Glucose Calibration Modeling in Blood with Spline Regression Approaching to Non-Invasive Tools

Authors

  • Ria Hayatun Nur  Statistics Department, Bogor Agricultural University, Bogor, West Java, Indonesia
  • Indahwati  Statistics Department, Bogor Agricultural University, Bogor, West Java, Indonesia
  • Erfiani  

DOI:

https://doi.org/10.32628/IJSRSET2184111

Keywords:

Diabetes Mellitus, Glucose, Spline, Regression

Abstract

In this globalization era, health is the most important thing to be able to run various activities. Without good health, this will hinder many activities. Diabetes mellitus is one of the diseases caused by unhealty lifestyle.There are many treatments that can be done to prevent the occurrence of diabetes. The treatments are giving the insulin and also checking the glucose rate to the patients.Checking the glucose rate needs the tools which is safety to the body. This research want to develop non invasive tool which is safety and do not injure the patient. The purpose of this research is also finding the best model which derived from Linear, Quadratic, and Cubic Spline Regression. Some respondents were taking to get the glucose measuring by invasive and non invasive tools. It could be seen clearly that Spline Linear Regression was the best model than Quadratic and Cubic Spline Regression. It had 70% and 33.939 for R2 and RMSEP respectively.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-12-30

Issue

Volume 4, Issue 11, November-December-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Ria Hayatun Nur, Indahwati, Erfiani "Glucose Calibration Modeling in Blood with Spline Regression Approaching to Non-Invasive Tools" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 11, pp.144-149 , November-December-2018. Available at doi : https://doi.org/10.32628/IJSRSET2184111