Attendance Record Research Articles

Maternal perinatal anxiety and infant primary care use in 1998–2016: a UK cohort study

BackgroundThere is some evidence that perinatal anxiety (PNA) is associated with lower rates of infant vaccinations and decreased access to preventative infant healthcare, but results across studies have not been...

Revolutionizing Classroom Attendance: A Wireless Smart System Using ESP-NOW Protocol

In an era where technological advancements drive improvements across various sectors, enhancing efficiency in educational management systems is crucial. This paper presents a novel wireless attendance system that leverages the ESP-NOW protocol, which offers advantages over traditional Wi-Fi by enabling low-power, low-latency, and direct device-to-device communication without the need for an intermediary network. The system employs ESP32 modules configured as both slave and master devices. Slave devices, positioned on the lecturer’s desk, interact with students' smartphones when the lecturer initiates the class, while master devices, strategically placed at multiple locations within the classroom, compile and consolidate attendance data for each room. The system incorporates RSSI-based restrictions via the ESP-NOW protocol to prevent overlapping attendance between rooms and ensure that students can only record their presence if they are physically within the designated classroom. Attendance data is automatically logged and made accessible in real-time through a dedicated mobile application for lecturers. Empirical testing demonstrates 100% accuracy in attendance recording, with an average verification time of less than 1 second and a data transmission rate ranging from 700 to 800 Bytes/seconds.

A Fingerprint based Students attendance System with SMS alert to Parents

Technological developments in the domains of electronics and telecommunication have led to an expanding variety of arrangements in the home and office. This project presents the design methodology for a mobile fingerprint-based student attendance system that utilizes a global system for mobile communication (GSM) technology. This course of study mostly entails matching fingerprints based on the number of minute pairings between two fingerprints and extracting minutiae points from model fingerprint pictures. The system has an attendance module and a terminal for collecting fingerprints. It is capable of autonomously carrying out tasks like fingerprint data collection and processing as well as wireless communication, creating an attendance record, and matching fingerprints. Following the attendance check, Through GSM, this technology transmits each student’s attendance to their parent’s mobile device. An attendance system makes it easier to obtain a specific student’s attendance for a given class. This effort heralds a new era for parent alerts and student security.

Implementation of a Web-Based Student and Teacher Attendance System With QR Code Integration using the RAD

This study aims to implement a web-based student and teacher attendance system with QR Code integration at SMK Muhammadiyah Campaka, Purwakarta. Currently, the school still uses a manual attendance system that is proven to be inefficient, time-consuming, prone to human error, and difficult to monitor in real-time. The proposed system is expected to overcome these problems by increasing the efficiency of managing and monitoring student attendance data. The Rapid Application Development (RAD) approach is used in developing this system, which allows for a faster and more flexible development process. QR Code was chosen as the attendance method because it can speed up attendance recording and reduce data input errors. The results showed that the new system succeeded in reducing attendance recording time by 50%, from an average of 10 minutes to only 5 minutes per class. In addition, the recording error rate was reduced by more than 70%, from the previous 36% to only 9% after the system was implemented. This system also allows attendance reports that can be accessed in real-time, supporting increased efficiency in the school environment. With the implementation of this system, it is hoped that the attendance process will be faster, more accurate, and easier to monitor, which in turn can improve the quality of education management at SMK Muhammadiyah Campaka.

SMART ATTENDANCE WITH FACE ANTI-SPOOFING TECHNOLOGY USING HAAR CASCADE CLASSIFIER

Traditional attendance systems often encounter challenges in efficiently and accurately recording attendance. This research aims to introduce an innovative solution through the development of an intelligent anti-spoofing attendance system based on facial recognition using the Haar Cascade Classifier method. Designed to overcome the inefficiencies in attendance recording, this system ensures the accuracy of educational staff attendance records. Its development method relies on the Haar Cascade Classifier, employing image processing to detect learned object features, particularly focusing on facial recognition. Research findings indicate that the implementation of this system achieves an average accuracy rate of 98.90% in attendance recording. The facial recognition technology ensures reliable attendance recording with confidence levels exceeding 80%, signifying precise facial identification that addresses various challenges and ensures attendance data integrity. Not only does the system identify educational staff with high accuracy, but it also provides prompt responses for efficient attendance logging and verification. Beyond its technical benefits, this study significantly contributes to the development of smarter and more efficient attendance technology. The system plays a crucial role in enhancing the discipline of educational staff at STMIK IKMI Cirebon and streamlining attendance management and evaluation across educational institutions.

