Attendify: development of facial recognition attendance monitoring system for faculty members using multi-task cascade convolutional neural networks (mtcnn) in computer studies department at tup-manila/ Romar N. Dela Peña, John Michael C. Llosa, and Edzel B. Olaer.--

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Dela Peña, Romar N [author]

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TextPublication details: Manila: Technological University of the Philippines, 2025.Description: x, 125pages: 29cmContent type:

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BTH QA 76 D45 2025

Dissertation note: College Of Science.-- Bachelor of science in computer science: Technological University of the Philippines, 2025. Summary: This study introduces Attendify, a system that uses facial recognition to help track faculty attendance in the Computer Studies Department of the Technological University of the Philippines-Manila. Using the MTCNN algorithm, the system provides a quick, accurate and touchless way to replace fingerprint-based identification. The system was developed using PHP, MySQL, HTML and JavaScript and it utilized the formal steps of planning, developing, testing and evaluation. The results showed that Attendify was rated "Highly Acceptable" in ISO 25010 software quality metrics which means it is appropriate, usable, reliable, secure and efficient. The system solved issues with manual errors and paperwork, allowing Attendify to grow and be trusted for future improvements in education attendance systems.

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Holdings
Item type	Current library	Shelving location	Call number	Copy number	Status	Date due	Barcode
Bachelor's Thesis COS	TUP Manila Library	Thesis Section-2nd floor	BTH QA 76 D45 2025 (Browse shelf(Opens below))	c.1	Not for loan		BTH0006619

Bachelor's thesis

College Of Science.--
Bachelor of science in computer science: Technological University of the Philippines,
2025.

Includes bibliographic references and index.

This study introduces Attendify, a system that uses facial recognition to help track
faculty attendance in the Computer Studies Department of the Technological University of
the Philippines-Manila. Using the MTCNN algorithm, the system provides a quick,
accurate and touchless way to replace fingerprint-based identification. The system was
developed using PHP, MySQL, HTML and JavaScript and it utilized the formal steps of
planning, developing, testing and evaluation. The results showed that Attendify was rated
"Highly Acceptable" in ISO 25010 software quality metrics which means it is appropriate,
usable, reliable, secure and efficient. The system solved issues with manual errors and
paperwork, allowing Attendify to grow and be trusted for future improvements in education
attendance systems.

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