Analyzing the Distribution of Health Workers in Semarang City Using K-Means Clustering Method - Setiyaji, Akhfan; Purnomo, Hindriyanto Dwi (Universitas Bina Darma, 2024)
This research employed the K-Means Clustering method to examine the distribution of health workers in Semarang City, emphasizing their pivotal role in the public health infrastructure. Leveraging current data encompassing health worker locations and quantities, the clustering analysis discerned areas exhibiting similar distribution characteristics through the application of the K-Means technique. Quantitative analysis revealed distinct clusters, shedding light on the spatial patterns of health workforce dispersion within Semarang City. The study's quantitative findings furnish valuable insights crucial for formulating more efficacious health policies. By delineating the utility of the K-Means Clustering method in public health planning and providing quantitative evidence of health worker distribution, this research substantially augments geographical comprehension in the examined region.