisiensi dan produktivitas perusahaan.
Kata Kunci: face recognition, haarcarcade, LBPH, face detection
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