Students' Attendance Monitoring System with SMS Notification

Bakhri, Fatheenursyaza; Ekhsan, Hawa Mohd; Hamid, Jiwa Noris

doi:10.24191/jcrinn.v5i1.159

Cited by 3 publications

(2 citation statements)

References 1 publication

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“…The aforementioned software-based system focused on the Short Message Service (SMS) notification to monitor student absenteeism based on the percentage of attendance allowed by the university [16]. The system will send SMS notifications automatically to the parents and students in order to assist the Academic Affairs Division (ADD) to manage the warning letters issued by the lecturer.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Smart Attendance for Faculty Monitoring System Using the Bluetooth Low Energy: Design and Implementation

Jantan¹,

Rasli²,

Zainudin³

et al. 2022

Preprint

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Student attendance serves many other important purposes aside from monitoring. In certain universities, the attendance of students in a course is also used as one of the requirements for students to be allowed to sit for the final examination. Traditionally, among most Malaysian Institutions of Higher Learning (IHL), attendance recording is usually done using pen and paper, or uses simple web-based system that is time consuming and difficult for faculty periodic monitoring. To address the identified drawbacks, this research aims to develop a Smart Attendance for Faculty Monitoring System using the Bluetooth Low Energy (BLE) technology to assist faculty in recording, managing and monitoring students’ attendance and class schedules effectively. The system is developed for Android-based devices using an agile methodology consists of iteration and incremental approaches. Thus, to evaluate the effectiveness of the system, a survey was conducted on 140 respondents involving lecturers and students of Kolej Universiti Poly-Tech MARA (KUPTM). Respondents were selected using purposive sampling. The descriptive analysis showed that 87.9% of the respondents strongly agreed that the system is effective in assisting lecturers to record attendance, manage class schedules and student attendance as well as to assist faculty in monitoring students’ absenteeism.

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Smart Attendance for Faculty Monitoring System Using the Bluetooth Low Energy: Design and Implementation

Jantan¹,

Rasli²,

Zainudin³

et al. 2022

Preprint

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“…Accurate and timely attendance records are fundamental for identifying student absenteeism, serving as a crucial component in promoting student retention and academic achievement [1]. By meticulously tracking attendance, educators can readily implement necessary interventions for atrisk students, facilitating their academic success.…”

Section: Introductionmentioning

confidence: 99%

Monitoring Student Attendance Through Vision Transformer-based Iris Recognition

Ennajar,

Bouarifi

2024

IJACSA

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In the context of the ongoing digital transformation, the effective monitoring of student attendance holds paramount significance for educational establishments. This study presents an innovative approach using Vision Transformer technology for iris recognition to automate student attendance tracking. We fine-tuned Vision Transformer models, specifically ViT-B16, ViT-B32, ViT-L16, and ViT-L32, using the CASIA-Iris-Syn dataset and focused on overcoming challenges related to intra-class variation through data augmentation techniques, including rotation, shearing, and brightness adjustments. The results reveal that ViT-L16 is the most proficient, achieving an impressive accuracy of 95.69%. Comparative analysis with prior methodologies, specifically those employing Vision Transformer with Convolutional Neural Network, underscores the superiority of our proposed ViT-L16 model. This superiority is evident across various metrics, including accuracy, precision, recall, and F1 score. The experimental setup involves the use of Jupyter Notebook, Python technologies, TensorFlow, and Keras, emphasizing evaluations based on loss, accuracy, and Confusion Matrix. ViT-L16 consistently outshines other models, showcasing its resilience in iris recognition for student attendance. This research marks a significant step towards modernizing attendance systems, offering an accurate and automated solution suitable for the evolving needs of educational settings. Future work could explore integrating additional biometric modalities and refining Vision Transformer architecture for enhanced performance and broader application in educational environments.

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Taxonomy of Intelligent Attendance Systems

Hasan

2024

Communications in Computer and Information Science

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Students' Attendance Monitoring System with SMS Notification

Cited by 3 publications

References 1 publication

Smart Attendance for Faculty Monitoring System Using the Bluetooth Low Energy: Design and Implementation

Smart Attendance for Faculty Monitoring System Using the Bluetooth Low Energy: Design and Implementation

Monitoring Student Attendance Through Vision Transformer-based Iris Recognition

Taxonomy of Intelligent Attendance Systems

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