Student Research Journal
Vol. 1 No. 6 (2023): Desember : Student Research Journal

Analisis Perbandingan Algoritma Machine Learning untuk Klasifikasi Tingkat Risiko Ibu Hamil

Rafiqi Aidil Fitra (Universitas Negeri Medan)
Wahyu Abadi Harahap (Universitas Negeri Medan)
Wahyu Kurnia Rahman (Universitas Negeri Medan)

Article Info

Publish Date
08 Dec 2023

Abstract

This research aims to conduct a comparative analysis of machine learning algorithms for classifying the risk levels of maternal health. With a focus on the significance of identifying and classifying health risks for pregnant women, this study applies supervised learning methods employing Naïve Bayes, Decision Tree, and K-Nearest Neighbors algorithms. Utilizing the "Maternal Health Risk" dataset from UCI Machine Learning, the research is conducted on Google Colaboratory using Python. The results indicate that the Decision Tree algorithm achieves the highest accuracy rate at 90%, surpassing K-Nearest Neighbors (86%) and Naïve Bayes (65%). Consequently, Decision Tree emerges as the preferred choice for predicting maternal health risks, offering the potential for enhanced care and monitoring.

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Journal Info
Student Research Journal
Website

Abbrev

srj

Publisher

Sekolah Tinggi Ilmu Administrasi Yappi Makassar

Subject

Religion Humanities Economics, Econometrics & Finance Education Social Sciences

Description

1. Ilmu Sosial 2. Ilmu Ekonomi 3. Akuntansi 4. Manajemen 5. Kebudayaan 6. Pendidikan 7. Sejarah 8. Pariwisata 9. Gender 10. Humaniora 11. Seni Budaya 12. Linguistik 13. Sastra 14. Filsafat 15. Studi Agama 16. Studi Media dan Komunikasi 17. Berbagai bidang penelitian yang ...