RANCANGAN BANGUN SISTEM ABSENSI BERBASIS WEB MENGGUNAKAN TEKNOLOGI PENGENALAN WAJAH DENGAN LIBERARY OPEN CV PADA FRAME WORK LARAVEL

BHINEKTA WAHYUNI DELE, NPM 2208100017 (2026) RANCANGAN BANGUN SISTEM ABSENSI BERBASIS WEB MENGGUNAKAN TEKNOLOGI PENGENALAN WAJAH DENGAN LIBERARY OPEN CV PADA FRAME WORK LARAVEL. Skripsi thesis, Universitas Labuhanbatu.

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Abstract

Perkembangan teknologi informasi telah mendorong berbagai instansi untuk memanfaatkan sistem digital dalam meningkatkan efektivitas dan efisiensi kerja, termasuk pada proses absensi. Penelitian ini bertujuan untuk merancang dan membangun sistem absensi berbasis Face Recognition menggunakan metode Haar Cascade Classifier dan Local Binary Pattern Histogram (LBPH). Sistem dikembangkan menggunakan framework Laravel, bahasa pemrograman PHP, database MySQL, dan library OpenCV. Metode Haar Cascade Classifier digunakan untuk mendeteksi wajah pengguna secara real-time, sedangkan metode Local Binary Pattern Histogram (LBPH) digunakan untuk mengenali identitas pengguna berdasarkan karakteristik wajah yang telah tersimpan dalam database. Pengembangan sistem dilakukan dengan metode Waterfall yang meliputi tahapan analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Pengujian sistem menggunakan metode Black Box Testing menunjukkan bahwa seluruh fitur, seperti login, registrasi wajah, proses absensi, pengelolaan data pengguna, rekapitulasi, dan pembuatan laporan absensi, dapat berjalan sesuai dengan fungsinya. Hasil penelitian menunjukkan bahwa sistem absensi berbasis Face Recognition mampu meningkatkan kecepatan, ketepatan, keamanan, serta efisiensi dalam proses pencatatan kehadiran, sekaligus meminimalkan terjadinya kesalahan pencatatan dan praktik titip absen yang sering terjadi pada sistem absensi konvensional. Kata Kunci: Sistem Absensi, Face Recognition, Haar Cascade Classifier, Local Binary Pattern Histogram (LBPH), OpenCV, Laravel =============================================================================== The development of information technology has encouraged various institutions to adopt digital systems to improve work effectiveness and efficiency, including attendance management. This study aims to design and develop a Face Recognition-based attendance system using the Haar Cascade Classifier and Local Binary Pattern Histogram (LBPH). The system was developed using the Laravel framework, PHP programming language, MySQL database, and the OpenCV library. The Haar Cascade Classifier method was applied to detect users‟ faces in real time, while the Local Binary Pattern Histogram (LBPH) method was used to recognize user identities based on facial characteristics stored in the database. The system was developed using the Waterfall method, which consists of requirement analysis, system design, implementation, testing, and maintenance. System testing was conducted using the Black Box Testing method, and the results showed that all features, including login, face registration, attendance recording, user data management, attendance recap, and report generation, functioned properly. The results indicate that the proposed Face Recognition-based attendance system improves the speed, accuracy, security, and efficiency of attendance recording while minimizing recording errors and preventing attendance fraud commonly found in conventional attendance systems. Keywords: Attendance System, Face Recognition, Haar Cascade Classifier, Local Binary Pattern Histogram (LBPH), OpenCV, Laravel

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	Sistem Absensi, Face Recognition, Haar Cascade Classifier, Local Binary Pattern Histogram (LBPH), OpenCV, Laravel=================Attendance System, Face Recognition, Haar Cascade Classifier, Local Binary Pattern Histogram (LBPH), OpenCV, Laravel
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Divisions:	Fakultas Sains Dan Teknologi > Teknologi Informasi
Depositing User:	Unnamed user with email repository@ulb.ac.id
Date Deposited:	04 Sep 2026 03:04
Last Modified:	04 Sep 2026 03:04
URI:	http://repository.ulb.ac.id/id/eprint/2747

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