Ramadhan, Almudava Ainur Rizky (2025) Application of classification and regression trees and k-nearest neighbor algorithms on website-based maternal health classification / Almudava Ainur Rizky Ramadhan</p>. Diploma thesis, Universitas Negeri Malang.
Full text not available from this repository.Abstract
p The high maternal mortality rate in Indonesia is still quite high indicating the need for efforts to maintain the health of pregnant women. A data-based approach can be an important step to overcome this problem. This study aims to create a website for a maternal health classification system to classify pregnancy health risks using the Classification and Regression Trees (CART) and K-Nearest Neighbor (KNN) algorithms that can be used for medical personnel in hospitals and integrated health posts. The website development system uses the waterfall method and the streamlit framework. The final result of this study the best model for CART was 92.38% accuracy with data treatment using oversampling and without hyperparameter tuning while the best model for KNN was 91.34% accuracy with data treatment using oversampling and hyperparameter tuning. /p
| Item Type: | Thesis (Diploma) |
|---|---|
| Divisions: | Fakultas Matematika dan IPA (FMIPA) > Departemen Matematika (MAT) > S1 Matematika |
| Depositing User: | library UM |
| Date Deposited: | 19 May 2025 04:29 |
| Last Modified: | 09 Sep 2025 03:00 |
| URI: | http://repository.um.ac.id/id/eprint/394692 |
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