Vol. 2 No. 01 (2026): Journal of Data Science Applications.

Welcome to the latest edition of the Journal of Data Science Applications. This issue highlights the versatility of data science, spatial modeling, and machine learning in solving multi-sectoral challenges. Interestingly, three of the four featured studies focus on regional data within East Java, emphasizing the value of localized analytics for decision-making.

Here is a brief overview of the research presented in this edition:

• Spatial Modeling for Family Planning: Using Elastic Net and Geographically Weighted Regression (GWR), this study maps the spatial heterogeneity of active family planning participation in East Java, offering visual insights for targeted resource allocation.

• Clustering Pediatric Respiratory Diseases: By comparing unsupervised learning methods, this research proves that Hierarchical Clustering (Ward linkage) is highly effective in mapping and clustering childhood respiratory cases in Lamongan Regency to prioritize health interventions.

• Optimizing Disaster Relief Logistics: This study introduces a dynamic, Python-based application that utilizes Dijkstra’s Algorithm to calculate the shortest, most efficient routes for distributing humanitarian aid to flood victims in Gresik.

• Predictive Analytics in E-Sports: Analyzing Magic Chess gameplay via Machine Learning, this paper debunks a common gamer myth. It reveals that economic metrics only account for 1.6% of a player's final ranking, proving that other tactical decisions are far more dominant.

These papers reflect a strong methodological exploration—from health and disaster management to digital entertainment. We hope this edition inspires researchers and policymakers to continue leveraging data science for practical solutions.

Happy reading!