Klasterisasi Pasien Rawat Inap Peserta BPJS Berdasarkan Jenis Penyakit Menggunakan Algoritma K-Means
DOI:
https://doi.org/10.37034/jsisfotek.v5i2.162Keywords:
Medical Record, BPJS, Data Mining, K-Means, ClusterAbstract
Medical records of patients from the Health Insurance Administering Body (BPJS) consist of complete patient data along with a complex history of patient services stored in every health facility. Inpatient medical record data contains important data as well as contains useful information as new knowledge using data mining techniques. This study aims to assist and provide new information related to the clustering of BPJS inpatients at the Arifin Achmad Hospital, Riau Province, so as to obtain information related to the spread of the patient's disease. The data used are medical records of inpatients in 2021. The data obtained are then processed using the K-Means clustering algorithm with a total of 3 clusters. The study resulted in cluster K1 dominated by Malignant neoplasm, breast, unspecified (C50.9) and Non-Hodgkin's lymphoma, unspecified type (C85.9) disease. Cluster K2 is dominated by fracture of neck of femur, closed (S71.00) and Dengue haemorrhagic fever (A91).
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