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All Journal Journal of Islamic Pharmacy Journal of Islamic Medicine International Journal of Informatics and Computation Jurnal Pengembangan Sistem Informasi dan Informatika J-Intech (Journal of Information and Technology) Prosiding Seminar Nasional Inovasi Teknologi Terapan Journal Of Artificial Intelligence And Software Engineering Jurnal Inovasi Teknologi Terapan Journal of Technology and Engineering
Evvin Faristasari
Politeknik Manufaktur Negeri Bangka Belitung
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Library & Information Science Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences

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Journal : J-Intech (Journal of Information and Technology)

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Preventive Attendance Record using Photo from Mobile Phone and Printed Paper using CNN Wisesa, Bradika Almandin; Mahat Putri, Vivin; Faristasari, Evvin; Jasman Duli, Sirlus Andreanto; Agustin, Silvia
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1927

Abstract

Face-based attendance systems are increasingly popular for their ease of use, but they are susceptible to fraud, such as using photos or videos for unauthorized attendance. This study introduces a digital attendance system that combines facial recognition with liveness detection powered by Convolutional Neural Networks (CNN). Liveness verification is achieved by analyzing subtle movements and responses to ambient lighting. The dataset includes 30 facial images, encompassing both authentic and fraudulent samples. Testing demonstrates a facial recognition accuracy of 91.3% and effective spoofing detection in static and dynamic settings. This system provides a secure, fraud-resistant attendance solution ideal for educational and corporate settings. Further enhancements are suggested to improve performance across diverse facial expressions and lighting conditions.
Co-Authors Abd. Rasyid Syamsuri Ade Putra Maulana Ade Amin, Fita Avrista Vilusi Better Swengky Bradika Almandin Wisesa Daniel, Rodo Enggar Hero Istoto Fadila, Resma Hero Istoto, Enggar Indra Irawan Jasman Duli, Sirlus Andreanto Lionza, Rahmat Peprizal, Peprizal Putri, Vivin Mahat Silvia Agustin Silvia Agustin Sirlus Andreanto Jasman Duli Sukma, Shafril Muliawan Wathan, M.Hizbul Yudhi