Result comparison between categorical and numerical predictor variables on CART method in predicting factors related to diabetic retinopathy in patients with type 2 diabetes mellitus

S. F. Hariany, Titin Siswantining, Alhadi B., B. Budiman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

CART (Classification and Regression Tree) is a classification nonparametric method that employs learning sample to construct decision tree. Type 2 Diabetes mellitus is classified under diabetes mellitus group that could result in complication, both macrovascular and microvascular. Diabetic Retinopathy is a part of microvascular complication of diabetes mellitus that is considered as the most frequent cause of blindness in adult. Predicting factors related to diabetic retinopathy is important to be done to decrease the prevalence of diabetic retinopathy. The aim of this research is to determine the factor related to diabetic retinopathy in patients with type 2 diabetes mellitus using CART method. CART method is applied in two types of independent variable data (numeric and category). The research uses 174 patients with type 2 diabetes mellitus in Cipto Mangunkusumo Hospital Jakarta as its sample. From the result of analyzing numeric data, the factor related with diabetic retinopathy is microalbuminuria, blood creatinine, gylocohemoglobin, and triglyceride. Meanwhile, from categorical data, factors that has correlation with diabetic retinopathy is microalbuminuria, 2 hour post prandial glucose, the history of diabetes mellitus in the family, and fasting blood glucose. From these two types of data that are analyzed using CART method, it is concluded that microalbuminuria is considered as the major factor that is related to diabetic retinopathy in patients with type 2 diabetes mellitus.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
EditorsRatna Yuniati, Terry Mart, Ivandini T. Anggraningrum, Djoko Triyono, Kiki A. Sugeng
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735417410
DOIs
Publication statusPublished - 22 Oct 2018
Event3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017 - Bali, Indonesia
Duration: 26 Jul 201727 Jul 2017

Publication series

NameAIP Conference Proceedings
Volume2023
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
CountryIndonesia
CityBali
Period26/07/1727/07/17

Keywords

  • Classification and Regression Tree
  • diabetes mellitus type 2
  • microalbuminuria

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    Hariany, S. F., Siswantining, T., B., A., & Budiman, B. (2018). Result comparison between categorical and numerical predictor variables on CART method in predicting factors related to diabetic retinopathy in patients with type 2 diabetes mellitus. In R. Yuniati, T. Mart, I. T. Anggraningrum, D. Triyono, & K. A. Sugeng (Eds.), Proceedings of the 3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017 [020226] (AIP Conference Proceedings; Vol. 2023). American Institute of Physics Inc.. https://doi.org/10.1063/1.5064223