Development on Mechatronics Based RFID Attendance System with Artificial Intelligence

An RFID attendance system is a system that uses radio frequency identification (RFID) technology to track and record attendance. RFID tags are small electronic devices that store a unique identifier. When an RFID tag is brought near an RFID reader, the reader can read the identifier and send it to a computer. The computer can then use the identifier to look up the corresponding person's attendance record. An RFID attendance system is an automated system that uses RFID (Radio Frequency Identification) technology to track and record employee attendance. It consists of two main components: RFID tags and RFID readers. RFID tags are small electronic devices that store a unique identifier. They are typically attached to employee badges or cards. RFID readers are devices that can read the unique identifiers stored on RFID tags. They are typically installed at entry points to buildings or rooms. When an employee enters a building or room, they must present their RFID badge or card to an RFID reader. The reader will read the unique identifier stored on the tag and send it to a computer. The computer will then use the identifier to look up the employee's attendance record. If the employee is not already clocked in, they will be clocked in. If the employee is already clocked in, they will be clocked out.

Development Of A Web-Based E-Presence Application For Tracking Maps And Selfies Using Laravel

Attendance is an activity aimed at assessing the level of employee presence and discipline within an organization or company. The E-Presence application is developed as a tool to enhance efficiency, accountability, and transparency in employee attendance, as well as to facilitate the processing of attendance data The E-Presence application aims to reduce errors and improve the accuracy of employee attendance records, which are crucial for the decision-making process. The development of the E-Presence application uses the Laravel framework, MySQL database, and UML (Unified Modeling Language) tools to design Use Case Diagrams, Activity Diagrams, and Class Diagrams. The system development method follows the waterfall model, and Black Box Testing is employed as the testing method. The urgency of this research lies in the system's ability to perform real-time attendance tracking that can be conducted outside the office within a maximum distance of 20 meters. With the implementation of tracking maps, employees do not need to queue, thereby increasing work efficiency. Attendance recording can be done in real time, is flexible, easily accessible, improves efficiency in attendance recording, reduces the potential for errors, enhances human resource management, and provides attendance reports in Excel format. The novelty of this research is the development of a web-based application that incorporates Tracking Maps and Selfie features, ensuring that employees must be in a designated area to check in. Thus, the company/organization can easily analyze and evaluate employee discipline. The testing results indicate that the application functions well and meets user needs.

An Automated Face Detection and Recognition for Class Attendance

Class attendance is a crucial indicator of students' seriousness towards learning. Many institutions continue to use manual methods, which are usually error-prone and unproductive. By leveraging computer vision algorithms, the system accurately captures and verifies the identity of students attending class. This paper aims to investigate and create an automated facial recognition system for classroom attendance to increase the precision and effectiveness of the attendance tracking system. To achieve this, we propose a system using computer vision technologies, namely Histogram of Oriented Gradients (HOG) with Support Vector Machine (SVM) for face detection and deep Convolutional Neural Networks (CNN) for face identification. The facial recognition system simplifies attendance recording, requiring participants to only gaze into the camera for the system to record their presence automatically. The system is rigorously tested and evaluated, and its accuracy is compared to our institution's current QR code attendance method. The study results reveal that the recommended approach is more accurate and competent than the existing procedures. The system allows for precise attendance records with real-time face detection and recognition capabilities. This technology ensures accurate and reliable attendance data, empowering organizations to make informed decisions, effectively manage resources, and provide a seamless experience for all students. In addition, a similar attendance system can be deployed for any event in an organization, thereby enhancing overall operational efficiency.

