CD Skripsi

Implementasi algoritma random forest dalam klasifikasi metode persalinan pasien hipertensi di rumah sakit umum daerah Dumai

---

This study examines the application of the Random Forest algorithm to classify delivery methods among hypertensive patients at RSUD Dumai. The research is motivated by the issue of data imbalance, where cesarean deliveries are substantially more prevalent than normal deliveries. To address this challenge, two modeling approaches are implemented: a baseline model and an optimized model, with performance evaluated on both the original dataset and resampled data. The findings indicate that Random Forest achieves reliable performance even under imbalanced conditions, though it demonstrates a tendency to favor the majority class. The use of resampling techniques, particularly oversampling, improves predictive balance between classes and yields more representative classification outcomes, with an average accuracy of 71%, precision of 75%, recall of 83%, f1-score of 78%, and an AUC of 71%. Overall, the developed model provides a foundation for identifying delivery patterns among hypertensive patients. Nevertheless, the incorporation of synthetic data in medical research requires careful consideration to ensure that the results remain valid and applicable in real-world clinical contexts.

Keywords: Childbirth, Classification, Hypertension, Random Forest, RSUD Dumai

---

Ketersediaan

Informasi Detail

Judul Seri

-

No. Panggil

2103112016

Penerbit

Pekanbaru : Universitas Riau FMIPA Sistem Informasi., 2025

Deskripsi Fisik

-

Bahasa

Indonesia

ISBN/ISSN

-

Klasifikasi

2103112016

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

SISTEM INFORMASI

Info Detail Spesifik

-

Pernyataan Tanggungjawab

Mutia

Versi lain/terkait

Lampiran Berkas

Komentar

---

Anda harus masuk sebelum memberikan komentar