Analisis Perbandingan Algoritma Machine Learning untuk Klasifikasi Tingkat Risiko Ibu Hamil

Authors

  • Rafiqi Aidil Fitra Universitas Negeri Medan
  • Wahyu Abadi Harahap Universitas Negeri Medan
  • Wahyu Kurnia Rahman Universitas Negeri Medan

DOI:

https://doi.org/10.55606/srjyappi.v1i6.846

Keywords:

Classification, Maternal Health Risk, Decision Tree, Naïve Bayes, K-Nearest Neighbors (KNN)

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.

References

Amalia, H., Rahmadanti, R., Syaiin, A., Salsabila, S., & Bina Sarana Informatika, U. (2012). Prediksi Risiko Kesehatan Ibu Hamil Dengan Menggunakan Metode Decision Tree. JURNAL SWABUMI, 11(1), 2023.

Brawijaya, H., Samudi, & Widodo, S. (2019). Komparasi Algoritma K-Nearest Neighbor dan Naiive Bayes pada Pengobatan Penyakit Kutil Menggunakan Cryotheraphy. JUITA: Jurnal Informatika, VII(2), 93–100.

Hasanah, Q., Andrianto, A., & Hidayat, M. A. (n.d.). Sistem Informasi Posyandu Ibu Hamil dengan Penerapan Klasifikasi Risiko Kehamilan Menggunakan Metode Naïve Bayes (Implementing Classification Risk in Posyandu System Information for Pregnant Using Naïve Bayes Method).

Nasrullah, A. H. (2021). IMPLEMENTASI ALGORITMA DECISION TREE UNTUK KLASIFIKASI PRODUK LARIS. 7(2). http://ejournal.fikom-unasman.ac.id

Nurahmadan, I. F., Agusta, A., Winarno, P. A., Sazali, B. H., Thurfah, Y., & Rosaliah, A. (2021). Perbandingan Algoritma Machine Learning Untuk Klasifikasi Denyut Jantung Janin. In Nurul Chamidah, S.Kom., M.Kom.

Susiana, S. (2019). Angka Kematian Ibu: Faktor Penyebab Dan Upaya Penanganannya. Bidang Kesejahteraan Sosial Info Singkat, XI(24), 13–18.

Utami, N., Dewi Puspitasari, R., Kurniawati, I., Graharti, R., & Yudho, A. (n.d.). Tingkat Pengetahuan Ibu Hamil Mengenai Kesehatan Ibu dalam Masa Kehamilan dan Nifas di RSUD Dr. H. Abdul Moeloek Bandar Lampung (Vol. 3).

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Published

2023-12-08

How to Cite

Rafiqi Aidil Fitra, Wahyu Abadi Harahap, & Wahyu Kurnia Rahman. (2023). Analisis Perbandingan Algoritma Machine Learning untuk Klasifikasi Tingkat Risiko Ibu Hamil. Student Research Journal, 1(6), 246–261. https://doi.org/10.55606/srjyappi.v1i6.846

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