Show simple item record

dc.contributor.authorKRISTINA, Bibi Candra
dc.contributor.authorHADI, Alfian Futuhul
dc.contributor.authorRISKI, Abduh
dc.contributor.authorKAMSYAKAWUNI, Ahmad
dc.contributor.authorANGGRAENI, Dian
dc.date.accessioned2020-11-18T06:12:38Z
dc.date.available2020-11-18T06:12:38Z
dc.date.issued2020-09-21
dc.identifier.urihttp://repository.unej.ac.id/handle/123456789/102058
dc.descriptionAhmad Dahlan International Conference on Mathematics and Mathematics Education 8-9 November 2019, Yogyakarta, Indonesiaen_US
dc.description.abstractIn the classical-classification multivariate process, it becomes an interesting topic to be discussed in the research area because of the larger variables with smaller observations. For this we need a method that can handle this problem. One answer is to use machine learning. SVM is a classification method in machine learning that is able to classify these data types. In addition, SVM can also model and classify relationships between variables efficiently and easy interpretation. This paper aims to create a visualization of SVM classifiers, then obtain an accuracy value to have an optimal classification with a misclassification of small numbers. This study aims to find good SVM input parameters by assessing the importance of variables using visual methods. This visualization will distinguish groups of people who contract diffuse lymphoma cancer and follicular lymphoma cancer with data on the genetic expression of lymphoma cancer. The classification using kernel Linear, Gaussian RBF, Polynomial and Sigmoid. The best classification accuracy using linear kernel functions with training data has a classification accuracy of 100% and testing data has a classification accuracy of 94, 73%.en_US
dc.language.isoenen_US
dc.publisherJournal of Physics: Conference Series IOP Publishing, 1613 (2020) 012065en_US
dc.subjectsupport vector machineen_US
dc.subjectlymphoma canceren_US
dc.titleThe Visualization and Classification Method of Support Vector Machine in Lymphoma Canceren_US
dc.typeArticleen_US
dc.identifier.kodeprodikodeprodi1810101#Matematika
dc.identifier.nidnNIDN019077403
dc.identifier.nidnNIDN0006049001
dc.identifier.nidnNIDN0029117202
dc.identifier.nidnNIDN0016028201


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record