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Data Mining Menggunakan Algoritma K-Nearest Neighbor Dalam Menentukan Kredit Macet Barang Elektronik
Author(s) -
Silvilestari Silvilestari
Publication year - 2021
Publication title -
jurnal media informatika budidarma/jurnal media informatika budidarma
Language(s) - English
Resource type - Journals
eISSN - 2614-5278
pISSN - 2548-8368
DOI - 10.30865/mib.v5i3.3100
Subject(s) - payment , business , order (exchange) , process (computing) , closeness , obstacle , commerce , computer science , finance , mathematical analysis , mathematics , political science , law , operating system
Business is an activity that is routinely carried out by many people, one of the promising businesses is a business that provides the needs of electronic goods to meet the needs of daily life, high demand causes business people to be more careful and selective in seeing the pattern of customers who want perform transactions in order to avoid business risks appropriately. Business people use a credit system to increase sales for a long time, but the obstacle that often occurs is that many customers who use credit services often delay payments to make the company's finances unstable so someone needs to predict someone who has the potential to do bad credit for electronic goods. using a system that helps business owners to make it easier to process data and predict patterns of bad credit for electronic goods that have been formed from previous data using the KNN algorithm approach, so that the results show the closeness of the value to the data of old customers, both those who pay properly and those who make payments in default and it can be obtained that the processing process accelerates data processing with precise results in the problem solving process

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