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All Journal CESS (Journal of Computer Engineering, System and Science) Prosiding National Conference for Community Service Project
Lius, Kevin
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education

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Perancangan dan Implementasi Back end Website Profile & Crud Product Knowledge di PT. Panca Utama Lius, Kevin; Sama, Hendi; Yulianto, Andik
National Conference for Community Service Project (NaCosPro) Vol. 7 No. 01 (2025): The 7th National Conference for Community Service Project 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/nacospro.v7i01.10797

Abstract

This community service activity aims to design and implement a backend system for a corporate profile website and product knowledge CRUD features for PT. Panca Utama. The company, which supplies equipment to the hospitality industry, previously lacked a digital platform to support its online presence and customer engagement. The development process followed the Scrum framework, consisting of sprint planning, collaborative development, iterative evaluation, and implementation phases. Django, a Python-based backend framework, was employed to build a secure, structured, and efficient system. The final website successfully fulfilled the partner's needs in terms of functionality, accessibility, and ease of content management. The implementation contributed to improving the company’s digital visibility and enhancing customer service quality. Beyond the direct benefits to the partner, this program also provided students with practical experience in applying technical skills in a real-world industrial context.
The Effectiveness of Smart Traffic Management system in Indonesia: Systematic Literature Review Sama, Hendi; Yulianto, Andik; Lius, Kevin
CESS (Journal of Computer Engineering, System and Science) Vol. 11 No. 1 (2026): Januari 2026
Publisher : Universitas Negeri Medan

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Abstract

Traffic congestion in Indonesia causes significant economic losses and impacts the quality of life of the community. The Smart Traffic Management System (STMS) emerges as a technology-based solution that integrates the Internet of Things (IoT), Artificial Intelligence (AI), and big data to manage vehicle flow adaptively. This research employs the Systematic Literature Review (SLR) method with the PRISMA approach to analyze the effectiveness of STMS in reducing congestion and carbon emissions, both in Indonesia and in other countries. The reviewed articles indicate that STMS can reduce vehicle travel time by 8-15%, improve traffic flow smoothness by up to 50%, and decrease carbon emissions by 30-40% per year. Trials in Jakarta demonstrate a 15% increase in traffic smoothness and a reduction in travel time during peak hours. These findings confirm that the implementation of STMS has tremendous potential to realize a more efficient, safe, environmentally friendly, and sustainable urban transportation system.
Co-Authors Andik Yulianto Sama, Hendi