Open AccessArtificial neural network model for banckrupty prediction
Author(s) -
Budi Prasetiyo,
Alamsyah Alamsyah,
Much Aziz Muslim,
Subhan Subhan,
Niswah Baroroh
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 - 10.1088/1742-6596/1567/3/032022
Subject(s) - bankruptcy prediction , bankruptcy , artificial neural network , artificial intelligence , computer science , class (philosophy) , debt , machine learning , business , finance
Bankruptcy is a financial failure in a business where the company fails to generate profits and cannot pay its debts. The impact of bankruptcy is very large for the organization and can be felt by the whole community. Thus, the prediction of a company’s financial failure is absolutely necessary to prevent bankruptcy. Prediction can be done with data mining, one of the methods is to use a network model. This study was to obtain the results of the classification of types of companies that went bankrupt and get the performance of the algorithm used. The results obtained are with an accuracy of class recal 99.30% (trueNB) dan 99.07% (trueB). Sedangkan class precision 99.30% (predNB) dan 99.07% (pred.B). Hasil evaluasi kinerja algoritma Naïve Bayesian Classifier pada penelitian ini menunjukkan tingkat akurasi yang cukup tinggi yaitu 99.20%.