Klasterisasi Peserta BPJS Berdasarkan Rekam Medis Menggunakan Algoritma K-Means
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Ana Fitri Khairani
*
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru,
Indonesia
- Alwis Nazir Universitas Islam Negeri Sultan Syarif Kasim, Pekanbaru, Indonesia
- Teddie Darmizal Universitas Islam Negeri Sultan Syarif Kasim, Pekanbaru, Indonesia
- Yelfi Vitriani Universitas Islam Negeri Sultan Syarif Kasim, Pekanbaru, Indonesia
- Yusra Yusra Universitas Islam Negeri Sultan Syarif Kasim, Pekanbaru, Indonesia (*) Corresponding Author
Abstract
The history of the patient's medical examination with the BPJS (Social Security Administration Agency) at the Dumai City Hospital will be stored in the form of a medical record. The medical record is a file that contains patient identification information whether it contains the results of control, treatment and other services. The purpose of this research is to. to assist the Dumai Hospital in grouping BPJS participants based on medical records to find out the disease, gender and BPJS group that is most dominant in Dumai City BPJS participants. The results of grouping the disease will then be processed using data mining techniques. In this study, the focus was on BPJS PBI participants inpatient medical record data from January to December 2022, which were then processed using the K-Means Clustering algorithm with 3 clusters. Cluster 0 is dominated by disease types with code O342 (Maternal care due to uterine scar from previous surgery), female sex and age range 21-40 years. Cluster 1 is dominated by types of disease with code E119 (Diabetes mellitus without complications), female sex and age range 41-60 years and cluster 2 is dominated by disease types with code J180 (Bronchopneumonia, unspecified organism), female sex and age range 41-60 years.
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Copyright (c) 2023 Ana Fitri Khairani, Alwis Nazir, Teddie Darmizal, Yelfi Vitriani, Yusra Yusra
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