Implementation of AdaBoost Algorithm in Prediction of Chronic Kidney Disease

The kidneys are one of the important organs for humans with various tasks to keep humans healthy. One of them is to remove excess water and toxins from the blood. The chronic kidney is a disease that interferes with kidney function that is progressive and irreversible in which the body's abilit...

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Bibliographic Details
Published in:	2021 7th International Conference on Engineering, Applied Sciences and Technology (ICEAST) pp. 264 - 268
Main Authors:	Asra, Taufik, Setiadi, Ahmad, Safudin, Mahmud, Lestari, Endah Wiji, Hardi, Nila, Alamsyah, Doni Purnama
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-04-2021
Subjects:	Accuracy AdaBoost Algorithm Classification algorithms Electrolytes Fluids Kidney Kidney Disease Prediction algorithms Predictive models Task analysis
Online Access:	Get full text
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Summary:	The kidneys are one of the important organs for humans with various tasks to keep humans healthy. One of them is to remove excess water and toxins from the blood. The chronic kidney is a disease that interferes with kidney function that is progressive and irreversible in which the body's ability to fail to maintain metabolism and fluid and electrolyte balance resulting in uremia. There have been many studies aimed at predicting chronic kidney disease. In this study, using the C4.5 algorithm as a classification algorithm and by adding the Adaboost algorithm. The results showed that using the algorithm obtained an accuracy value of 95%, 92% precision, and Area Under the Curve by 1. Whereas using the algorithm combined with Adaboost got an accuracy value is precision, and Area Under the Curve by 1. Based on the results accuracy, precision, and Area Under the Curve, it can be seen by using Adaboost in the algorithm can improve the results of accuracy and precision with very good classification, because the Area Under the Curve value is accepted.
DOI:	10.1109/ICEAST52143.2021.9426291