PENERAPAN DATA MINING UNTUK PENGELOMPOKKAN HASIL DIAGNOSA PENYAKIT PESERTA JKN-KIS BPJS KESEHATAN KANTOR CABANG PRABUMULIH
Keywords:
Diagnosis, K-Means Clustering, Data Mining
Abstract
BPJS Kesehatan has collaborated with several health facilities in Indonesia to provide health services. So far, the use of grouping the results of disease diagnosis of JKN-KIS participants used by BPJS Health Partners and also the Health Office only uses a general description of the patient data. Optimal utilization of disease diagnosis data from JKN-KIS patients has not been done. Therefore, Clustering is also a method of grouping several data objects into a certain group of information with a high degree of similarity. Testing the best value with the Elbow method produces a K value that is close to The Shape of a 90 degree angle that is in the 4th cluster. So therefore, the medical record data grouping system produces the best cluster by using 8 clusters.
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Jurnall Time, II(1), 1–5. https://doi.org/10.1007/s13398-014-0173-7.2
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Jurnall Sistem Daln Informaltikal, 3(Februalri), 47–60.
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Published
2023-01-31
How to Cite
Aulia, A. (2023). PENERAPAN DATA MINING UNTUK PENGELOMPOKKAN HASIL DIAGNOSA PENYAKIT PESERTA JKN-KIS BPJS KESEHATAN KANTOR CABANG PRABUMULIH. Jurnal Saintifik (Multi Science Journal), 21(1), 25-36. https://doi.org/10.58222/js.v21i1.123
Section
Articles
