Resumen
The study sought to improve attendance control in an educational institution through a web application based on neural networks. Under an applied research approach with a pure experimental design, direct observation was used to evaluate indicators related to the registration and generation of attendance reports, considering 30 records selected through simple random probabilistic sampling. The XP methodology was implemented, which includes the planning, design, development and testing phases. The experimental group showed notable advances compared to the control group: the average attendance registration time decreased by 53.33%, 60% in the generation of reports, and 80% exceeded the average precision of the information. Additionally, 96.67% exceeded the accuracy of the control group. It follows that the digital tool, backed by neural networks, has been essential to enhance the control of attendance in the institution. It was concluded that for the development of the results the Mann-Whitney U and Student’s T statistical tests were used according to the corresponding indicator.
Título traducido de la contribución | Web Application Based on Neural Networks for Attendance Control with Facial Recognition: A Case Study in an Educational Institution in La Esperanza, Trujillo-Peru |
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Idioma original | Español |
Páginas (desde-hasta) | 17-30 |
Número de páginas | 14 |
Publicación | RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao |
Volumen | 2024 |
N.º | 1 E65 |
Estado | Publicada - 2024 |
Palabras clave
- Artificial Intelligence
- Attendance Monitoring
- Extreme Programming
- Face Detection
- Online Platform