IMPLEMENTATION OF DATA MINING FOR DIABETES PREDICTION USING THE C4.5 ALGORITHM

Sabrina Aulia Rahmah

Abstract


This study focuses on the implementation of data mining techniques to predict diabetes using the C4.5 algorithm. Diabetes is a syndrome characterized by metabolic disturbances and abnormally high blood glucose levels due to insulin deficiency or decreased tissue sensitivity to insulin. Maintaining blood sugar levels is crucial for health, as it is a vital energy source for cells and tissues. The research employs various classification attributes, including weight, gender (as an auxiliary attribute), blood pressure, blood sugar levels, and diabetes history. These attributes are used to help individuals predict whether their diabetes is hereditary or non-hereditary.


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References


American Diabetes Association. (2021). Standards of medical care in diabetes.

American Heart Association. (2018). Understanding blood pressure readings.

Chen, H., Hailey, D., Wang, N., & Yu, P. (2017). A review of data mining applications in healthcare.

Han, J., Kamber, M., & Pei, J. (2012). Data mining: Concepts and techniques.

International Diabetes Federation. (2019). IDF Diabetes Atlas, 9th edition.

Jothi, N., & Husain, W. (2015). Data mining in healthcare – A review.

Karegowda, A. G., Manjunath, A. S., & Jayaram, M. A. (2011). Comparative study of attribute selection using gain ratio and correlation-based feature selection.

National Institute of Diabetes and Digestive and Kidney Diseases. (2020). Diabetes prevention.

Patil, B. M., & Kumaraswamy, Y. S. (2009). Intelligent and effective heart attack prediction system using data mining and artificial neural network.

Quinlan, J. R. (1993). C4.5: Programs for machine learning.

World Health Organization. (2020). Global report on diabetes.

Zhou, X. H., Obuchowski, N. A., & McClish, D. K. (2014). Statistical methods in diagnostic medicine.




DOI: https://doi.org/10.46576/ijsseh.v5i2.4685

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