000			02686nam a22003257a 4500
003			OSt
005			20250403172349.0
008			250403b |||||||| |||| 00| 0 eng d
040			_aTUPM _bEnglish _cTUPM _dTUPM _erda
050			_aBTH QA 76.9 _bD43 2023
100			_aDe Castro, Ceejay B. _eauthor
245			_aFace Recognition Attendance System for Students of Electronics Department in College of Industrial Technology of Technological University of the Philippines _cCeejay B. De Castro, Nick Jade B. Pacun, Russel D. Pagatpatan, Erwin Sabas and Joshua Daniel D. Villarosa.--
260			_aManila: _bTechnological University of the Philippines _c2023
300			_axiii 125pages _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege of Industrial Technology.-- _bBachelor of Engineering Technology major in Computer Engineering Technology _cTechnological University of the Philippines _d2023.
504			_aIncludes bibliographic references and index.
520			_aAttendance recording is a regular task for students attending universities and colleges. Most college classes make use of written attendance methods for the students’ and professors’ record. The method of manually monitoring attendance possesses various drawbacks, such as being time-consuming, prone to errors, and susceptible to loss of copy. This study aims to develop an alternative attendance method that utilizes Artificial Intelligence and face recognition technology. The researchers were able to design and develop a user-friendly user interface for students, professors, and administrators that will use the system. And a system prototype that is built for user interaction such as web camera and a touch-screen monitor. By conducting the test procedure among the students of ESET department of Technological University of the Philippines, the researchers were able to identify the system’s face recognition accuracy, with a total computed accuracy of 77% and an equivalent descriptive interpretation of “Very Good” based on Likert Scale Interpretation. On the other hand, the evaluation result shows that the system is considered functional, performance efficient, user-friendly, and secured as it yielded a total average score of 4.75 or 95%, interpreted as “Excellent”.
650			_2Computer Engineering Technology
650			_2Face Recognition
650			_2attendance system
700			_aPacun, Nick Jade B. _eauthor
700			_aPagatpatan, Russel D. _eauthor
700			_aSabas, Erwin _eauthor
700			_aVillarosa, Joshua Daniel D. _eauthor
942			_2lcc _cBTH CIT _n0
999			_c29658 _d29658