MULTICLASS CLASSIFICATION STADIUM PENYAKIT JANTUNG MENGGUNAKAN METODE NAIVE BAYES

GIRI, ALAM KUSUMA and Rini, Dian Palupi and Rodiah, Desty (2022) MULTICLASS CLASSIFICATION STADIUM PENYAKIT JANTUNG MENGGUNAKAN METODE NAIVE BAYES. Undergraduate thesis, Sriwijaya University.

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Abstract

Coronary heart disease is one of disease that causes abnormalities in heart function. Coronary heart disease has 4 stages from stage 1 to stage 4. This study uses the Naive Bayes method in classifying 5 classes of heart disease stages because other studies using the Naive Bayes method produce a fairly high accuracy value and can be used on categorical data. Classification of 5 classes of heart disease stages is done by converting numeric data into categorical data and then multiplying the label probability by the probability of each attribute category of each data. The amount of data used is 297. The distribution of data for model testing uses the K-Fold Cross Validation method with a value of k = 5 which divides the data into 5 parts. The classification accuracy test uses a confusion matrix model which gives an average classification performance of 52.5924%, an average precision of 24.8339%, and an average recall of 26.9122%. The greatest accuracy is obtained in fold 3, which is 57.6271% and the smallest accuracy is obtained in fold 5, which is 42.623%

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Confusion Matrix, K-Fold Cross Validation, Naive Bayes, Penyakit Jantung
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. Q Science > QA Mathematics > QA299.6-433 Analysis > Q334.A755 Artificial intelligence. Computational linguistics. Computer science. R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics T Technology > T Technology (General) > T10.5-11.9 Communication of technical information
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Alam Kusuma Giri
Date Deposited:	29 Jul 2022 04:30
Last Modified:	28 Feb 2023 06:43
URI:	http://repository.unsri.ac.id/id/eprint/75211

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