Pemanfaatan Algoritma K-Means untuk Pengelompokkan Pasien Penyakit Infeksi Saluran Pernafasan Akut (ISPA)

Authors

  • Friska Selvina Agoestina STIKOM Tunas Bangsa
  • Heru Satria Tambunan STIKOM Tunas Bangsa
  • Rizki Alfadillah Nasution STIKOM Tunas Bangsa

DOI:

https://doi.org/10.54259/satesi.v2i1.804

Keywords:

Data Mining, ARI, Bah Biak, Clustering, Puskesmas

Abstract

This study discusses Acute Respiratory Infections (ARI) at the Bah Biak Health Center. Bah Biak Health Center is one of the health centers in Marihat in Pematangsiantar city. Every day the number of patients who come and perform medical treatment at this health center is quite a lot. The high number of patient visits at this puskesmas causes the amount of medical record data to be very large as well. So far, data containing information about patients at the puskesmas has not been used properly. This information can actually be used as knowledge for puskesmas, especially for patients who have a history of ARI disease. Therefore, the purpose of this study was to classify patients with ARI at the Puskesmas. The method used is K-Means clustering. The results of this study were able to classify ARI patients into 2 clusters, cluster 1 gave a high recommendation of 72 patients, and cluster 2 gave a low recommendation of 70 patients. The cluster process stops at the 5th iteration of data. Based on the manual calculation process using Ms. Excel and testing using Rapidminer 5.3, yielded the same value. It can be concluded that in this case, the K-Means algorithm can classify ARI patients at the Bah Biak health center well.

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Published

2022-04-30

How to Cite

Agoestina, F. S., Tambunan, H. S., & Nasution, R. A. (2022). Pemanfaatan Algoritma K-Means untuk Pengelompokkan Pasien Penyakit Infeksi Saluran Pernafasan Akut (ISPA). SATESI: Jurnal Sains Teknologi Dan Sistem Informasi, 2(1), 60–69. https://doi.org/10.54259/satesi.v2i1.804

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