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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi SALEE: Study of Applied Linguistics and English Education Jurnal PRIMED:Primary Education Journal atau Jurnal Ke-SD An JUSIFOR : Jurnal Sistem Informasi dan Informatika
Tasaufi, Bila Nastiti
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Journal : METHOMIKA: Jurnal Manajemen Informatika

 1 
RANCANG BANGUN APLIKASI PENGENALAN WAJAH UNTUK SISTEM PRESENSI DI PRODI TEKNIK INFORMATIKA UNIVERSITAS ISLAM RADEN RAHMAT MALANG MENGGUNAKAN METODE LBPH DAN LIBRARY OPENCV BERBASIS ANDROID Wulandari, Gresy Ayu; Akbar, Muhammad Sonhaji; Tasaufi, Bila Nastiti
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp247-253

Abstract

The attendance system is a mechanism to record the attendance of students in each class they take. The attendance system serves as evidence of students' presence in the learning process. In its journey, Universitas Islam Raden Rahmat has been using manual attendance through attendance journals in the learning process. However, with technological advancements, the attendance process has followed this trend, one of which is face recognition. In this research, the researcher designed a face recognition application for the attendance system that can be implemented on mobile platforms, especially Android. This application using the Local Binary Pattern Histogram (LBPH) method and the OpenCV library. The objective of this application is to enhance the flexibility and efficiency of the current attendance system by eliminating the need to repeatedly retrieve attendance forms, preventing fraud, and reducing paper usage. By using the waterfall system development method, testing showed a face recognition accuracy of 70%
Co-Authors Ainun Nikmah Akbar, Muhammad Sonhaji Choirina, Priska Cipta, Bagus Seta Inba Herwiana, Sakhi Novitasari, Nine Febrie PANGESTUTI PRIMA DARAJAT Rahmawati, Zurriat Nyndia Ramadhan, Robby Wahyu Urnika Mudhifatul Jannah, Urnika Mudhifatul Wulandari, Gresy Ayu Zamzami, Ana Zamzami, Muhammad Rizal Akbar