Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Bangkit Indonesia
Jayusman, Yus
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Sistem Presensi menggunakan Deteksi Objek Wajah Mahasiswa Berbasis YOLO-V5 Rahayu, Mina Ismu; Rizaludin, Muhamad; Jayusman, Yus
Jurnal Bangkit Indonesia Vol 13 No 2 (2024): Bulan Oktober 2024
Publisher : LPPM Sekolah Tinggi Teknologi Indonesia Tanjung Pinang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52771/bangkitindonesia.v13i2.310

Abstract

Attendance is a crucial aspect across various sectors, such as corporate, governmental, and educational institutions, for efficient management. The advancement of deep learning technology, particularly in the field of facial recognition, has become a primary focus in enhancing identification accuracy. In this context, visual object detection through computer vision plays a key role, with the You Only Look Once (YOLO) method emerging as a leading choice for real-time object detection across various media, including webcams, due to its speed and efficiency. This research proposes the application of YOLO-V5 in the development of a student attendance system. This approach utilizes deep learning and data augmentation to enhance the accuracy of student identification. YOLO-V5 enables efficient real-time object detection, achieving an accuracy rate of up to 95% on each frame. The implementation of the student attendance system using the YOLO-V5 method successfully detects student attendance in real-time with a high level of accuracy. This demonstrates the potential of this method to improve the efficiency of attendance management and its suitability for integration into student attendance systems. This research represents a significant advancement in the use of deep learning and computer vision to increase the accuracy and efficiency of attendance management
Implementasi Sistem Pendukung Keputusan menggunakan Metode Simple Multi Attribute Rating Technique (SMART) untuk Seleksi Penerimaan Siswa Baru Jayusman, Yus
Jurnal Bangkit Indonesia Vol 14 No 1 (2025): Bulan Maret 2025
Publisher : LPPM Sekolah Tinggi Teknologi Indonesia Tanjung Pinang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52771/bangkitindonesia.v14i1.441

Abstract

The admission of new students is a crucial process for schools to select prospective students who meet predefined criteria. Currently, the selection process at SMA Bina Muda Cicalengka is still conducted manually, which increases the risk of errors and inefficiencies. Therefore, a more modern and structured student admission selection system is required. This study aims to develop a Web-Based Decision Support System for New Student Admission Selection to facilitate the registration process, enhance selection accuracy, and provide more systematic data for in-depth analysis. The system employs the Simple Multi-Attribute Rating Technique (SMART) to evaluate prospective students based on several criteria, such as the average diploma score, academic achievements, and economic background. The development process follows the Extreme Programming (XP) methodology, enabling a more flexible and adaptive approach to user requirements. The research findings indicate that implementing a web-based system at SMA Bina Muda Cicalengka allows for broader accessibility and generates a faster and more optimal selection process. The integration of information technology in the student admission selection process has proven to enhance transparency and fairness, thereby improving the school's decision-making quality and overall service efficiency.
Co-Authors Rahayu, Mina Ismu Rizaludin, Muhamad