Implementasi Algoritma C4.5 Untuk Deteksi Dini Penyakit Diabetes Mellitus Pada Manusia


Authors

  • Chandra STMIK Time, Medan, Indonesia
  • David STMIK Time, Medan, Indonesia
  • Hendri STMIK Time, Medan, Indonesia

DOI:

https://doi.org/10.47065/bulletincsr.v4i2.337

Keywords:

Prediction System; Diabetes Mellitus; Decision Tree; C4.5

Abstract

Diabetes is classified as one of the fastest growing life-threatening chronic diseases which has affected 422 million people worldwide according to the World Health Organization (WHO) report, in 2018. Therefore, it is very important to carry out early detection of DM disease because if the disease If left for too long without treatment, it can result in dangerous complications such as kidney failure, damage to the function of other organs to heart attacks. In this research an information system will be built by applying the C4.5 data mining algorithm for early detection of Diabetes Mellitus in humans. The dataset in this study was taken from the Kaggle Diabetes Dataset. The results of the study show that the information system built can assist the medical world in early detection of Diabetes Mellitus in humans through a predictive feature that implements the C4.5 algorithm. In addition, the results of testing the C4.5 algorithm show that the algorithm is classified as accurate in predicting early detection of Diabetes Mellitus if it follows the decision tree rules that are formed.

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ARTICLE HISTORY

Submitted: 2024-02-21
Published: 2024-02-26

Abstract View: 23 times

How to Cite

Chandra, David, & Hendri. (2024). Implementasi Algoritma C4.5 Untuk Deteksi Dini Penyakit Diabetes Mellitus Pada Manusia. Bulletin of Computer Science Research, 4(2). https://doi.org/10.47065/bulletincsr.v4i2.337

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