PEMODELAN RESIKO KREDIT DENGAN PENDEKATAN SUPPORT VECTOR MACHINE SUPPORT VECTOR MACHINE APPROACH TO CREDIT RISK
This study focuses on classification models using Support Vector Machine approach. This SVM has the advantage of data computation. The computation of finite data with complexity of the variables can be done using SVM. SVM for classification was applied in credit risk management. Classification was a...
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| Main Authors: | , |
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| 格式: | Theses and Dissertations NonPeerReviewed |
| 出版: |
[Yogyakarta] : Universitas Gadjah Mada
2012
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| 主題: | |
| 在線閱讀: | https://repository.ugm.ac.id/98055/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=54586 |
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| 總結: | This study focuses on classification models using Support Vector Machine
approach. This SVM has the advantage of data computation. The computation of
finite data with complexity of the variables can be done using SVM. SVM for
classification was applied in credit risk management. Classification was applied to
separate the credit application of the client of a particular Bank Perkreditan
Rakyat (BPR) into two classes, �good� and �bad�. A particular bank, which
classifies the credit application correctly, can minimize the risk of bankruptcy and
gain the society trust. By applying the classification, banks can prevent the
problems appear to default credit. |
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