Authors:

I GEDE SEKA SUYOGA, I PUTU EKA NILA KENCANA, I KOMANG GDE SUKARSA

Abstract:

“Tuition fee is the payment of tuition fees each semester borne by each student based on their economic capabilities. Tuition fee is divided into five groups from tuition fee group 1 to tuition fee group 5. This research aims to find the accuracy of the classification of tuition fee using Support Vector Machine (SVM). SVM is a method used for classification of the concept to find hyperplane (separator function) that can separate the data into a predetermined class. In this research, SVM is used to determine the accuracy of tuition fee classification. The variables used are income parents, father’s occupation, mother’s occupation, home ownership status, building, land area, electricity cost, water cost, phone cost, saving accounts, jewelry ownership, and a premium ownership. The results obtained are five hyperplanes to separate tuition fee with accuracy of the classification of tuition fee was 59,69%.”

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PDF:

https://jurnal.harianregional.com/mtk/full-35470

Published

2017-11-28

How To Cite

SUYOGA, I GEDE SEKA; KENCANA, I PUTU EKA NILA; SUKARSA, I KOMANG GDE. PENGGOLONGAN UANG KULIAH TUNGGAL MENGGUNAKAN SUPPORT VECTOR MACHINE.E-Jurnal Matematika, [S.l.], v. 6, n. 4, p. 220-225, nov. 2017. ISSN 2303-1751. Available at: https://jurnal.harianregional.com/mtk/id-35470. Date accessed: 02 Jun. 2025. doi:https://doi.org/10.24843/MTK.2017.v06.i04.p169.

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Issue

Vol 6 No 4 (2017)

Section

Articles

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