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PENERAPAN ALGORITMA RELIEFF DAN BACKPROPAGATION NEURAL NETWORK (BNN) DALAM PENANGANAN DATA HILANG DAN KLASIFIKASI PENYAKIT JANTUNG

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Penilaian

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Classification is the process of classifying an object based on a certain model. This process is often used in various fields, such as health, environment, and data research. One application of classification in the health sector is to predict factors for heart disease. The dataset used to predict cardiovascular disease factors comes from the University of California Irvine (UCI). This dataset has a weakness there is missing data in some features. Missing data can be overcome by applying the ReliefF algorithm, where each feature is sorted from the largest weight to the smallest weight. The advantage of the ReliefF algorithm is that it does not limit the data types used and can effectively deal with multiclass problems, missing data, and noise tolerance. In this research, the application of the ReliefF algorithm and testing using the Backpropagation Neural Network (BNN) method was carried out to determine the best features of the predictive factors for heart disease. Before applying the ReliefF algorithm in the detection of heart disease, the accuracy, precision, and recall values obtained were 77.21%, 72.31%, and 76.60%. Meanwhile, after applying the ReliefF algorithm, the performance evaluation results obtained were 84.01%, 80.09%, and 84.76%. Based on the performance results obtained through testing using the Backpropagation Neural Network (BNN) method, these values indicate that the ReliefF algorithm can be used to select the most influential and good features to increase the level of accuracy in predicting heart disease patients.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2207002971	T73145	T731452022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T731452022

Publisher

Inderalaya : Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2022

Collation

xii, 53 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

518.107

Content Type

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Media Type

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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

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