Skripsi

OPTIMASI FUZZY TSUKAMOTO DALAM MENENTUKAN PREDIKSI HASIL TINGKAT RISIKO PENYAKIT JANTUNG MENGGUNAKAN ALGORITMA ARTIFICIAL BEE COLONY

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Penilaian

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Heart disease is a common health problem. If not treated promptly, heart disease can have various impacts on a person's health, even causing death. To be able to prevent heart disease early, a method is needed that can determine whether a person is at risk of heart disease or not. This study can provide information about the risk of heart disease by determining predictions using the Fuzzy Tsukamoto method with Artificial Bee Colony optimization. The data studied amounted to 40 data, originating from the Heart Disease Dataset taken from Kaggle. To determine the prediction, 5 risk factor variables were used, namely age, cholesterol, blood sugar, blood pressure, and maximum heart rate. The results of the study showed a decrease in error value using Artificial Bee Colony optimization, namely with a MAPE (Mean Absolute Percentage Error) value from 42.43% to 36.28%. These results indicate that the Fuzzy Tsukamoto method optimized with Artificial Bee Colony can determine the prediction of the level of heart disease risk well.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507005298	T182205	T1822052025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1822052025

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xvii, 64 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

006.307

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Kecerdasan Buatan
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

KA

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