Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA)
Jeremy Nugrahanto Kotten
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Design and Development of a Client-Server Architecture Database Information System for Inventory Management and Transaction Efficiency Afifah Trista Ayunda; Master Edison Siregar; Ephraim Eleazer Reva Manopo; Rizky Anggara Wicaksono; Jeremy Nugrahanto Kotten
Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA) Vol. 2 No. 2 (2025): Journal of Information Technology, Computer Engineering and Artificial Intellig
Publisher : Redtech Putra Benua

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Transaction management and inventory control in automotive Micro, Small, and Medium Enterprises (MSMEs) often rely on manual record-keeping systems, leading to stock data discrepancies, accounting vulnerabilities, and operational inefficiencies. This study aims to design and implement a Client-Server database information system named Bengkelqu-AI (Accounting & Inventory) at Bengkel Zulva Motor. Data collection was conducted through structured interviews with the business owner to identify business entity requirements and daily transaction workflows. The system was developed using the PHP programming language, MySQL DBMS, Apache web server via the XAMPP package, and Visual Studio Code. The relational database design for dbpenjualan yielded five integrated tables (tvendor, tcustomer, tbarang, tpembelian, and tbpenjualan). The implementation results demonstrate that the system successfully facilitates data processing through Create, Read, Update, and Delete (CRUD) operations, automated report generation, and database backup features in .sql format. The deployment of the Bengkelqu-AI system is proven to enhance transaction recording accuracy, minimize potential losses due to human error, and simplify real-time inventory monitoring.
Co-Authors Afifah Trista Ayunda Ephraim Eleazer Reva Manopo Master Edison Siregar Rizky Anggara Wicaksono