Development of location suitability prediction for health facilities using random forest machine learning in 2030 integrating remote sensing and GIS in West Java, Indonesia

Development of location suitability prediction for health facilities using random forest machine learning in 2030 integrating remote sensing and GIS in West Java, Indonesia

Access to healthcare facilities is crucial in the present day. Healthcare facilities must be proportional to the population in a given area. Therefore, it is important to increase the number of healthcare facilities in regions where there is an imbalance. Proper planning and a sustainability review...

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Bibliographic Details
Main Authors: Riantini Virtriana, Kalingga Titon Nur Ihsan, Tania Septi Anggraini, Albertus Deliar, Agung Budi Harto, Akhmad Riqqi, Anjar Dimara Sakti
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Environmental Advances
Subjects:
Health Facility
GIS
Remote Sensing
Machine Learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2666765724001224
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