Journal of Deep Learning, Computer Vision and Digital Image Processing
Volume 4 Issue 2 June 2026

Web-Based Regional Map Repository System for Administrative Boundaries Survey Management

Muhammad Ramdani (Nusa Putra University)
Arny Lattu (Nusa Putra University)
Carti Irawan (Nusa Putra University)



Article Info

Publish Date
08 Jul 2026

Abstract

Purpose – This study aims to design and implement a web-based regional map repository system to improve the management of administrative boundary survey archives at the Central Statistics Agency (BPS) of Bogor City. The study addresses the limitations of conventional physical archiving, including poor document traceability, potential data loss, damaged map records, and inefficient monitoring of map borrowing activities.Methods – The system was developed using the Rapid Application Development (RAD) method through requirements planning, user design, construction, and cutover stages. Data were collected through semi-structured interviews, direct observation, and literature review. The system was built using Laravel 12, PHP, MySQL, and deployed through a local server environment. System design was modeled using UML, while evaluation was conducted using black-box testing and the System Usability Scale (SUS) involving 10 respondents.Findings – The system integrates WA and WS map repositories, document borrowing history, role-based access, regional data management, and SLS merging and splitting features. Black-box testing showed a 100% success rate across all tested functional scenarios. The SUS evaluation produced an average score of 79 out of 100, categorized as “Good” and “Acceptable.”Research implications – The findings are limited to one local BPS institution and a small usability sample. Further testing, including load and stress testing, is required to assess scalability and resilience.Originality – This study offers an integrated repository model combining map archiving, administrative boundary management, and transaction-based tracking for local e-government archive transformation.

Copyrights © 2026






Journal Info

Abbrev

DECODING

Publisher

Subject

Computer Science & IT

Description

The Journal of Deep Learning, Computer Vision and Digital Image Processing (DECODING), covers all topics of artificial intelligence and soft computing and their applications, including but not limited to: • Neural networks • Reasoning and evolution • Intelligent search • Intelligent planning ...