Penerapan Metode Random forest untuk Analisis Risiko pada dataset Peer to peer lending
Renata Erick
Primary Author
mixed material
bibliography
Bandung
Maranatha University Press
2020
Indonesia
hlm : 462-474
JUTISI : Jurnal Teknik Informatika dan Sistem Informasi
Abstract
Abstract — Peer to peer lending (P2PL) is one of financial technology (fintech) that develops very fast in society. On the other side, P2PL project has many risks. The risk of P2PL project can be analyzed using classification. There are two conditions of a loan, namely a good loan and a bad loan. This study uses two methods to analyze a P2PL dataset, that are Random Forest method and Logistic Regression method. Data is taken from P2PL loan dataset provided by Data World, which contains 887.379 entries with 74 features. The result of experiments is a model that can be used to predict and classify a P2PL loan as a good or bad one.
Informatika
Sistem Informasi
JUTISI
24432210
Perpustakaan Teknik UPI YAI
JUTISI V6N3 Desember 2020
JUTISI3-005
Perpustakaan FT UPI YAI
JUTISI V6N3 Desember 2020
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2023-02-27 14:34:47
2023-02-27 14:34:47
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