Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal OKTAL : Jurnal Ilmu Komputer dan Sains
Mia Septiana Wambrauw
Unknown Affiliation
Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
LITERATURE REVIEW: PENERAPAN GRADIENT BOOSTING UNTUK KLASIFIKASI PENYAKIT DIABETES TIPE 2 Emison Wonda; Mia Septiana Wambrauw; Renaldi Ferrari; Rizka Gifani Napitupulu; Rosita Hermalinda Dwi Febrianti
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 10 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Diabetes mellitus type 2 is a metabolic condition with a rising global prevalence. Accurate classification is crucial for proper diagnosis and management. This research reviews the literature on the application of Gradient Boosting algorithms, particularly XGBoost and LightGBM, in classifying type 2 diabetes. The review indicates that Gradient Boosting algorithms have significant potential in improving the accuracy of disease diagnosis and risk prediction. Studies examined demonstrate the ability of these algorithms to handle complex data, achieve high accuracy rates, and address class imbalance issues. Moreover, parameter optimization such as hyperparameter tuning can significantly enhance model performance. This review highlights the benefits and potential of Gradient Boosting algorithms in enhancing healthcare systems through early detection and more effective management of type 2 diabetes.
Co-Authors Emison Wonda Renaldi Ferrari Rizka Gifani Napitupulu Rosita Hermalinda Dwi Febrianti