Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Jurnal Computer Science and Information Technology (CoSciTech) Bulletin of Information Technology (BIT)
Syawali, Yusfi
Unknown Affiliation
Computer Science & IT

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

Found 2 Documents
Search

 1 
SISTEM PENDUKUNG KEPUTUSAN UNTUK OPTIMALISASI PEMILIHAN BIBIT PADI TERBAIK MENGGUNAKAN METODE MOORA Syawali, Yusfi; Niska, Debi Yandra; Rangkuti, Muhammad Haikal Hafiz; Mayadi, Kaka Aprianda
Computer Science and Information Technology Vol 6 No 1 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i1.9104

Abstract

This study aims to develop a Decision Support System (DSS) based on the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to assist farmers in selecting the best rice seeds in a systematic, objective, and data-driven manner. The case study was conducted in Cengkeh Turi Subdistrict, Binjai City, considering ten key criteria such as productivity, pest resistance, grain quality, and seed availability in the market. A quantitative-descriptive approach was used, with data obtained from field observations, interviews, documentation, and relevant literature. The system was built using Python and the Streamlit framework to create an interactive web-based application. The MOORA calculation results showed that the Sidenok (Rambutan) rice variety achieved the highest optimization score (Yi) of 0.2127. The system not only provides accurate technical recommendations but also helps farmers understand the selection process through a user-friendly interface and clear visualizations. System validation showed consistency between manual and system-generated calculations, and local farmers provided positive feedback on usability and result reliability. These findings demonstrate the effectiveness of the MOORA method in local agricultural decision-making and highlight its potential for further development through the integration of climate-based predictive features. The system is expected to contribute to precision agriculture innovation and support sustainable national food security efforts.
Face Recognition Motorcycle Rider Registration System for Rider Data Management Saputra S, Kana; Taufik, Insan; Ramadhani, Irham; Sasalia S, Putri; Syawali, Yusfi; Yusuf, Dede; Nadilla Putri, Rezkya; Latifah Hasibuan, Najwa; Hafiz Harahap, Fauzan
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2157

Abstract

This research aims to develop a motorcycle rider registration system using facial recognition technology that can improve the efficiency of rider data management. This system is designed to identify and authenticate riders with high accuracy, thereby simplifying the registration and monitoring process. The methods used in this research include collecting rider facial data through cameras, image processing for feature extraction, and implementing a facial recognition algorithm. Testing was conducted in several locations with varying lighting conditions and viewing angles to ensure the system's robustness. The results show that the developed system is capable of achieving facial recognition accuracy of up to 95%. In addition, this system provides an intuitive user interface to facilitate the registration and data management process. With the implementation of this system, it is expected to reduce the time and costs required in managing motorcycle rider data, as well as improve safety and comfort while riding.
Co-Authors Fachry Abda El Rahman Hafiz Harahap, Fauzan Insan Taufik Irham Ramadhani Kana Saputra S Latifah Hasibuan, Najwa Mayadi, Kaka Aprianda Nadilla Putri, Rezkya Niska, Debi Yandra Rangkuti, Muhammad Haikal Hafiz Sasalia S, Putri