PENERAPAN DATA MINING DENGAN ALGORITMA CLASSIFICATION BASED ON ASSOCIATION (CBA) UNTUK KLASIFIKASI RISIKO PEMBERIAN KREDIT (STUDI KASUS PT. PUPUK SRIWIJAYA PALEMBANG)
Daftar Isi:
- In order to prevent loan defaults on micro enterprises which caused by internal factors, it needs a system that able to predict credit risk of loan applicants more accurately and objectively. One of the ways to do so is by utilizing data mining technique using Classification Based on Association (CBA) algorithm that able to build a model to predict credit risks by classifying loan applicants data into “good” or “delinquent” class. The data mining process was done by using Cross-Industry Standard Process for Data Mining (CRISP-DM) method. The accuracy level of the resulting model using the CBA algorithm with R language then was tested. A model with the highest accuracy level was then implemented into a web based application system.