Klasifikasi Status Calon Pendonor Darah Menggunakan Algoritma Support Vector Machine dan Kernel RBF

Jurnal ICT : Information Communication & Technology

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Field Value
 
Title Klasifikasi Status Calon Pendonor Darah Menggunakan Algoritma Support Vector Machine dan Kernel RBF
 
Creator Suryadi, Usep Tatang
Andriyani, Nindi Azis
 
Subject Donor Darah Support Vector Machine Metode Sequential, Kernel Rbf
 
Description To donate blood, generally must qualify the requirements, including physically and mentally healthy, aged 17-65 years, minimum body weight of 45kg, Hb levels 12.5g% - 17.0g%, upper tension (systole) 100-170mmHg, under tension (diastole) 70-100mmHg, 36.6-37.5 degrees Celsius body temperature, never had hemophilia, pulse range 50-100 times/minute, and the timescales > 3 months after a previous blood donors. The problem that arises is the small number of officers who often have difficulty recording donor data on the form sheets. Thus allowing unwanted error occurred when registering the identity or the results of the initial examination of prospective donors. Based on these problems, the classification of potential donors is needed as a step to determine the status of potential donors, whether the prospective donors are accepted as donors or rejected based on predetermined requirements. According to this research that using primary data which obtained from The Indonesian Red Cross Subang Regency, the data are using a plenty 50 of the data has accepting and 50 of the data has rejected. Afterwards required to doing continued analysis toward a method capability based on age, Hb level, body weight, sistolik dan diastolik, that using SVM (Support Vector Machine) algorithm.and using Sequential method for training phase in SVM and Kernel RBF for calculating the dot product value. The algotirhm accuration reached 90% / excellent categories with the value gamma = 0.5, C = 1, epsilon = 0.001.
 
Publisher STMIK IKMI Cirebon
 
Contributor Palang Merah Indonesia Kabupaten Subang.
 
Date 2020-09-09
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://ejournal.ikmi.ac.id/index.php/jict-ikmi/article/view/113
10.36054/jict-ikmi.v19i1.113
 
Source Jurnal ICT : Information Communication & Technology; Vol 19, No 1 (2020): JICT-IKMI, Juli 2020; 27-33
2303-3363
2302-0261
10.36054/jict-ikmi.v19i1
 
Language eng
 
Relation https://ejournal.ikmi.ac.id/index.php/jict-ikmi/article/view/113/pdf
https://ejournal.ikmi.ac.id/index.php/jict-ikmi/article/downloadSuppFile/113/21
 
Rights Copyright (c) 2020 Jurnal ICT : Information Communication & Technology
https://creativecommons.org/licenses/by/4.0
 

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