ANALISIS CREDIT SCORING KELAYAKAN DEBITUR MENGGUNAKAN METODE ENSEMBLE BACKPROPAGATION NEURAL NETWORK (BPNN) DAN TECHNIQUE FOR OTHERS PEFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS)

SAPUTRI, SUSAN DWI and Zuhairi, Ermatita and Sukemi, Sukemi (2019) ANALISIS CREDIT SCORING KELAYAKAN DEBITUR MENGGUNAKAN METODE ENSEMBLE BACKPROPAGATION NEURAL NETWORK (BPNN) DAN TECHNIQUE FOR OTHERS PEFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS). Master thesis, Sriwijaya University.

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Abstract

Credit scoring has been widely used by the finance company to increase cash flow and sales of the company’s products. The advantages of credit scoring are reduced operating costs, bad debt losses, closer monitoring of existing accounts, prioritizing collections, and enabling faster credit decisions making. Therefore, many financial institutions and researchers to developed various models to support credit scoring decisions. Recently, hybrid systems or ensemble method are one of the most promising approaches for complex technical systems analysis. Consequently, in this study using Backpropagation Neural Network (BPNN) and TOPSIS for credit scoring modeling. BPNN were used to classify characteristics of the customers for the segregation of acceptable and unacceptable based on information of a prospective debto, while TOPSIS were used to determine the priority of credit recipients as the final decision. The results showed that the ensemble methods of BPNN and TOPSIS obtained 90% accuracy, 85.7 % precision, and 100% recall with epoch 100 and error rate 0.01. Keywords: Credit Scoring, Backpropagation Neural Network (BPNN), Technique For Others Peference by Similarity to Ideal Solution (TOPSIS).

Item Type: Thesis (Master)
Uncontrolled Keywords: Credit Scoring, Backpropagation Neural Network (BPNN), Technique For Others Peference by Similarity to Ideal Solution (TOPSIS).
Subjects: T Technology > T Technology (General) > T58.6-58.62 Management information systems > T58.6 General works Industrial engineering Information technology. Information systems (General) Management information systems -- Continued
T Technology > T Technology (General) > T58.6-58.62 Management information systems > T58.62 Decision support systems Cf. HD30.213 Industrial management
Divisions: Faculty of Computer Science > 55101-Informatics (S2)
Depositing User: Susan Dwi Saputri
Date Deposited: 14 Jan 2020 06:58
Last Modified: 14 Jan 2020 06:58
URI: http://repository.unsri.ac.id/id/eprint/24033

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