Skripsi

PREDIKSI RISIKO PENYAKIT JANTUNG KORONER DENGAN METODE ENSEMBLE MENGGUNAKAN ALGORITMA NAIVE BAYES, DECISION TREE C4.5 DAN REGRESI LOGISTIK BINER

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Penilaian

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Coronary heart disease is one of the causes with high amount of death in Indonesia. Coronary heart disease is a coronary atherosclerotic disease that causes narrowing of blood vessels. Therefore, there are many who conduct research on coronary heart disease both on a large and small scale which is carried out by a classification process using a certain algorithm. This research aims to predict the risk of heart disease using the Ensemble method by combining the three classification algorithms. The data used in this study has 16 variables with a total data of 4238 data. The classification prediction uses the Ensemble Majority Vote method by combining the Naive Bayes algorithm, Decision Tree C4.5 and Binary Logistics Regression. The results of this study indicate that the prediction of the risk of heart disease using the Ensemble Majority Vote method obtains an accuracy rate of 84.79%, a precision of 86.01%, and a recall of 97.91%

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107003421	T55008	T550082021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T550082021

Publisher

Inderalaya : Prodi Ilmu Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam., 2021

Collation

xiv, 79 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

518.107

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Prodi Ilmu Matematika
Algoritma Naive Bayes

Specific Detail Info

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Statement of Responsibility

MURZ

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