Open AccessAnalysis of Perceptron Quantum Artificial Neural Networks to Classify the Feasibility of Prospective Debtors
Author(s) -
Lise Pujiastuti,
Mochamad Wahyudi,
. Solikhun
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1641/1/012091
Subject(s) - multilayer perceptron , artificial neural network , perceptron , quantum , prospective cohort study , computer science , artificial intelligence , machine learning , pattern recognition (psychology) , finance , business , medicine , physics , quantum mechanics
Bank is a business entity whose activities are collecting funds from the public in the form of deposits and channeling them to the public in the form of loans or other forms to improve the lives of many people. This study aims to classify the feasibility data of prospective borrowers with the perceptron algorithm using quantum computing to facilitate the bank in determining the prospective debtor. The results of this study are an analysis of the feasibility of prospective borrowers using the perceptron algorithm with quantum computing.