TY  - BOOK
AU  - Lustre, Marc Vien L., author.
AU  - Pangilinan, Jasmin Shin D., author.
AU  - Combinido, Lucky B., author.
AU  - Estonilo, Christopher G., adviser.
AU  - Ramos, Dann Patrick G., technical critic.
TI  - FRAMS : Face Recognition Attendance Management System of Cavite State University - CCAT / 
AV  - UM TA 1650  L87 2019
PY  - 2019///
CY  - Rosario, Cavite
PB  - Cavite State University-CCAT Campus
KW  - Face recognition
KW  - Image processing
KW  - Computer vision
KW  - Human face recognition ( Computer Science )
KW  - Biometric identification
KW  - Attendance Management System
N1  - An Undergraduate Thesis (BSCS) -- Cavite State University-CCAT Campus, 2019; Includes bibliographical references and appendices
N2  - LUSTRE, MARC VIEN L., PANGILINAN, JASMIN SHIN D., COMBINIDO, LUCKY B.FRAMS: Face Recognition Attendance Management System Using Image Processing for Cavite State University  CCAT. Cavite State University - CCAT, Rosario, Cavite. May 2019. Adviser: Prof. Christopher G. Estonilo.

The study was conducted from August 2018 to April 2019 to improve the class monitoring system using FRAMS or Face Recognition Attendance Management System The general objective of the study was to improve the class attendance monitoring system in Cavite State University - CCAT Specifically, the study aimed to: 1) design and develop the class attendance monitoring system in Cavite State University- CCAT, which is capable of entering the class information of the instructor, scanning. training and testing the face of students belong to the class, recognizing the face of students presents in the class, and providing reports of class attendance, 2) evaluate the system using ISO-IE 25010 software evaluation standards, and3) prepare an implementation plan for the deployment of the system in the Department of Computer Studies

The system analysis and design of FRAMS applied the rapid application development or RAD software development model which was composed of requirement analysis, user design (prototype, test, refine), construction, and cut over

The mobile application was evaluated by five (5) IT experts and (15) general end- user in the campus It gained a mean of 4.52 and described as Excellent for the IT experts. On the other hand, it gained a mean of 4.6 and also described as Excellent for the end-users
ER  -