Vol 12 No 2 (2019): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)

Pemodelan Bayesian Network untuk Prediksi Penyakit Saluran Pernapasan

Novi Indah Pradasari (Politeknik Negeri Ketapang)
Rizqia Lestika Atimi (Unknown)

Article Info

Publish Date
05 Oct 2019


This Bayesian network model was developed by analyzing the correlation between the cause of disease symptom variables and disease variables. The Bayesian network is a method that can depict causality between variables in a system. In this research, the Bayesian network was developed with a scoring based method and it was implemented using a hill-climbing algorithm with scoring BIC score function approach. There were 18 variables and 31 arcs representing the interconnection between symptom variable and respiratory tract disease. In the testing phase, the inference process using approximate inference was carried out and the accuracy was nearly 100% for all testing scenarios. The application of this method could result in a representative Bayesian network. Its resulted structure was affected so much by data condition, thus data cleaning was important to do before the training and testing phase.

Copyrights © 2019

Journal Info





Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering


Journal Petir is a scientific journal published by STT-PLN Department of Information Engineering since 2007, as a media for disseminating research results, Library Study Technique, Observation Result, Surveying Survey, STT-PLN Department of Informatics Engineering and Supporting Science Development ...