APLIKASI SISTEM PENDUKUNG KEPUTUSAN UNTUK KELAYAKAN PEMBERIAN KREDIT BUMN GRIYA MENGGUNAKAN METODE PROBABILISTIC NEURAL NETWORK

Dedy Feriyanto, . (2014) APLIKASI SISTEM PENDUKUNG KEPUTUSAN UNTUK KELAYAKAN PEMBERIAN KREDIT BUMN GRIYA MENGGUNAKAN METODE PROBABILISTIC NEURAL NETWORK. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

BUMN Griya is a bank product that give a homeowner credit facilities for loaning of home purchase, apartment, etc. On loan giving to his debtor candidate, the bank is firstly selecting based on the criteria. But, in the BUMN Griya current system, there are some variables in the system that do not affect lending decisions, so that during the process of selecting prospective borrowers require more time. So, this research is giving an idea to build an application of decision support system to eligibility of giving a BUMN griya credit by summarize the variables that do not affect the decision making. The purpose is speeding the bank process on doing selection to debtor candidates. The method is using PNN (Probabilistik Neural Network). From 18 tested data reach 100% level of accuracy. Suggestions for further research are expected to be further developed system can not only determine whether viable borrowers get credit but also includes tenor of the payment and the policies to be taken into the Bank in determining the granting of credit on borrowers. Using other methods that can be applied to subsequent research.

Item Type:	Thesis (Skripsi)
Additional Information:	[No Panggil : 1010511138] [Pembimbing : Ki Pramono} [Penguji 1 : Bambang Tri Wahyono] [Penguji 2 : Ati Zaidiah]
Uncontrolled Keywords:	Application of Decision Support Systems, Giving Loan, Probabilistic Neural Network, PNN, Homeowner Credit
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User:	Deny Wahyudin
Date Deposited:	16 Jan 2023 06:50
Last Modified:	16 Jan 2023 06:50
URI:	http://repository.upnvj.ac.id/id/eprint/22067

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