BERKALA SAINSTEK
Vol 10 No 3 (2022)

Classification of Cardiovascular Disease Gene Data Using Discriminant Analysis and Support Vector Machine (SVM)

Prayogo, Rizky (Unknown)
Anggraeni, Dian (Unknown)
Hadi, Alfian Futuhul (Unknown)



Article Info

Publish Date
04 Oct 2022

Abstract

Cardiovascular disease is a disease caused by impaired function of the heart and blood vessels. This disease is caused by many factors, one of which is genetics, while the causes are age, gender, and family history. In this study, classification of 62 individuals with normal response and cardiovascular disease was carried out. Discriminant Analysis (AD) is a method that classifies data into two or more groups based on several variables where data that has been entered into one group will not be included in another group. The Support Vector Machine (SVM) performs classification by building an N-dimensional hyperplane that optimally separates data into two categories in the input space. Furthermore, AD and SVM will be compared to get which method has the best accuracy, after that it will be added to clustering using k-means and k-means kernels to improve the accuracy of each method. The results of this study are AD and SVM have accuracy values of 83.33% and 91.66%, for AD and SVM which are subjected to k-means have accuracy values of 91.66 % and 91.66 %, and for AD and SVM subjected to k-means kernel has an accuracy value of 100 % and 100 %.

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Journal Info

Abbrev

BST

Publisher

Subject

Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Mathematics Physics

Description

Berkala SAINSTEK (BST) merupakan jurnal ilmiah yang memuat artikel hasil penelitian di bidang sains dan teknologi. Secara khusus BST diperuntukan bagi penulis internal mahasiswa Universitas Jember bidang fisika, matematika, biologi, kimia, teknik sipil, teknik mesin, teknik elektro dan sistem ...