PREDICTION OF GLUCOSE LEVEL IN DIABETICS WITH SUPPORT VECTOR REGRESSION

Prediksi Level Glukosa pada Penderita Diabetes dengan Support Vector Regression

  • Devi Wulandari (1*) Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
  • Agus Subekti (2) Lembaga Ilmu Pengetahuan Indonesia (LIPI)

  • (*) Corresponding Author
Keywords: Diabetes, Glukosa Level, Support Vector Regression

Abstract

One of the common diabetes factors that people hear is that they consume too much or often consume sweet foods or drinks so that blood sugar in the human body increases. The times and increasingly sophisticated technology make it easier for someone to be able to predict a disease such as diabetes with machine learning techniques. Therefore, from the existing problems, a machine learning technique will be made in predicting glucose levels in diabetics. The aim is to predict glucose levels in diabetics and find the best algorithm from several comparison algorithms. The results of the experiments carried out by the support vector regression algorithm have a lower mean squared error value of 28.9480 compared to other comparative algorithms and visualize the error classification seen that Instance no 47 has a prediction of the highest plasma glucose value of 189.2305.

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Author Biographies

Devi Wulandari, Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri

Masters in Computer Science

Agus Subekti, Lembaga Ilmu Pengetahuan Indonesia (LIPI)

Pusat Penelitian Informatika LIPI

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Wulandari, D., & Subekti, A. (2019). Laporan Akhir Penelitian Mandiri: Prediksi Level Glukosa Pada Penderita Diabetes Dengan Support Vector Regression.

Published
2020-03-31
How to Cite
Wulandari, D., & Subekti, A. (2020). PREDICTION OF GLUCOSE LEVEL IN DIABETICS WITH SUPPORT VECTOR REGRESSION. Jurnal Pilar Nusa Mandiri, 16(1), 97-102. https://doi.org/10.33480/pilar.v16i1.1264
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