Authors:

VANIA RISKASARI YR, I PUTU EKA NILA KENCANA, I KOMANG GDE SUKARSA

Abstract:

“Cirrhosis is one type of liver disease and is caused by forming fibrosis so that changes the liver structure become abnormal. Based on the presence of ascites, varicose veins, and bleeding, cirrhosis is divided into four clinical stages. This study aims to find the best classification model of cirrhosis using the support vector machine (SVM). SVM is a supervised learning method that aims to find the hyperplane with the maximum margin. In this study, the resulted model useful for determining the cirrhosis’ stage from patients. The variables to classify are age, gender, ascites status, hepatomegaly status, spiders status, edema status, total bilirubin, total cholesterol, amount of albumin, amount of copper, alkaline phosphatase level test results, SGOT test results, amount of tryglycerides, amount of platelets, and prothrombin time. By applying radial basis function kernel, combination of parameter C and that gives the best accuracy is determined. The final model using SVM with parameters C = 1 and = 0,6 is the best model with the accuracy value of 67,86 percent.”

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PDF:

https://jurnal.harianregional.com/mtk/full-96413

Published

2023-05-31

How To Cite

RISKASARI YR, VANIA; KENCANA, I PUTU EKA NILA; SUKARSA, I KOMANG GDE. KLASIFIKASI PENYAKIT SIROSIS MENGGUNAKAN SUPPORT VECTOR MACHINE.E-Jurnal Matematika, [S.l.], v. 12, n. 2, p. 87-91, may 2023. ISSN 2303-1751. Available at: https://jurnal.harianregional.com/mtk/id-96413. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/MTK.2023.v12.i02.p404.

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ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol 12 No 2 (2023)

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License