Jefta Supraja, . (2025) RANCANG BANGUN PROTOTIPE SISTEM PRESENSI BERBASIS WEB SERVICE DENGAN PENGENALAN WAJAH DAN GEOLOKASI REAL-TIME. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
![[img]](http://repository.upnvj.ac.id/style/images/fileicons/text.png) |
Text
ABSTRAK.pdf Download (235kB) |
|
Text
AWAL.pdf Download (883kB) |
|
Text
BAB 1.pdf Restricted to Repository UPNVJ Only Download (304kB) |
|
Text
BAB 2.pdf Restricted to Repository UPNVJ Only Download (317kB) |
|
Text
BAB 3.pdf Restricted to Repository UPNVJ Only Download (893kB) |
|
Text
BAB 4.pdf Restricted to Repository UPNVJ Only Download (6MB) |
|
Text
BAB 5.pdf Download (366kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (247kB) |
|
Text
RIWAYAT HIDUP.pdf Restricted to Repository UPNVJ Only Download (167kB) |
|
Text
LAMPIRAN.pdf Restricted to Repository UPNVJ Only Download (5MB) |
|
Text
HASIL PLAGIARISME.pdf Restricted to Repository staff only Download (22MB) |
|
Text
ARTIKEL KI.pdf Restricted to Repository staff only Download (353kB) |
Abstract
Manual attendance in higher education often disrupts the flow of lectures due to its time-consuming nature and susceptibility to errors. To address this issue, this study developed a web-based attendance system utilizing facial recognition and real-time geolocation technology. The system was built using Next.js for the frontend and Flask for the backend, and includes an additional verification feature in the form of classroom photo capture to prevent potential fraud. Testing results indicate that the system significantly improves attendance efficiency, with an average time reduction of 52%, decreasing from 12.5 minutes to 6 minutes per session. Moreover, the system achieved 100% accuracy, precision, recall, and F1-score in facial recognition performance, with no misclassifications. These results demonstrate that the proposed system is effective, accurate, and reliable, offering a faster and more secure alternative to traditional manual attendance methods.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil : 2110511131] [Pembimbing 1: Didit Widiyanto] [Pembimbing 2: I Wayan Rangga Pinastawa] [Penguji 1: Widya Cholil] [Penguji 2: Novi Trisman Hadi] |
| Uncontrolled Keywords: | Attendance, Facial Recognition, Real-Time Geolocation, Web-Based Attendance System, Next.js, Flask, Time Efficiency, Accuracy |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | JEFTA SUPRAJA |
| Date Deposited: | 05 Aug 2025 07:19 |
| Last Modified: | 05 Aug 2025 07:19 |
| URI: | http://repository.upnvj.ac.id/id/eprint/37436 |
Actions (login required)
 |
View Item |