Joined Journal (Journal of Informatics Education
Vol 7 No 1 (2024): Volume 7 Nomor 1 (2024)

Penentuan Jenis Persalinan Berdasarkan Faktor-Faktor Klinis Menggunakan K-NN dan Naive Bayes

Ibrahim, Kristianto Oggie (Unknown)
Candrasari, Diwahana Mutiara (Unknown)
Hariningsih, Rosa Ratri Kusuma (Unknown)



Article Info

Publish Date
30 Jun 2024

Abstract

The purpose of this research is to classify the type of normal or caesarean delivery using the K-NN and Naïve Bayes algorithms. The data used are data on maternal age, hemoglobin, gestational age, pregnancy problems. The results of this study show that the Naïve Bayes algorithm is able to classify the type of normal or cesarean delivery. With the validation method K-Fold Cross Validation and Confusion Matrix for the calculation of misclassification which will make us know how bad our model is in making predictions, to calculate the accuracy level of the classification method we use. The results show that in the calculation of Cross Validation validation, the accuracy presentation value is 63.57% for training data and 95.48% for testing data and in Confusion Matrix, the accuracy presentation value is 66.2% for training data and 96.18% for testing data.

Copyrights © 2024






Journal Info

Abbrev

jiptika

Publisher

Subject

Computer Science & IT Control & Systems Engineering Education Engineering Other

Description

JOINED JOURNAL is a peer-reviewed scientific journal published by Informatics Education Program in Universitas Ivet Central Java. This journal provides a platform for lecturers, researchers, students and practitioners to promote and share knowledge in the field of Informatics Education. Journals ...