A Formal Research Study on Correlating Student Attendance to Student Success

The student <span>attendance system is what is needed in the process of recording attendance in learning and the development of student achievement. Currently several modern educational institutions have implemented a student attendance system using QR codes or fingerprints, but many still use the traditional system by calculating the number of students attending class. Based on these problems, the solution that can be given is to implement a student attendance system through face matching in the Android mobile application with Eigenface algorithm and support vector machine (SVM) algorithm. Eigenface using the principal component analysis (PCA) method can be used to reduce the dimensions of facial images so that they produce fewer variables and are easier to handle. The results obtained are then entered into a pattern classifier to determine the identity of the owner of the face. This study used 100 facial data as test data and training data. The system test results show that the use of Eigenface with SVM as a classifier can provide a fairly high level of accuracy. For facial images that were included in the training, 91% of the identification was correct.</span>

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“…To simplify equation ( 1) must be transformed into the Lagrange Multiplier function itself, so that (1) becomes (3).…”

Section: Methodsmentioning

confidence: 99%

“…One of the factors that influence student learning success is their presence [3], [4]. Student attendance is used as a requirement to take exams at several universities [5].…”

Section: Introductionmentioning

confidence: 99%

Implementation of eigenface method and support vector machine for face recognition absence information system

Annubaha

Widodo

Adi

2022

IJEECS

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show abstract

“…Regular lecture attendance is typically expected from college students. Indeed, as the findings presented in [1], [2], and [3] demonstrate, there is a positive correlation between regular attendance and the student's grades.…”

Section: Introductionmentioning

confidence: 80%