Implementasi Metode Artificial Neural Network Untuk Analisis Resiko Kredit Pada Sistem Peer To Peer Lending


Authors

  • Pieter Octaviandy STMIK Time, Medan, Indonesia
  • Octara Pribadi STMIK Time, Medan, Indonesia

DOI:

https://doi.org/10.47065/bulletincsr.v3i1.208

Keywords:

Peer To Peer Lending; Lender; Borrower; Feature Selection; Artificial Neural Network

Abstract

Peer to Peer (P2P) lending is an example of implementing Financial Technology (Fintech) in the form of information technology-based lending and borrowing services. This service offers flexibility where lenders and borrowers can allocate and get capital or funds almost from and to anyone, in any amount of value, effectively and transparently, and with competitive returns. The problem with the Peer to Peer lending application is how to provide recommendations to users, especially to lenders regarding the risk of borrowing from borrowers. To solve this problem, the Artificial Neural Network method is applied. The result of this research is a web- based Peer to Peer Lending system application. The software is able to provide information on the results of recommendations to lenders regarding the type of loan. From the test results, information is obtained that the Artificial Neural Network method is suitable to be applied in a peer-to-peer lending system, with a validity level of 80%. In addition, the software is also able to provide highly reliable recommendation information to lenders regarding the type of loan, with a sensitivity level of 100% loan risk prediction, 60% positive predictive value and 100% negative predictive value.

Downloads

Download data is not yet available.

References

S. Yuharnita, “Kebijakan Restrukturisasi Pinjaman Pada Peer To Peer Lending,” Media Iuris, vol. 4, no. 1, pp. 91-102, 2021.

D. Wijayanti dan Pujiyono, “LEGALITAS SISTEM PEER TO PEER LENDING FINANCIAL TECHNOLOGY DI INDONESIA,” Privat Law, vol. 9, no. 1, pp. 43-51, 2021.

A. P. Harp, R. Fitri dan Y. Mahanani, “Peer-to-Peer Lending Syariah dan Dampaknya terhadap Kinerja serta Kesejahteraan Pelaku Usaha Mikro dan Kecil (UMK) pada Masa Pandemi Covid-19,” AL- MUZARA’AH, vol. 9, no. 1, pp. 109-127, 2021.

N. Widyaningsih, “Analisi Mitigasi Resiko Financial Technology Peer to Peer Lending Dalam Penyaluran Kredit Terhadap UMKM di Indonesia (Studi Kasus Pada PT. Amartha Mikro Fintek),” UNIVERSITAS BRAWIJAYA, pp. 1-14, 2018.

A. H. Wijaya, “ARTIFICIAL NEURAL NETWORK UNTUK MEMPREDIKSI BEBAN LISTRIK DENGAN MENGGUNAKAN METODE BACKPROPAGATION (Studi Kasus PT. PLN Regional Sumatera Barat),” Jurnal CoreIT, vol. 5, no. 2, pp. 61-70, 2019.

M. A. Razak dan E. Riksakomara, “Peramalan Jumlah Produksi Ikan dengan Menggunakan Backpropagation Neural Network (Studi Kasus: UPTD Pelabuhan Perikanan Banjarmasin,” JURNAL TEKNIK ITS, vol. 6, no. 1, pp. 142-148, 2017.

A. Y. Prathama, A. Aminullah dan A. Saputra, “PENDEKATAN ANN (ARTIFICIAL NEURAL NETWORK) UNTUK PENENTUAN PROSENTASE BOBOT PEKERJAAN DAN ESTIMASI NILAI PEKERJAAN STRUKTUR PADA RUMAH SAKIT PRATAMA,” Jurnal TeknoSains, vol. 7, no. 1, pp. 1-82, 2017.

H. Jayadianti, T. A. Cahyadi, N. A. Amri dan M. F. Pitayandanu, “METODE KOMPARASI ARTIFICIAL NEURAL NETWORK PADA PREDIKSI CURAH HUJAN - LITERATURE REVIEW,” Jurnal Tekno Insentif, vol. 14, no. 2, pp. 48-53, 2020.

A. S. Saputra, “PERLINDUNGAN TERHADAP PEMBERI PINJAMAN SELAKU KONSUMEN DAN TANGGUNG JAWAB PENYELENGGARA PEER TO PEER LENDING DALAM KEGIATAN PEER TO PEER LENDING DI INDONESIA,” VeJ, pp. 238-261, 2019.

I. G. A. A. P. Dewi, “INTENSI MASYARAKAT BERINVESTASI PADA PEER TO PEER LENDING:ANALISIS THEORY OF PLANNED BEHAVIOR,” Jurnal Ilmiah Akuntansi & Bisnis, pp. 118-132, 2018.

E. Saraswati, Y. Umaidah dan A. Voutama, “Penerapan Algoritma Artificial Neural Network untuk Klasifikasi Opini Publik Terhadap Covid-19,” Generation Journal, vol. 5, no. 2, pp. 109-118, 2021.


Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Implementasi Metode Artificial Neural Network Untuk Analisis Resiko Kredit Pada Sistem Peer To Peer Lending

Dimensions Badge

ARTICLE HISTORY

Published: 2022-12-31

Abstract View: 302 times
PDF Download: 279 times

How to Cite

Octaviandy, P., & Octara Pribadi. (2022). Implementasi Metode Artificial Neural Network Untuk Analisis Resiko Kredit Pada Sistem Peer To Peer Lending. Bulletin of Computer Science Research, 3(1), 116-122. https://doi.org/10.47065/bulletincsr.v3i1.208

Issue

Vol. 3 No. 1 (2022): Desember 2022

Page: 116-122

Section

Articles

Copyright (c) 2022 Pieter Octaviandy, Octara Pribadi

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).