Aruni, Rani (2021) Penerapan Metode Naive Bayes Classifier untuk Klasifikasi Status Pinjaman. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
ABSTRACT Determining the criteria for applying for a loan is one of the most important factors for reducing arrears in payments. Data mining can be used to predict the risk of arrears by classifying borrowers applying for large loans. To prevent arrears, a system is needed that can classify borrower criteria so that it can provide input for the borrowing process with predictive analysis using the Naive Bayes Classifier method. The data used in this study were 1000 data where the data was divided into two, namely 600 training data and 400 test data. The accuracy for testing is 68.25%. With this system, it is hoped that it can provide an alternative in predicting potential borrowers in order to reduce the risk of arrears in payments. Keywords : Classification of Loan Status, Naive Bayes Classifier
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 26 Mar 2021 08:33 |
| Last Modified: | 26 Mar 2021 08:33 |
| URI: | http://eprints.uty.ac.id/id/eprint/7177 |
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