Development of mobile and desktop applications for a fingerprint-based attendance management system

Akinola, Olubunmi Adewale; Olopade, Sikiru Olatunde; Afolabi, Akindele Segun

doi:10.11591/ijeecs.v24.i1.pp570-580

Cited by 4 publications

(7 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…To enable access to the MySQL database where the symptoms and the damage list are maintained. In hypertext preprocessor (PHP) code, structured query language (SQL) queries are written in the form of strings that are processed by the MySQL database server [30], [31]. Figure 4 presented the graphical user interface of the mobile expert system.…”

Section: Resultsmentioning

confidence: 99%

Development of a mobile expert system for the diagnosis on motorcycle damage using forward chaining algorithm

Naryanto

Delimayanti

Kriswanto

et al. 2022

IJEECS

View full text Add to dashboard Cite

Indonesia is an <span>ASEAN country with the most motorcycle users, where one-third of its population own motorcycles. The automatic motorcycle is the most widely used type due to its agility and fuel-efficient abilities. Sudden motorcycle damage could hamper the users' activities. However, most of these users do not know the reason for the damage. This paper presents the development of expert system for diagnosing the damage of motorcycle using forward chaining method. This system was implemented in mobile application. Through a mobile application, a solution for these users can be obtained. This application immediately discovers the damaged location and repair process. Furthermore, it acts as the first solution before motorcycle repair is carried out in a shop. In this study, the forward chaining method was implemented. It is based on a pattern-matching algorithm whose primary objective is to match facts (input data) with appropriate rules from the rule base. Various test results showed that the diagnostic application used for automatic motorcycle damages 100% worked.</span>

show abstract

Section: Resultsmentioning

confidence: 99%

Development of a mobile expert system for the diagnosis on motorcycle damage using forward chaining algorithm

Naryanto

Delimayanti

Kriswanto

et al. 2022

IJEECS

View full text Add to dashboard Cite

show abstract

“…Attendance automation: Similar to other studies [7] [8] [10], the current study aims to automate the attendance registration process in educational institutions. This is achieved through the development of a mobile application that simplifies and expedites the task for teachers, thus enhancing the efficiency of the process.…”

Section: Discussionmentioning

confidence: 99%

“…Use of advanced technology: The current study, similar to some previous studies [7] [8] [10], leverages advanced technologies such as machine learning and cloud computing to improve attendance registration. This reflects a trend towards integrating cutting-edge technology into educational management.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

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

Caytuiro-Silva,

Maraza Quispe,

Castro-Gutierrez

et al. 2024

Int. J. Interact. Mob. Technol.

View full text Add to dashboard Cite

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.

show abstract

“…En el trabajo de Akinola, Olopade y Afolabi [6] se presenta una solución automatizada, en la que se desarrolló un aplicativo móvil basado en JAVA, la cual se conectó de forma inalámbrica a una Base de Datos central que se creó utilizando MySQL, cuya tarea, entre otras, era registrar la información de asistencias. El sistema se implantó en una universidad para registrar los datos de los estudiantes, el tiempo de ausencia, el tiempo de presencia y las asistencias acumuladas por mes, dando como resultado el uso eficaz y eficiente del sistema.…”

Section: Revisión De La Literaturaunclassified

Development of a mobile application for the registration and attendance control of university students based on Machine Learning

Silva¹,

Samayani²,

Alejandro³

et al. 2022

Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development (LEIRD 202

View full text Add to dashboard Cite

This research aims to develop an Android mobile application that allows registration and control of attendance in educational institutions based on Machine Learning and Cloud Computing technology. For this, the project management methodology XP (EXtreme Programming) is used, in whose phases the entire process of implementation of the application and the launch are detailed; likewise, Firebase is used as a service for database management. The application tests were carried out on the students of the seventh semester of the Professional School of Systems Engineering of the University of Peru. The attendance control system was connected to a database that stores student information and attendance records. To implement the QR code attendance record functionality, the Firebase Machine Learning kit was used to Validate the student attendance record. In addition, the user interface displays the attendance records from an attractive, intuitive approach that is easy for teachers and students to manage. The results of the research show that the use of the application by teachers and students reduces and optimize the time invested in the attendance registration process compared to traditional methods, according to the satisfaction and acceptance criteria of the mobile application called "ASYS."

show abstract

Development of mobile and desktop applications for a fingerprint-based attendance management system

Cited by 4 publications

References 17 publications

Development of a mobile expert system for the diagnosis on motorcycle damage using forward chaining algorithm

Development of a mobile expert system for the diagnosis on motorcycle damage using forward chaining algorithm

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

Development of a mobile application for the registration and attendance control of university students based on Machine Learning

Contact Info

Product

Resources

About