Analysis of Geographical Characteristics and Risk Factors for Non-Communicable Diseases: Diabetes in Central Java Using Random Forest and SHAP
Diabetes mellitus is a growing health issue in Indonesia, particularly in Central Java Province.In 2023, it contributed significantly to public health concerns due to its increasing prevalence.This study utilizes the Random Forest algorithm to identify dominant diabetes risk factors and map their geographic distribution across the region.The analysis incorporates community lifestyle indicators such as the number of sweet drink stores, gyms, sports halls, transportation availability, karaoke venues, tourist attractions, fast food outlets, and alcohol stores in each regency/city.Results indicate that the number of tourist attractions (feature importance: 0.2817) and sweet drink stores (feature importance: 0.1502) are the primary global risk factors.Locally, tourism dominates as the key risk factor in 18 regencies/cities (51.4% of the region).The model employs optimal hyperparameter tuning to improve accuracy and utilizes SHAP techniques to evaluate the importance of local features.This study aims to enhance understanding of the key risk factors contributing to diabetes cases and their distribution in Central Java Province.
Authors
- Andi Prademon Yunus (ORCID: https://orcid.org/0000-0002-1185-5763)
- Ambar Arum Prameswari
Institutions
- Telkom University (ID)
Publication Details
- Journal
- Proceedings of International Conference on Artificial Life and Robotics
- Published
- 2025-02-13
- DOI
- https://doi.org/10.5954/icarob.2025.os26-6
- Primary Topic
- Data Mining and Machine Learning Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universitas Telkom