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All Journal Elkom: Jurnal Elektronika dan Komputer LET: Linguistics, Literature and English Teaching Journal INTECOMS: Journal of Information Technology and Computer Science Petir Community Engagement and Emergence Journal (CEEJ) SmartComp
Novi Indah Pradasari
Politeknik Negeri Ketapang
Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media

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Journal : Petir

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Pemodelan Bayesian Network untuk Prediksi Penyakit Saluran Pernapasan Novi Indah Pradasari; Rizqia Lestika Atimi
PETIR Vol 12 No 2 (2019): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (476.906 KB) | DOI: 10.33322/petir.v12i2.637

Abstract

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.
Co-Authors Darmanto Darmanto Eka Wahyudi Indra Pratiwi Ivan Suwanda . M Khadafi Rizqia Lestika Atimi . Ruhibnur, Refid Safar Dwi Kurniawan