Klasifikasi Penyakit Jantung Menggunakan Extreme Gradient Boosting

Authors

  • Gillang Fernando Universitas Pamulang
  • Haekal Mimtazulfaqhi Zaydan Universitas Pamulang
  • Iqmal Akbar Universitas Pamulang
  • Ryan Dwi Irawan Universitas Pamulang

Keywords:

Penyakit Jantung, Klasifikasi, Extreme Gradient Boosting, Machine Learning, Prediksi Kesehatan

Abstract

Heart disease or cardiovascular disease is a condition that causes restriction and blockage of blood vessels, which is one of the most deadly diseases in all countries. Risk of disease Heart disease is an event that cannot be avoided due to lack of attention to heart health. implementing a healthy lifestyle and healthy diet. This requires a heart disease risk analysis. Explanation is one of the methods widely used to extract data to determine predictable decisions. based on previous data processed by translation algorithms.

References

Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 785-794.

Dua, D., & Graff, C. (2019). UCI Machine Learning Repository [https://archive.ics.uci.edu/ml].

Witten, I. H., Frank, E., & Hall, M. A. (2016). Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann.

Friedman, J. H. (2001). Greedy function approximation: A gradient boosting machine. Annals of Statistics, 1189-1232. Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer.

Published

2024-12-20

How to Cite

Fernando, G. ., Mimtazulfaqhi Zaydan, H., Akbar, I. ., & Dwi Irawan, R. . (2024). Klasifikasi Penyakit Jantung Menggunakan Extreme Gradient Boosting. BINER : Jurnal Ilmu Komputer, Teknik Dan Multimedia, 2(5), 667–670. Retrieved from https://journal.mediapublikasi.id/index.php/Biner/article/view/4613