Skripsi

 KOMPARASI METODE KLASIFIKASI DECISION TREE ALGORITMA C4.5 DAN NAIVE BAYES DALAM MEMPREDIKSI SERANGAN JANTUNG

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Penilaian

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Heart attack is a heart disorder when the heart muscle does not receive blood flow. This condition interferes with the function of the heart in circulating blood throughout the body. According to WHO in Indonesia in 2021, there are 17.8 million deaths from heart attacks. Therefore, it is quite important to predict someone who has a heart attack so that it can be treated early. In this study, secondary data was used taken from the kaggle.com website, this data has 13 predictor variables and 1 target variable with 303 data on 2 classifications of heart attacks. Prediction of heart attack classification using the Naïve Bayes and Decision Tree methods.The results of this study are that for Split data 90% and 10% the accuracy rate for Naïve Bayes is 96,77% and Decision Tree is 77,42%. Keyword: Heart Attack, Naïve Bayes, Decision Tree

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307001733	T94998	T949982023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T949982023

Publisher

Inderalaya : Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Sriwijaya., 2023

Collation

xiv, 66 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

518.107

Content Type

Text

Media Type

unmediated

Carrier Type

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Edition

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Subject(s)

Algoritma
Jurusan Matematika

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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