ALGORITMA PENGAPLIKASIAN CLASSIFICATION BASED ON ASSOCIATION UNTUK KLASIFIKASI RESIKO PEMBERIAN KREDIT (Studi Kasus: PT. Telkom CDC Sub Area Kupang)
| Main Authors: | , Robynson Willson Oktovianus Amseke, , Drs. Edi Winarko, M.Sc., Ph.D |
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| Format: | Thesis NonPeerReviewed |
| Terbitan: |
[Yogyakarta] : Universitas Gadjah Mada
, 2013
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| Subjects: | |
| Online Access: |
https://repository.ugm.ac.id/123528/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=63640 |
Daftar Isi:
- This can be solved One of the causes of non-performing loans come from the internal, is caused by a lack of rigorous team in conducting the survey and analysis, or it could be due to subjective evaluation and analysis. using other selection techniques that have the thoroughness of analysis and objective assessment, the computer application that uses data mining techniques. This algorithm is Data mining technique was used in this study to classify credit risk by applying algorithms Classification Based on Association (CBA). an algorithm classification of data mining which integrating association and classification techniques. Preprocessed initial-credit data, will be processed using the CBA algorithm to create a model of which is to classify the new loan data into swift class or bad one. was measured Testing techniques the accuracy of the model by 10-fold cross validation. The result shows that the accuracy average value using the CBA algorithm (57,86%), was slightly higher than those using the algorithms of SVM and Naive Bayes from Rapid Miner 5.3 software (56,35% and 55,03%, respectively).