数据挖掘算法在摩托车分期付款收款人中的应用

ComTech Pub Date : 2015-12-01 DOI:10.21512/COMTECH.V6I4.2192
Harry Dhika, Fitriana Destiawati
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引用次数: 2

摘要

这项研究是在提供信贷购买摩托车相关金融服务的子公司进行的。在申请时,消费者输入他们的个人数据。根据个人资料,我们会得知个人信贷资料是否被批准或拒绝。从获得的224个消费者数据中可以得知,申请被批准的消费者占87%,约217个消费者,申请被拒绝的消费者占16%,多达6个消费者。通过crisp - DM应用该算法处理摩托车信贷融资是数据挖掘处理的行业标准。决策中使用的算法为C4.5算法。在之前得到的结果中,准确度水平是用混淆矩阵和接收者工作特征(ROC)来衡量的。混淆矩阵的求值是求正确率值、精密度值、召回率值。而接受者工作特征(ROC)用于查找数据表和比较曲线下面积(AUC)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Data Mining Algorithm to Recipient of Motorcycle Installment
The study was conducted in the subsidiaries that provide services of finance related to the purchase of a motorcycle on credit. At the time of applying, consumers enter their personal data. Based on the personal data, it will be known whether the consumer credit data is approved or rejected. From 224 consumer data obtained, it is known that the number of consumers whose applications are approved is 87% or about 217 consumers and consumers whose application is rejected is 16% or as much as 6 consumers. Acceptance of motorcycle financing on credit by using the method of applying the algorithm through CRIS-P DM is the industry standard in the processing of data mining. The algorithm used in the decision making is the algorithm C4.5. The results obtained previously, the level of accuracy is measured with the Confusion Matrix and Receiver Operating characteristic (ROC). Evaluation of the Confusion Matrix is intended to seek the value of accuracy, precision value, and the value of recall data. While the Receiver Operating Characteristic (ROC) is used to find data tables and comparison Area Under Curve (AUC).
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来源期刊
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6
审稿时长
16 weeks
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