ANALISIS PENERAPAN SISTEM INFORMASI AKUNTANSI PENGGAJIAN NON ASN DAN PENGENDALIAN INTERNAL DALAM UPAYA MENINGKATKAN KINERJA PEGAWAI PADA DINAS PERDAGANGAN DAN PERINDUSTRIAN KABUPATEN SUKABUMI

Payroll Accounting Information System and Internal Control are important aspects in managing a government agency because a good payroll accounting information system and internal control can provide accurate information and avoid errors in payroll so that it can improve employee performance. The type of research used is a qualitative descriptive method, the data processed is the result of unstructured interviews and observations that will be analyzed qualitatively and described in descriptive form. The results of the study show that the implementation of the Non ASN payroll accounting information system and internal control has been running well in improving employee performance. However, the Sukabumi Regency Trade and Industry Service needs to improve the attendance recording system which is still done manually as one of the weaknesses that needs to be improved into a computerized system to avoid fraud. In addition, internal control related to organizational structure also needs to be improved to separate the performance of employee tasks and functions more effectively and add human resources in several parts to prevent a decline in performance

Sistem E-Presensi Berbasis Web Dengan Kode QR di SMK Negeri 2 Cimahi

The web-based e-Attendance system with QR Code at SMK Negeri 2 Cimahi enhances student attendance monitoring digitally. By integrating QR Code technology, students easily record their attendance by scanning a QR Code on the attendance page. The system’s key advantage is automatic attendance recording, providing real-time access for teachers and administrative staff. The user-friendly interface ensures accurate monitoring and efficient data management, minimizing errors and offering a precise understanding of student attendance. The implementation of QR Code technology has improved administrative efficiency and reduced errors, leading to better insights into student attendance. Data analysis enables teachers to take appropriate actions to enhance student engagement, fostering a more responsive learning environment. Overall, the e-Attendance system significantly optimizes student attendance management in the digital era.

Applying Biometric Technology in School Attendance and Security Management

In today's digital era, security and efficiency in attendance management in the school environment are very important. Biometric technology has become a new trend in improving security and optimizing the attendance recording process, replacing manual systems prone to errors and fraud. This research aims to analyze the effectiveness of applying biometric technology in school attendance and security management. Specifically, this research focuses on evaluating how this technology can reduce cheating, increase the accuracy of attendance data, and strengthen school security systems. This research uses quantitative methods with a case study approach at five schools implementing a biometric system. Data was collected through surveys of school administrators and direct observation of the registration and identity verification processes at these schools. Data analysis was carried out using descriptive and inferential statistics. This research shows that using biometric technology significantly increases the efficiency and accuracy of the attendance recording system. Student attendance is recorded quickly and accurately, with virtually no cheating. This technology also strengthens the security system by ensuring that only verified individuals can access school facilities. This research concludes that applying biometric technology in school attendance and security management has proven very effective. This technology optimizes attendance and improves security, providing a safe environment for students and staff. The research recommends wider adoption of biometric technology in other schools to improve security and operational efficiency.

Face Recognition Based Attendance System using ESP 32CAM

Abstract: In the modern industrial system, attendance logging is essential to raising system quality. Thus, it is necessary to have a robust computerized Face detection attendance recording system that uses an ESP32 camera. Each and every organization has strict attendance policies. It takes time and effort to manually maintain an attendance register. For example, RFID and biometric technology are two ways of solving the same issue. This research outlines a creative and efficient method for determining presence and verifying attendance. The ESP32 microcontroller family features integrated Wi-Fi and dual-mode Bluetooth. This facial detection-based technology does not require a person to be in close proximity to the fingerprint reader module, in contrast to biometric attendance systems. The biometric device becomes contaminated when the same employee or student records their attendance using the same biometric system. Furthermore, the likelihood of a proxy in RFID is considerable. This forecast will track student or employee attendance using facial recognition technology.

