Klasifikasi Penyakit Diabetes Menggunakan Metode SVM Dan KNN

Authors

  • Aswin Ardiansyah Universitas Negeri Medan
  • Enos C.O.Telaumbanua Universitas Negeri Medan
  • Aron S. Gultom Universitas Negeri Medan
  • Angelita A. S. M. Limbong Universitas Negeri Medan

DOI:

https://doi.org/10.55606/juprit.v3i1.3151

Keywords:

Classification, Diabetes, SVM, KNN, Confusion Matrix

Abstract

Diabetes is a disease caused by high blood sugar levels and impaired insulin production in the body. Although it is not a contagious disease, in fact, many Indonesians suffer from diabetes. In fact, according to the North Sumatra Health Department, the prevalence of diabetes in Indonesia is estimated to reach 21.3 million people by 2030. As technology develops, machine learning has helped many health practitioners in dealing with diabetes, one of which is modeling with SVM and KNN. The application of this algorithm aims to create a model that is able to classify diabetes in patients based on data of diabetes factors such as age, weight, blood pressure, blood sugar levels, etc. The model that has been built is then evaluated for its performance with a confusion matrix, with the evaluation results of the SVM model being better than KNN with an accuracy of 100% for the SVM model and an accuracy of 96% for the KNN model.

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Published

2023-12-16

How to Cite

Aswin Ardiansyah, Enos C.O.Telaumbanua, Aron S. Gultom, & Angelita A. S. M. Limbong. (2023). Klasifikasi Penyakit Diabetes Menggunakan Metode SVM Dan KNN. Jurnal Penelitian Rumpun Ilmu Teknik, 3(1), 77–83. https://doi.org/10.55606/juprit.v3i1.3151