Development of Machine Learning Models to Predict Health Insurance Claim Costs Among Older Indonesians: A Retrospective Predictive Modeling Study
XGBoost provides reliable predictions of claim costs among older adults, capturing clinical, utilization, and structural drivers. These findings can inform targeted interventions, improve chronic disease management, optimize the referral system, and support integration of predictive tools into JKN to enhance responsiveness and promote sustainable, equitable financing.
Authors
- Syarif Rahman Hasibuan (ORCID: https://orcid.org/0009-0007-1354-2748)
- Yeni Mahwati (ORCID: https://orcid.org/0000-0002-6567-9486)
- Yeni Indriyani (ORCID: https://orcid.org/0000-0001-7551-264X)
- Andi Afdal Abdullah
- Halik Malik
- Bhirau Wilaksono
- Andi Alfian Zainuddin
- Dhihram Tenrisau
Institutions
- Yogyakarta State University (ID)
- Social Insurance Institute (GR)
- University of Indonesia (ID)
- Muhammadiyah University of Surakarta (ID)
- State University of Makassar (ID)
- Hasanuddin University (ID)
Publication Details
- Journal
- Journal of Preventive Medicine and Public Health
- Published
- 2026-01-06
- DOI
- https://doi.org/10.3961/jpmph.25.350
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00