Подготовка будущих педагогов для советской трудовой школы: педуклоны в 1920-1930-е г.г. в Оренбуржье

This article highlights and discusses the periods of development of peduklons in the 1920-1930s in the Orenburg region. The features of training future teachers for the Soviet school are revealed. And also the pain points characteristic of schools in 1297 are given, which were identified as a result of a survey of students, namely: a) the monotony of work methods in first-level schools, which discouraged interest in passive practical training; b) little time to study notes, since it was not always possible to get material from the teacher in a week; c) poor participation of trainees in the social work of the first-level school; d) insufficient number of trial lessons; e) the impossibility for everyone to familiarize themselves with the work of 3 and 4 gr. And recommendations are given: “a) contact the school more closely; b) improve relationships between teachers of first-level schools and trainees; c) strengthen work in public organizations of schools; d) increase the number of trial lessons; e) more opportunities on the part of schools for trainees to demonstrate their activity; f) more fully organize the recording of school attendance by trainees; g) allocate one day from the weekly schedule specifically for the workshop, since students have to study without rest after the workshop at their school.” Based on theoretical analysis, a specific curriculum for a labor school of the second stage is presented (using the example of school No. 8 named after Profintern in Orenburg (1928-29 academic year), the practice of organizing education in Orenburg schools that worked according to “pedagogical lines” is considered.

IoT-Integrated Smart Attendance and Attention Monitoring System For Primary and Secondary School Classroom Management

The monitoring of student attendance is a crucial aspect of the assessment of academic performance. The conventional methods for monitoring student attendance have inherent limitations in terms of both time efficiency and accuracy. Consequently, there is a clear need for a more expedient and precise attendance system. The objective of this research is to present the design of a real-time attendance recording and monitoring system for students from elementary school to senior high school, which will be implemented using the concept of the Internet of Things (IoT). The proposed system employs biometric technology in the form of face recognition. The methodology commences with the capture of images of students who leave the classroom during the instructional period via an active camera positioned on the classroom door. The system employs a Convolutional Neural Network (CNN) algorithm and a powerful computer vision tool, OpenCV, to perform real-time face recognition. Teachers will be informed of student absences and returns, as well as at the 15th and 30th minutes. An absence exceeding 30 minutes is classified as truancy. The integration of sophisticated technologies, such as machine learning and image processing, not only enhances the precision of attendance records but also equips educators with an efficient and automated system for streamlining classroom attendance management. This not only optimizes the learning environment but also facilitates more advanced and efficient pedagogical practices.

Optimizing Attendance Management in Educational Institutions Through Mobile Technologies: A Machine Learning and Cloud Computing Approach

The primary goal of the study is to optimize and streamline the attendance recording and monitoring process for learning sessions by leveraging advanced technologies such as machine learning and cloud computing. The methodology employed is based on the extreme programming (XP) project management approach. Throughout its phases, the entire implementation process of the application, from conception to launch, is described in detail. Firebase is used as the database manager to ensure the efficiency and security of student information and attendance records. Additionally, the Firebase machine learning kit is used to verify attendance registration through QR codes. The application was tested with fifth-year high school students from an educational institution. The user interface has been designed to be attractive, intuitive, and easy to use for both teachers and students. The study results demonstrate that the use of this application significantly reduces the time spent on attendance recording compared to traditional methods. There has been a high level of satisfaction and acceptance of the “ASYS” application among teachers and students. In conclusion, this study has successfully implemented a mobile application that revolutionizes attendance recording and monitoring in educational institutions. It harnesses the power of machine learning and cloud computing to enhance efficiency and the user experience.

Facial Recognition Based Attendance System with Cloud-Integrated Data Management

Managing attendance at a place where number of people are more is a challenging task, and likely there are few percent chances of error always there. To solve this problem in this paper we have proposed our Face-recognition based attendance system with cloud integrated data management. Another important thing that is having the record of attendance we have used cloud database to store and record attendance. The database is automatically updated by system developed by PyMongo, so that later that can be also displayed to user via their login onto a dashboard. In this project we have built face recognizer with OpenCV python and Eigenfaces algorithm which uses Principal Component Analysis (PCA) and used MongoDB Atlas, a service of Mongo for hosting the cloud database. We will be using MERN stack for building dashboard on which one can monitor their attendance. Using OpenCV against MATLAB also helps in saving memory and gives higher speed of execution

