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All Journal Jurnal Penelitian Rumpun Ilmu Teknik
Angelita A. S. M. Limbong
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Computer Science & IT Engineering

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Klasifikasi Penyakit Diabetes Menggunakan Metode SVM Dan KNN Aswin Ardiansyah; Enos C.O.Telaumbanua; Aron S. Gultom; Angelita A. S. M. Limbong
Jurnal Penelitian Rumpun Ilmu Teknik Vol. 3 No. 1 (2024): Februari : Jurnal Penelitian Rumpun Ilmu Teknik
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juprit.v3i1.3151

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.
Co-Authors Aron S. Gultom Aswin Ardiansyah Enos C.O.Telaumbanua