{"title":"借方信贷客户数据分类使用从k -手段对大型中央融资进行分类","authors":"Rike Limia Budiarti, Gina Cendana","doi":"10.53564/akademika.v14i2.866","DOIUrl":null,"url":null,"abstract":"Mega Central Finance (MCF) Group is a company under CT.Corpora. The Mega Central Finance (MCF) Group company functions as a company engaged in financing and credit, located in Muara Bulian. The purpose of this study using the \"K-means\" data mining method is to obtain data reports on customers who are entitled to receive loans from the Mega Central Finance (MCF) Group. Clustering includes inputting data from customers who apply for loans, then entering the registration process to enter the customer's name, the calculation process using RapidMiner. It takes several variables used in clustering, namely the variable \"Amount of Loans, Term, Income, Number of Pickup Vehicles\". The results of clustering obtained three clusters, namely cluster 1 there are 7 active customer data which has a very small number of clusters. Cluster 2 contains 93 passive customer data which has a cluster number with the highest number of customer data from cluster 1 and cluster 3. Cluster 3 contains 50 repeat order customer data which has a moderate number of clusters. Finally, the results from the three clusters above are obtained.","PeriodicalId":17695,"journal":{"name":"Jurnal Akademika Kimia","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"KLASIFIKASI DATA NASABAH KREDIT PINJAMAN MENGGUNAKAN DATA MINING DENGAN METODE K-MEANS PADA MEGA CENTRAL FINANCE\",\"authors\":\"Rike Limia Budiarti, Gina Cendana\",\"doi\":\"10.53564/akademika.v14i2.866\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mega Central Finance (MCF) Group is a company under CT.Corpora. The Mega Central Finance (MCF) Group company functions as a company engaged in financing and credit, located in Muara Bulian. The purpose of this study using the \\\"K-means\\\" data mining method is to obtain data reports on customers who are entitled to receive loans from the Mega Central Finance (MCF) Group. Clustering includes inputting data from customers who apply for loans, then entering the registration process to enter the customer's name, the calculation process using RapidMiner. It takes several variables used in clustering, namely the variable \\\"Amount of Loans, Term, Income, Number of Pickup Vehicles\\\". The results of clustering obtained three clusters, namely cluster 1 there are 7 active customer data which has a very small number of clusters. Cluster 2 contains 93 passive customer data which has a cluster number with the highest number of customer data from cluster 1 and cluster 3. Cluster 3 contains 50 repeat order customer data which has a moderate number of clusters. Finally, the results from the three clusters above are obtained.\",\"PeriodicalId\":17695,\"journal\":{\"name\":\"Jurnal Akademika Kimia\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Akademika Kimia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.53564/akademika.v14i2.866\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Akademika Kimia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53564/akademika.v14i2.866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
兆丰金融(MCF)集团是一家隶属于CT.Corpora的公司。Mega Central Finance (MCF) Group公司是一家从事融资和信贷的公司,位于Muara Bulian。本研究使用“K-means”数据挖掘方法的目的是获得有权从Mega Central Finance (MCF) Group获得贷款的客户的数据报告。聚类包括输入申请贷款的客户的数据,然后进入注册过程输入客户的姓名,计算过程使用RapidMiner。它取聚类中使用的几个变量,即变量“贷款金额、期限、收入、皮卡车数量”。聚类的结果得到三个聚类,即聚类1中有7个活跃客户数据,其中聚类数量非常少。集群2包含93个被动客户数据,其集群号中来自集群1和集群3的客户数据数量最多。集群3包含50个重复订单客户数据,集群数量适中。最后,从以上三个聚类中得到结果。
KLASIFIKASI DATA NASABAH KREDIT PINJAMAN MENGGUNAKAN DATA MINING DENGAN METODE K-MEANS PADA MEGA CENTRAL FINANCE
Mega Central Finance (MCF) Group is a company under CT.Corpora. The Mega Central Finance (MCF) Group company functions as a company engaged in financing and credit, located in Muara Bulian. The purpose of this study using the "K-means" data mining method is to obtain data reports on customers who are entitled to receive loans from the Mega Central Finance (MCF) Group. Clustering includes inputting data from customers who apply for loans, then entering the registration process to enter the customer's name, the calculation process using RapidMiner. It takes several variables used in clustering, namely the variable "Amount of Loans, Term, Income, Number of Pickup Vehicles". The results of clustering obtained three clusters, namely cluster 1 there are 7 active customer data which has a very small number of clusters. Cluster 2 contains 93 passive customer data which has a cluster number with the highest number of customer data from cluster 1 and cluster 3. Cluster 3 contains 50 repeat order customer data which has a moderate number of clusters. Finally, the results from the three clusters above are obtained.