Interactive big data visualization for child mortality risk among children aged 5–14 in Asia

Othman, Nor Arzami and Uyop @ Ayob, Nurul Yusra and Osman, Mohd Nizam and Sedek, Khairul Anwar (2026) Interactive big data visualization for child mortality risk among children aged 5–14 in Asia. Journal of Computing Research and Innovation, 11 (1): 7. pp. 72-83. ISSN 2600-8793

Official URL: https://jcrinn.com/index.php/jcrinn

Identification Number (DOI): 10.24191/jcrinn.v11i1.570

Abstract

This project focuses on visualizing the probability of mortality among children aged 5 to 14, aiming to deliver a comprehensive understanding of geographical death rates and mortality trends from the year 2000 to 2030. Recognizing the critical importance of child survival in global health efforts, the study investigates regional disparities by reviewing existing literature, analysing global statistical data, and applying appropriate analytical methodologies. The core objective is to identify regions across Asia categorized by high, medium, and low mortality risks, thereby highlighting vulnerable populations. A data-driven dashboard was developed as the primary output of this research, enabling users to interactively explore mortality probabilities over time and across different countries. The development process followed the structured Waterfall model, progressing through five phases: preliminary study, planning, design, development, and testing. Each phase achieved specific milestones: defining project goals, designing user-friendly interfaces, integrating data, conducting usability testing, and evaluating user engagement. During the evaluation phase, 41 respondents participated in assessing the dashboard’s effectiveness. Findings revealed that the visualization significantly enhanced users’ understanding of child mortality trends, particularly excelling in the Perceived Usefulness dimension. Through advanced data visualization techniques and robust statistical analysis, the project provides clear and actionable insights for stakeholders. The visualization tool offers valuable support to researchers, policymakers, and healthcare practitioners, empowering them to make informed, evidence-based decisions aimed at improving child health outcomes and reducing mortality risks in the targeted age group.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Othman, Nor Arzami
UNSPECIFIED
Uyop @ Ayob, Nurul Yusra
UNSPECIFIED
Osman, Mohd Nizam
UNSPECIFIED
Sedek, Khairul Anwar
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Computer software > Application program interfaces
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus
Journal or Publication Title: Journal of Computing Research and Innovation
UiTM Journal Collections: UiTM Journals > Journal of Computing Research and Innovation (JCRINN)
ISSN: 2600-8793
Volume: 11
Number: 1
Page Range: pp. 72-83
Keywords: big data, data analysis, dashboard, mortality, visualization, waterfall model
Date: 2026
URI: https://ir.uitm.edu.my/id/eprint/135361
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