Open AccessAnalisis Kondisi Financial Distress pada Perusahaan Perbankan di Bursa Efek Indonesia
Author(s) -
Anindya Aulia Nisa,
Elok Sri Utami,
Ana Mufidah
Publication year - 2021
Publication title -
jurnal ekonomi akuntansi dan manajemen
Language(s) - English
Resource type - Journals
ISSN - 2459-9816
DOI - 10.19184/jeam.v20i1.17801
Subject(s) - financial distress , nonprobability sampling , logistic regression , pooling , financial ratio , business , return on assets , financial system , finance , statistics , mathematics , computer science , stock exchange , medicine , population , artificial intelligence , environmental health
This study aims to analyze financial ratios in predicting financial distress in banking companies listed on the IDX using the CAR, NPL, BOPO, ROA, ROE, and LDR ratios. The sampling technique is purposive sampling with the criteria of companies that have the potential to experience financial distress, characterized by companies that experience negative net income for at least two consecutive years and those that do not. The method of analysis is logistic regression with data pooling. The results show that NPL can predict the financial distress condition of a banking company, while CAR, BOPO, ROA, ROE, LDR cannot predict the financial distress condition of a banking company.
Keywords: Financial Distress, Financial Ratios, Banking, Logistic Regression