Open AccessNet income prediction of several leading bank in Indonesia using neural approach
Author(s) -
Rofiqoh,
Achmad Fanany Onnilita Gaffar,
Djoko Setyadi,
Syarifah Hudayah
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.2.12743
Subject(s) - net income , backpropagation , artificial neural network , net profit , profit (economics) , net (polyhedron) , time series , investment (military) , financial market , net interest income , economics , econometrics , finance , computer science , business , artificial intelligence , machine learning , mathematics , microeconomics , interest rate , politics , political science , law , geometry
The IFRS (International Financial Reporting Standards) defines net income as synonymous with profit and loss. Net income can be used as a consideration for investment decision making for investors who will invest their capital into a company. Net income for the next year cannot be ascertained but can be predicted by using several financial ratios that affect the change in net income. This study tries to predict net income next year by using several financial ratios obtained from four leading banks in Indonesia. The time series data modeling by using Artificial Neural Network (ANN) based Auto-Regressive with Exogenous input (ARX) model. In this study only use one net structure to model time series data in order to improve the efficiency of the model. Back-Propagation (BP) doing backpropagation to fix the weight of each layer of ANN such that to achieve appointed target error.