Clustering models for hospitals in Jakarta using fuzzy c-means and k-means

After facing the COVID-19 pandemic, national and local governments in Indonesia realized a gap in the distribution of health care and human health practitioners. This research proposes two unsupervised learning methods, K-Means and Fuzzy C-Means (FCM), for clustering a list of hospital data in Jakar...

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Detalles Bibliográficos
Autores principales: Setiawan, Karli Eka, Kurniawan, Afdhal, Chowanda, Andry, Suhartono, Derwin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829428/
https://www.ncbi.nlm.nih.gov/pubmed/36643178
http://dx.doi.org/10.1016/j.procs.2022.12.146

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829428/
https://www.ncbi.nlm.nih.gov/pubmed/36643178
http://dx.doi.org/10.1016/j.procs.2022.12.146

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