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All Journal Prosiding Semnastek JOIV : International Journal on Informatics Visualization Network Engineering Research Operation [NERO] Jurnal Pengabdian Teknologi, Ekonomi dan Humaniora Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Journal Technology Information and Data Analytic
Timor Setiyaningsih
Universitas Darma Persada
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences Other

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Perancangan Aplikasi Absensi dan Pengawasan Ruangan dengan Pengenalan Wajah menggunakan metode Convolutional Neural Network Nurpadilah, Rizki; Setiyaningsih, Timor
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.81

Abstract

The development of technology in the field of facial recognition provides a great opportunity to improve efficiency and security in various aspects, one of which is the attendance and room surveillance system. This study aims to design an attendance and room surveillance application based on facial recognition using the Convolutional Neural Network (CNN) method in a private company engaged in the property sector. This application is designed to simplify the employee attendance process and improve room surveillance by automatically recognizing employee faces, thereby reducing the risk of attendance fraud and ensuring more accurate attendance. The CNN method was chosen because of its ability to process images and recognize facial patterns with high accuracy. This system consists of several main features, namely employee face registration, automatic face-based attendance, and monitoring employee presence in the office space. The test results show that this application is able to identify faces with a good level of accuracy, as well as provide convenience and comfort for users.
Co-Authors Adam Arif Budiman Aji Setiawan Aji Setiawan Astuti, Eka Yuni Atik Kurnianto Azmi, Mohd Sanusi Budi Sumartono Draman, Azah Kamilah Eka Yuni Astuti Eva Novianti Gusti Rinanjar Herianto Iis Mawati, Anggy Isniah, Sarah Musyaffa, Luth Fais Mutiara Nur Afifah Nur Afifah, Linda Nur Hasanah Nur Syamsiah Nurpadilah, Rizki Ratih Dwilestari Rikhi, Muhammad S.Pd., MT, Herianto Suzuki Syofian Triwibowo Triwibowo Triwibowo, Triwibowo Wiwin Mafiroh yefri chan