IMPLEMENTASI LIVENESS DETECTION DAN ALGORITMA LOCAL BINARY PATTERNS HISTOGRAMS (LBPH) PADA SISTEM PRESENSI PEGAWAI BERBASIS WEB (STUDI KASUS: COFFEESHOP ARCHAIC)

Akhtar Ramadhan Putra, . (2026) IMPLEMENTASI LIVENESS DETECTION DAN ALGORITMA LOCAL BINARY PATTERNS HISTOGRAMS (LBPH) PADA SISTEM PRESENSI PEGAWAI BERBASIS WEB (STUDI KASUS: COFFEESHOP ARCHAIC). Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Attendance management at CoffeeShop Archaic is currently manual, leading to inefficiency in data recapitulation and vulnerability to "buddy punching" fraud. This research aims to build an accurate and secure web-based attendance system using face recognition technology. The system was developed using the Waterfall method, Python programming language, and Flask framework. The Haar Cascade Classifier algorithm is used for face detection, while Local Binary Patterns Histograms (LBPH) is applied for identity recognition due to its efficiency. To prevent attendance fraud using photos, the system is equipped with a Liveness detection feature that detects eye blinks and facial movements. Test results show that the system successfully recognizes employee faces, effectively rejects spoofing attempts using photos, and accelerates the monthly attendance report recapitulation process to be more efficient and transparent.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 2110511166] [Pembimbing 1: Ati Zaidiah] [Pembimbing 2: Nur Hafifah Matondang] [Penguji 1: Jayanta] [Penguji 2: Hamonangan Kinantan Prabu]
Uncontrolled Keywords: Face recognition, LBPH, Liveness detection
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: AKHTAR RAMADHAN PUTRA
Date Deposited: 10 Sep 2026 01:26
Last Modified: 10 Sep 2026 01:26
URI: http://repository.upnvj.ac.id/id/eprint/52075

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