Klasterisasi Data Penanganan dan Pelayanan Kesehatan Masyarakat dengan Algoritma K-Means - Yohanni Syahra; Dedi Rahman Habibie; Mardiah Nasution; Hanifah Nur Nasution; Asyahri Hadi Nasyuha (STMIK Budi Darma, 2022)
Quality public health services are one of the characteristics of the country's successful development in the health sector. The Health Office has formulated a number of methods to determine the level of progress of health development at the center to the sub-districts. Every year the Lubuk Pakam Health Office collects public health data for processing so that it produces a ranking of regions with the predicate of healthy districts/cities. Data mining is a process used to extract and identify useful information and obtain some important information from data in analyzing public health data. Furthermore, the algorithm that will be used for data mining management in the case of analyzing public health data and used for cluster formation is the K-Means algorithm. The results obtained in the data grouping there are categories of patient assessment levels Very Satisfied, Satisfied, and Dissatisfied. From the results of the K-Means method, it can be concluded to improve services and health care as for the results of grouping the level of satisfaction