PENERAPAN DATA MINING DENGAN METODE DECISION TREE UNTUK PREDIKSI KELAYAKAN PEMBERIAN KREDIT (STUDI KASUS : BANK TABUNGAN NEGARA KC PALEMBANG)

ISWANDA, VIYANKA WIDA R and Ermatita, Ermatita (2018) PENERAPAN DATA MINING DENGAN METODE DECISION TREE UNTUK PREDIKSI KELAYAKAN PEMBERIAN KREDIT (STUDI KASUS : BANK TABUNGAN NEGARA KC PALEMBANG). Undergraduate thesis, Sriwijaya University.

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Abstract

Data mining is the process of transforming huge quantity of data into knowledege. The research of this thesis aims to predict credit risk when credit application has been field and the data will be managed with decision tree methods using the algorithm C4.5 because it has a high degree of accuracy in determining the decision. In this research discusses about the performance of the decision tree algorithm C 4.5 to predict the feasibility of granting home ownership credit. From this research, note that the highest value of precision, recall, and accuracy is reached by the algorithm C4.5 with the partition data 90:10, the result is 92.31 %, 85.71%, and 94%. The end result of this research proves that the data partition has the most accurate value that is on the algorthm C4.5 with the partition data 90:10.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Decision Tree, C4.5, Classification Method, The Feasibility of Home Ownership Credit.
Subjects:	T Technology > T Technology (General) > T58.6-58.62 Management information systems
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Mrs Sri Astuti
Date Deposited:	09 Sep 2019 07:46
Last Modified:	09 Sep 2019 07:46
URI:	http://repository.unsri.ac.id/id/eprint/6755

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