Implementasi Support Vector Machine (SVM) Untuk Klasifikasi Dokumen
dc.contributor.advisor | Adisantoso, Julio | |
dc.contributor.author | Pratama, Dealis Hendra | |
dc.date.accessioned | 2013-09-03T02:34:03Z | |
dc.date.available | 2013-09-03T02:34:03Z | |
dc.date.issued | 2013 | |
dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/65220 | |
dc.description.abstract | Document classification is the process of grouping documents into specific categories that have been defined previously. In the real world, the distribution of the data is generally non-linear, which means the distribution of the data did not separate properly. Therefore we need a method that can classify documents that are non-linear. Support vector machine can classify documents that are non-linear with increasing dimension of the distribution of documents using kernel trick. This study will use a linear kernel for the classification of text documents. Results greatest accuracy in this study was 76% of 150 test documents with epsilon value 0.01. Factors affecting the results of the classification of which is the value of epsilon and length of test documents. | en |
dc.subject | Bogor Agricultural University (IPB) | en |
dc.subject | document classification. | en |
dc.subject | support vector machine | en |
dc.subject | linear kerne | en |
dc.subject | SVM | en |
dc.title | Implementasi Support Vector Machine (SVM) Untuk Klasifikasi Dokumen | en |
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UT - Computer Science [2323]