Analysis and Comparison of the Performance of K-Means Algorithm and X-Means Algorithm in Disease Type Clustering in Mitra Medika Hospital - Herdawani Afdilla; Hasibuan, Wilda Rina (Yayasan Kita Menulis, 2024)
The system used by the hospital is currently still manual in managing patient data and information. What happened at Mitra Medika Hospital is that it is difficult to provide medical needs related to the patient's illness, considering the many types of illnesses that provide many medical needs. Several inpatients have used BPJS facilities with various illnesses suffered by patients to undergo further examinations in order to recover from the illness they are suffering from. Mitra Medika Hospital only sees medical needs based on the illness suffered by the patient, but seeing the large amount of patient history data makes it very difficult for Mitra Medika Hospital to find out the group of illnesses that patients often experience. This study uses a quantitative approach which starts from a theoretical framework, expert ideas, or researchers' understanding based on their experience, then developed into problems and their solutions that are submitted to obtain justification (verification) or assessment in the form of empirical data support in the field. Here, a data mining pattern is applied where this data mining is a very large data mining (big data). Cluster 0: From 245 Men (Suffering Between Diseases 1-5) Cluster 1: From 255 Women (Suffering Between Diseases 6-10) By using the K-Means Algorithm and the X-Means Algorithm, clustering can be produced. By using the Disease History data, the K-Means Algorithm and the X-Means Algorithm methods can be applied to determine clusters. By using web programming, it can produce an Analysis and Comparison of the Performance of the K-Means Algorithm and the X-Means Algorithm in Clustering Types of Diseases at Mitra Medika Hospital.