Automatic Face Recognition Attendance System using Python and Open CV

The primary goal of this project is to develop a face recognition-based attendance monitoring system for educational institutions, aiming to improve and modernize the current attendance procedures, making them more efficient and effective. The existing system suffers from ambiguities that lead to inaccuracies and inefficiencies in attendance recording. Numerous issues arise when authorities cannot enforce the regulations of the old system. This project leverages face recognition technology to address these problems. During attendance sessions, the system will compare faces against a database to verify identities. Once an individual is identified, their attendance will be automatically recorded, with the necessary information in an Excel sheet. This automated system aids faculty in taking attendance for the entire class without causing any disruption or wasting time. We propose and have implemented a smart attendance system with the potential to incorporate Quick Response (QR) codes as a future method for managing attendance. This system aims to streamline and document student attendance during lectures and other activities across all relevant courses. At the end of the day, the Excel sheet containing attendance details for all individuals will be emailed to the respective faculty members.

Facial Feature-Based Attention Tracking System for Enhanced Online Learning Engagement

Recognizing and enhancing student engagement is crucial for improving learning outcomes, particularly in the context of online classes where monitoring can be challenging. Traditional methods of attendance tracking, such as calling out names, are impractical and susceptible to manipulation in the virtual environment. Students might appear 'online' without actively participating, and the absence of video feeds makes it difficult for teachers to verify attendance and attention. In order to realize a highly efficient and robust attendance management and engagement level prediction system for online learning, In the proposed System, the learner’s face is monitored by a video camera while attending a video lecture. Facial features were analyzed to predict reaction time (RT) to a task-irrelevant stimulus, which was assumed to be an index of the level of attention. Then apply a machine learning method, light Gradient Boosting Machine (LightGBM), to estimate RTs from facial features extracted as action units (AUs) corresponding to facial muscle movements by an open-source software (OpenFace). This project is to develops a user-friendly system integrated with private online learning and attendance recording system for teachers that can automatically record students ‘engagement state and attendance then generate attendance reports for online classrooms. It encompasses a novel design using the AI based FFCNN (Face Fiducial Convolution Neural Network) model to capture face biometric randomly from students’ video stream and record their attendance automatically. This integrated solution not only streamlines attendance management but also provides valuable insights into students' engagement levels through facial feature analysis.

Effective Payroll Procedures Enhanced by Electronic Attendance Recording in Indonesia (Prosedur Penggajian yang Efektif Ditingkatkan dengan Pencatatan Kehadiran Elektronik di Indonesia)

This research investigates the effectiveness of accounting information systems in the payroll cycle of a company. Utilizing purposive sampling for interviews, the study evaluates the organizational structure's separation of responsibilities and payroll procedures, including staffing, attendance recording, payroll creation, and financial functions. Findings reveal that these practices are effectively implemented, aligning with theoretical expectations. However, an evaluation suggests that incorporating electronic attendance recording, such as fingerprint systems, could further enhance accuracy and reduce errors in attendance and overtime tracking.

Face Recognition Attendance Monitoring System

The Face Recognition Attendance Management System is a cutting-edge technology solution designed to streamline and enhance the attendance tracking process in various institutions and organizations. This project report provides a concise overview of the system's key features, development process, and its potential impact on attendance management. In a rapidly evolving technological landscape, traditional attendance systems are often inefficient and prone to errors. The Face Recognition Attendance Management System addresses these issues by leveraging state-of-the-art facial recognition technology. This system automates attendance tracking, ensuring accuracy and efficiency while reducing the administrative burden on staff. Key features of the system include facial data capture and storage, real-time face recognition, attendance record generation, and user-friendly interfaces for both administrators and end-users. The project also encompasses the development of a mobile application, enabling users to access their attendance records conveniently. The development process involved the integration of facial recognition algorithms, database management, and user interface design. Additionally, privacy and security considerations were a top priority, with safeguards in place to protect the stored facial data. This report outlines the benefits of the Face Recognition Attendance Management System, such as reduced administrative workload, improved accuracy, and real-time monitoring of attendance. It also discusses potential challenges, including hardware and software requirements, scalability, and user acceptance. In conclusion, the Face Recognition Attendance Management System is a powerful tool for institutions and organizations seeking to modernize their attendance tracking processes. It represents a step forward in leveraging cutting-edge technology to enhance efficiency and accuracy in attendance management