Article Per Year (5 Year)
p-Index From 2021 - 2026
1.376
P-Index
This Author published in this journals
All Journal Sainteks Liquidity: Jurnal Riset Akuntansi dan Manajemen Justek : Jurnal Sains Dan Teknologi Muhammadiyah International Journal of Economics and Business JOURNAL OF SCIENCE AND SOCIAL RESEARCH PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Ekonomi Jutech: Jurnal Teknologi Informasi Jurnal Pengabdian Masyarakat dan Riset Pendidikan
Elliya Sestri
Institut Teknologi Dan Bisnis Ahmad Dahlan, Jakarta
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 12 Documents
Search

 1   2 
Implementasi Front-End Aplikasi Absensi Teknoid Menggunakan Tailwind CSS Studi Kasus ITB Ahmad Dahlan Muhammad Hendrik Tarigan; Elliya Sestri
Jurnal Teknologi Informasi (JUTECH) Vol. 7 No. 1 (2026): JUTECH: Jurnal Teknologi Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jutech.v7i1.3206

Abstract

The digital transformation in higher education institutions demands more efficient administrative systems, including staff attendance systems. ITB Ahmad Dahlan still faces challenges with its current attendance system, such as manual recapitulation, undeleted inactive employee data, and limited automation features. This study aims to implement the front-end interface of a web-based attendance system using Tailwind CSS with an Agile approach. The system is designed to be responsive, modular, and integrated with features such as attendance validation, employee account management, and automated recapitulation. The development process includes requirement analysis, interface design, implementation with an organized folder structure, and functionality testing through Black Box and System Usability Scale (SUS) methods. The test results indicate that the system is accessible across various devices, performs well, and receives positive feedback from users. This front-end implementation is expected to support administrative efficiency and serve as a foundation for future integration with RFID- and IoT-based attendance systems.
Penerapan YOLO dan OpenCV dalam Klasifikasi Kendaraan pada Lalu Lintas Kota Depok Aldo Pamungkas; Shevti Arbekti Arman; Elliya Sestri
Jurnal Teknologi Informasi (JUTECH) Vol. 6 No. 2 (2025): JUTECH: Jurnal Teknologi Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jutech.v6i2.3207

Abstract

The growth in the number of vehicles in Depok City has driven the need for an accurate and efficient traffic monitoring system. This study implements the You Only Look Once (YOLO) version 8 algorithm to automatically detect and classify vehicles based on Python and OpenCV. The focus of the study is on four types of vehicles, namely motorcycles, private cars, buses, and trucks. The dataset was obtained from CCTV recordings and field documentation, then annotated using LabelImg and processed into YOLO format. The training process was carried out using the pretrained YOLOv8 model, while the system testing was conducted on videos of Depok City roads. Model performance was evaluated using the metrics of mAP@0.5 and mAP@0.5:mAP95, precision, recall, and F1 score. The evaluation results show that the model achieved a mAP@0.5 of 91% and a mAP@0.5:mAP95 of 75.1%, precision of 88.5%, recall of 85.2%, and an F1-score of 86.8%. With these results, the model is capable of detecting and classifying vehicles in real time with high accuracy under various lighting conditions and camera angles. Additionally, this system is integrated with a web interface using Flask for direct visualization of detection results. This research contributes to supporting smart transportation systems in urban environments and provides a potential solution for data-based traffic management.
Co-Authors Adhitya Erlangga Ramadhan Aldo Pamungkas Athif Basyar Mussafa Bambang Surahman Bayangkari Karno, Adhitio Satyo Cakranegara, Pandu Adi Chalia Keviana Agatha Diana Yusuf Dodi Arif Ervin Ervin Eva Karla, Eva H Husnayetti Husnayetti Husnayetti Husnayetti, H Isnan Hari Mardika Kukuh Daruningsih Kurniawansyah Kurniawansyah M Koesmawan Muhammad Al Rafli Muhammad Hendrik Tarigan Muhammad Mujtaba Mitra Zuana Nada Kamilia Novida, Irma Nurul Amanah Puji Utami Rabiyatul Adawiyah Rian Ananda Putra Shevti Arbekti Arman Stevianus Stevianus Vany Terisia Widi Hastomo