Rancang Bangun Mesin Presensi berbasis Metode Pengenalan Wajah HoG berbantuan Proses Klasifikasi Linear SVM

Samuel Matthew, Ferry Rippun Gideon Manalu, Nova Eka Budiyanta

Abstract


Di dalam daerah perkantoran, salah satu benda yang sering disentuh adalah alat presensi/pencatat kehadiran. Studi ini bertujuan untuk menerapkan sistem presensi berbasis metode pengenalan wajah menggunakan Raspberry Pi dan kamera dilengkapi dengan sensor pendeteksi suhu tubuh berbantuan aplikasi web. Pendekatan pengenalan wajah yang dilakukan dalam studi ini adalah Histogram of Oriented Gradients (HoG) didukung dengan linear Support Vector Machine (SVM). Hasil yang didapatkan dalam studi ini berupa sebuah mesin presensi yang mampu mengenali wajah pengguna yang sudah terdaftar dengan tingkat akurasi sebsar 98% pada 43,02 frame per detik (idle) dan 2,90 frame per detik (aktif) dengan menggunakan dataset berisikan 20 data tiap wajah (20 data x 20 wajah = 400 data). Sensor yang digunakan dapat mengukur suhu dengan akurasi ±0,5°C. Daftar kehadiran dapat diakses oleh pihak yang berkepentingan melalui situs web yang menampilkan data dari basis data. Untuk menanggulangi kesalahan sistem pada saat uji coba, presensi secara manual dapat dilakukan melalui aplikasi berbasis web.

Keywords


Pengenalan Wajah, Histogram of Oriented Gradients, Linear Support Vector Machine, OpenCV, Raspberry Pi, Sistem Presensi

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DOI: https://doi.org/10.30591/jpit.v7i1.2843

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