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All Journal In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Raynald Damara Eriyanto
Fakultas Ekonomi dan Bisnis, Universitas Telkom
Arts Computer Science & IT Economics, Econometrics & Finance Other

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Model Kelayakan Kredit Pada P2P Lending Menggunakan Data Sosial Media Raynald Damara Eriyanto; Alvin Ramaquita; Andry Alamsyah
In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Vol 19 No 2 (2020): In Search
Publisher : LPPM UNIBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/insearch.v19i2.330

Abstract

Financial institutions tend to prefer to have borrowers with a clear source of credit history. Unlike P2P Lending which does not have complete data, P2P Lending uses alternative or substitute data to create a credit scoring model. Social media as one of the alternative data options cannot directly translate content related credit problems. Therefore, it is necessary to have an approach and understanding of social media data. By using data user demographic attributes or social media demographic features, this study aims to create a credit scoring model using substitute data in the form of social media data for P2P Lending. This study uses a data mining process that utilizes a decision tree algorithm and random forest. The results showed that the credit scoring model with the random forest algorithm produced the highest accuracy of 81.25% and was chosen to be the best model. From these results, P2P Lending can have the opportunity to open a new segment of consumers who do not have a complete financial or credit history.
Co-Authors Alvin Ramaquita Andry Alamsyah