Klasterisasi Pasien Rawat Jalan di Puskesmas dengan Menggunakan Metode Algoritma Clustering K-Means - Azkar, Azkar; Kusrini, Kusrini (STMIK Budi Darma, 2024)
The Aikmel Utara Public Health Center in Lombok Timur Regency began operating in mid-2019, but has never utilized patient data to obtain information as a basis for decision-making efforts to improve quality of health services and consequently enhance patient satisfaction. The target respondents patient satisfaction survey at the Public Health Center are visitors, the majority of whom are outpatient visitors. The purpose of this research is to group outpatient patients based on variables such as gender, age, participation status in the BPJS health insurance program and patient address, as well as diagnosis of the patient's disease using the k-means clustering algorithm method with the assistance of the RapidMiner application. Patient data totaling 1889 were grouped into 2 clusters, 3 clusters, 4 clusters, and 5 clusters, and evaluated using the Davies-Bouldin Index (DBI). The research results show that the number of clusters formed is 2, with cluster 1 consisting of 1570 data and cluster 2 consisting of 319 data. Cluster 1 is dominated by female patients (1074 or 68.4%), BPJS participants (819 or 52.2%), with the most common age group being adults (883 or 56.2%), and most of them are from Toya village (488 or 31.1%), with the most common diagnosis being acute respiratory infections (J06) (223 or 14.2%). Meanwhile, cluster 2 is dominated by female patients (205 or 64.3%), BPJS participants (202 or 63.3%), with the most common age group being adults (191 or 59.9%), and most of them are from Toya village (108 or 33.9%), with the most common diagnosis being pregnancy examinations (Z34) (29 or 9.1%). From these cluster results, it is obtained that the majority of outpatient visitors at the Aikmel Utara Public Health Center are from Toya village and are dominated by the adult age group and BPJS health insurance participants, with the most common disease being acute respiratory infections. It is hoped that this information can assist the Public Health Center in making decisions or policies related to health programs in its working area