Penerapan Data Mining Pengelompokan Hasil Diagnosa Pasien BPJS Berdasarkan Usia Menggunakan Metode Clustering (Studi Kasus: RSU Bidadari Binjai)

  • Leny Widiya Pa Program Studi Sistem Informasi, STMIK KAPUTAMA Binjai
Keywords: Data Mining, k-means algorithm, patient diagnosis result

Abstract

The hospital is a health service institution that provides complete individual health services that provide inpatient services. Because the large number of patient data in the hospital makes it difficult for the administration to process existing data and information, the authors want to group patient data at the hospital to produce information. and can also facilitate the hospital in providing information to patients. Cluster is finding a collection of objects in a group that are the same (or have a relationship) with others and different (or not related) with objects in other groups. The purpose of cluster analysis is to minimize the distance within the cluster and maximize the distance between clusters. And the Centroid on the cluster is the center point. From the tests carried out using the clustering method with the k-means algorithm, it can be seen that cluster 2 of the criteria for disease symptoms, diagnosis results, age, group that has the highest set / value and the most patient diagnosis data, namely in Cluster 1 totaling 825. Patient data with diagnosis results using BPJS on Symptoms of High Fever and the diagnosis is Asthma, then age is> 60 years. and the most intermediate data on patients who experience delinquency, namely in Cluster 1 amounted to 595 patient data with a diagnosis using BPJS on Symptoms of High Fever and the diagnosis is anemia, then the age used is> 60 years.

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Published
2022-03-13