Data Clusterization of Patient Medical Records for BPJS Kesehatan Service Users Using the K-Means Method

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Jeri Wandana
Sarjon Defit
Sumijan Sumijan

Abstract

Patient histories who use the services of Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan are stored in medical record data. Each medical record data contains important information that is very valuable and can be processed to explore new knowledge using a data mining approach. This study aims to help Prof. Dr. Tabrani hospital in classifying patient data who use BPJS Kesehatan, so that the pattern of disease spread is known based on class of service. The data used is patient medical record data in 2019 from October to December, the data will be processed using the K-Means Clustering algorithm with a total of 3 clusters. In cluster 0 (H0) there are 3 patients who are dominated by A09.9 disease (Diarrhea / Dysentery) in Class 2 and Class 3, for cluster 1 (H1) there are 5 patients with more diverse types of disease, while for cluster 2 (H2) there are 5 patients who are predominantly K30 disease (Dyspepsia) in Class 1.

Article Details

How to Cite
Wandana, J., Defit, S., & Sumijan, S. (2020). Data Clusterization of Patient Medical Records for BPJS Kesehatan Service Users Using the K-Means Method. Jurnal Informasi Dan Teknologi, 2(4), 119-125. https://doi.org/10.37034/jidt.v2i4.73
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References

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