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primary topic: KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE
type: Thesis
type: Article
abstract: Breast cancer is one of the non-communicable diseases that causes death worldwide, particularly among women. Early detection and classification of the survival status or death of breast cancer patients are crucial in determining appropriate treatment. This study aims to examine the performance steps of the SVM algorithm, assess the performance of the SVM algorithm using linear, polynomial, RBF, and sigmoid kernel methods, and identify the best-performing SVM kernel in this classification. The data used in this study were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program, November 2017 version, which includes female patients diagnosed with infiltrating duct and lobular carcinoma breast cancer between 2006 and 2010. There are 14 independen variables, namely: age, race, marital status, t stage, n stage, 6th stage, grade, a stage, tumor size, estrogen status, progesterone status, regional node examined, regional node positive, and survival months. The dependen variable is status. The method used involves four SVM kernels: linear, polynomial, Radial Basis Function (RBF), and sigmoid. The accuracy results obtained are as follows: linear kernel: 91.105%, polynomial kernel: 90.384%, RBF kernel: 91.225%, and sigmoid kernel: 90.384%. The best performance result in this classification was achieved by the RBF kernel.
date: 2025-06-05
status: published
author list: authors
type: EPrint
type: ThesisEPrint
is part of: repository
has document: KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Text)
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has document: KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Other)
subject: 510 Mathematics (Matematika)

KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Text)
type: Document
has file: 21106010038_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf
has part: 21106010038_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf

KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Text)
type: Document

UIN SUNAN KALIJAGA YOGYAKARTA
type: Organization

FAKULTAS SAINS DAN TEKNOLOGI, UIN SUNAN KALIJAGA YOGYAKARTA
type: Organization

NIM.: 21106010038 Refina Nur Asmia
type: Person
given name: NIM.: 21106010038
family name: Refina Nur Asmia

KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Other)
type: Document
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KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Other)
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KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Other)
type: Document
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KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Other)
type: Document
is version of: KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Text)
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KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Other)
type: Document
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KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Other)
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KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Other)
type: Document
is version of: KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Text)
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KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Other)
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is version of: KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (Text)
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primary topic: KLASIFIKASI KANKER PAYUDARA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

510 Mathematics (Matematika)
type: Concept