Implementasi Metode Naïve Bayes untuk Klasifikasi Penderita Penyakit Jantung

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Published: Jul 1, 2023
DOI: https://doi.org/10.35870/jtik.v7i3.910
Keywords:
Naïve Bayes, Heart Disease, Classification
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Bowo Hirwono
Universitas Teknologi Yogyakarta
Arief Hermawan
Universitas Teknologi Yogyakarta
Donny Avianto
Universitas Teknologi Yogyakarta

Abstract

Heart attack is a very serious heart disorder. This disorder occurs when the heart muscle does not get good blood flow. This condition will interfere with the function of the heart in flowing blood flow throughout the body. This study aims to develop a system capable of classifying people with heart disease using the Naïve Bayes method. Naïve Bayes is a method that works based on the probability that a person has a heart disease or not based on their medical record data. This algorithm is used with the aim of calculating the probability of a person suffering from heart disease based on their medical records. This data was obtained from the University of California Irvine Machine Learning website with a total of 303 datasets with 13 attributes. This research was conducted by dividing the data into 75% for training data and 25% for training data. The results of this study indicate that the Naïve Bayes algorithm used gives a fairly high accuracy value of 86.84%.

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How to Cite
Hirwono, B., Hermawan, A., & Avianto, D. (2023). Implementasi Metode Naïve Bayes untuk Klasifikasi Penderita Penyakit Jantung. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 7(3), 450–457. https://doi.org/10.35870/jtik.v7i3.910
Issue
Vol. 7 No. 3 (2023): JULY-SEPTEMBER 2023
Section
Computer & Communication Science
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Author Biographies

Bowo Hirwono, Universitas Teknologi Yogyakarta

Program Studi Informatika, Fakultas Teknik, Universitas Teknologi Yogyakarta, Kabupaten Sleman, Daerah Istimewa Yogyakarta, Indonesia

Arief Hermawan, Universitas Teknologi Yogyakarta

Program Studi Magister Teknologi Informasi, Fakultas Teknik, Universitas Teknologi Yogyakarta, Kabupaten Sleman, Daerah Istimewa Yogyakarta, Indonesia

Donny Avianto, Universitas Teknologi Yogyakarta

Program Studi Magister Teknologi Informasi, Fakultas Teknik, Universitas Teknologi Yogyakarta, Kabupaten Sleman, Daerah Istimewa Yogyakarta, Indonesia

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