Skripsi

PENERAPAN METODE REGRESI LOGISTIK BINER UNTUK MENGKLASIFIKASI RISIKO PENYAKIT JANTUNG

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Penilaian

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The heart is a human organ that plays a role in the circulatory system. Heart disease is a condition in which the heart cannot do its job properly. Heart disease is a disease that plays a major role as the number one cause of death worldwide. In this study, the risk of heart disease will be predicted based on age, gender, type of chest pain, lower limit blood pressure, cholesterol, fasting blood sugar, electrocardiography results, maximum heart rate, exercise that induces pain, depression induced by strenuous exercise, peak slope. ST segment, the number of major blood vessels and the type of vascular damage to be predicted in the sick or healthy group. This study aims to apply the binary logistic regression method in predicting the risk of heart disease. Based on the calculation results, the variables that affect the risk of heart disease are gender, chest pain, ECG (electrocardiogram) results, number of heartbeats, ST segments obtained from exercise relative to rest and heart status and the average level of overall classification accuracy with cross varidation of 49.38%. Keywords : Heart Disease, Classification, Binary Logistic Regression.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107003405	T52736	T527362021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T527362021

Publisher

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

Collation

xii, 40 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

513.507

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
Sistem Numerik- Regresi Logistik Biner

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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