MUHAMMAD, BINGAMAWA TOSAN (2016) Implementation of Naive Bayes Algorithm To Determine Customer Credit Status In PT. Multindo Auto Finance Semarang. Skripsi,Fakultas Ilmu Komputer.
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Abstract
As a finance company, PT. Multindo Auto Finance Semarang is giving fast, appropriate, and flexible finance solution for people to own cars. Finance solution offered by PT. Multindo Auto Finance Semarang is form as a credit loan. With the demand of the credit applicants, customer classification to provide information about customer credit status is needed for PT. Multindo Auto Finance Semarang. It is because credit risk will always be possible. An example of credit problems that frequently occur in the credit activity is loss credit. By using data mining classification approach that implemented in customer credit data, it would be possible to overcome the credit problems in PT. Multindo Auto Finance Semarang. In this study, Naive Bayes Classification Algorithm is performed for customer credit status categorization in PT. Multindo Auto Finance Semarang. Moreover, Cross-Industry Standard Process for Data Mining (CRISP-DM) and Knowledge Discovery in Database (KDD) phase are also performed for data processing technique. Experimental result of customer classification using customer credit data in this study provides the result of 91.29% accuracy. From this experimental result, system prototyping is developed for the visualization that can help PT. Multindo Auto Finance Semarang to predict the status of new credit applicants and also control their credit customer from any credit problems.
Item Type: | Article |
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Subjects: | T Technology > Teknik Informatika Universitas Dian Nuswantoro > Fakultas Ilmu Komputer > Teknik Informatika |
Divisions: | Fakultas Ilmu Komputer |
Depositing User: | Psi Udinus |
Date Deposited: | 22 Mar 2016 15:15 |
Last Modified: | 22 Mar 2016 15:15 |
URI: | http://eprints.dinus.ac.id/id/eprint/18263 |
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