Dika, Andhika Dwiky Pratama (2020) IMPLEMENTASI FACE RECOGNITION PADA SISTEM KEHADIRAN RAPAT HIMPUNAN MAHASISWA MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN). S1 thesis, Universitas PGRI Madiun.
Text
Halaman Depan.pdf Download (4MB) |
|
Text
Abstrak & Abstract.pdf Download (515kB) |
|
Text
Bab I.pdf Download (530kB) |
|
Text
Bab II.pdf Download (876kB) |
|
Text
Bab III.pdf Restricted to Repository staff only Download (614kB) |
|
Text
Bab IV.pdf Restricted to Repository staff only Download (1MB) |
|
Text
Bab V.pdf Download (513kB) |
|
Text
Daftar Pustaka.pdf Download (431kB) |
|
Text
Lampiran.pdf Download (4MB) |
Abstract
This research focuses on developing an attendance system for the meetings of the Informatics Engineering Student Association at Universitas PGRI Madiun. The attendance system is a website built using VueJs for the front-end, FastAPI for the backend, and SQLite for the database. The utilization of Machine Learning in the development of this system has resulted in a facial recognition model that can accurately detect the faces of registered members, as evidenced by the model's 100% accuracy. The use of CNN architecture was an excellent choice for designing an accurate facial recognition model. The system was developed using the Rapid Application Development (RAD) methodology, which allows for quick development with minimal bugs. The research results show that the system can be used effectively. The development of this system is a proper step in addressing the shortcomings of the current attendance process, which still relies on conventional paper-based methods. Implementing this system is also a suitable measure to prevent fraud in the attendance process.
Item Type: | Thesis/Skripsi/Tugas Akhir (S1) |
---|---|
Kata Kunci: | Face recognition; Machine learning; Python; JavaScript; SQLite |
Subjects: | T Technology > T Technology (General) |
Divisions: | Fakultas Teknik > Teknik Informatika |
Depositing User: | PRATAMA DWIKY ANDHIKA |
Date Deposited: | 22 Aug 2024 05:54 |
Last Modified: | 22 Aug 2024 05:54 |
URI: | http://eprint.unipma.ac.id/id/eprint/1773 |
Actions (login required)
View Item |