Vol. 3 No. 3 (2025): September - December 2025

Dear Readers,

Welcome to Volume 3, Number 3 of the International Journal of Information Technology and Computer Science Applications (IJITCSA). This issue brings together a diverse and high-quality collection of research articles that reflect the interdisciplinary and international scope of contemporary advances in information technology and computer science applications.

This issue features five original research contributions from scholars affiliated with institutions across Indonesia, Malaysia, the Philippines, Iraq, and Pakistan, representing a broad geography of research activity and collaboration:

Comparative Analysis of K-Means and Hierarchical Clustering for Regional Welfare Disparity Identification in West Java Province – A rigorous study on clustering techniques for socio-economic data analysis from Indonesia, offering insights into welfare disparity patterns and methodological comparisons.

The Adoption of Analytics in Handling Netflix’s Business Challenges – Research from Malaysia that investigates text and web analytics techniques for business intelligence, highlighting applications in customer behavior analysis and strategic decision support within digital media platforms.

An Overview of Business Intelligence Framework for Sentiment Analysis of United Airlines Using Data from Social Media – A comprehensive framework for sentiment analytics applied to airline service evaluation, authored from the University of Santo Tomas in the Philippines.

Integrating Structured and Unstructured Data for Enhanced Marketing Intelligence through Text Mining and Business Analytics – A contribution from the American University of Iraq that explores integration strategies for heterogeneous data sources to support advanced marketing analytics.

Complications in Healthcare Integration Models and Correlated Data Infrastructure Proposition – A cross-disciplinary investigation by researchers in Pakistan into data integration architectures for healthcare systems, with emphasis on data warehouse solutions to improve interoperability and efficiency.

Collectively, these articles illustrate the breadth of current research — from machine learning applications and clustering methods, through analytics and business intelligence frameworks, to data integration challenges in healthcare systems. Each contribution not only advances theoretical perspectives but also addresses practical challenges in real-world problem domains.

It is our hope that this issue will inspire further research, stimulate interdisciplinary dialogue, and encourage the application of innovative computational methods to complex societal and business problems worldwide.

We extend sincere appreciation to all authors, peer reviewers, and readers for contributing to the ongoing success and scholarly impact of IJITCSA.