Kemampuan Good Corporate Governance (GCG) dan Kinerja Keuangan untuk Memprediksi Financial Distress pada Perusahaan Manufaktur di Bursa Efek Indonesia

Safitri, Khusnul Intan (2021) Kemampuan Good Corporate Governance (GCG) dan Kinerja Keuangan untuk Memprediksi Financial Distress pada Perusahaan Manufaktur di Bursa Efek Indonesia. Undergraduate thesis, STIE Perbanas Surabaya.

[img]
Preview
Text
ARTIKEL ILMIAH.pdf

Download (486kB) | Preview
[img] Text
COVER.pdf
Restricted to Registered users only

Download (434kB)
[img]
Preview
Text
BAB I.pdf

Download (273kB) | Preview
[img]
Preview
Text
BAB II.pdf

Download (390kB) | Preview
[img] Text
BAB III.pdf
Restricted to Registered users only

Download (322kB)
[img] Text
BAB IV.pdf
Restricted to Registered users only

Download (355kB)
[img]
Preview
Text
BAB V.pdf

Download (173kB) | Preview
[img] Text
LAMPIRAN.pdf
Restricted to Registered users only

Download (977kB)

Abstract

Identification of financial distress in a company is very important because it can serve as an early warning system before bankruptcy occurs. This study aims to analyze whether good corporate governance (GCG) and financial performance can predict financial distress in manufacturing companies listed on the Indonesia Stock Exchange for the 2015-2019 period. The analytical method used is logistic regression. The sample consists of 19 observed data from companies with negative earnings for two consecutive years and 19 data observed from companies with positive earnings for two consecutive years. The results showed that the profitability ratio (return on assets) had a significant negative effect in predicting corporate financial distress. The liquidity ratio (current ratio), leverage (debt to equity ratio), and GCG (board size) do not have a significant effect in predicting the company's financial distress. Meanwhile, GCG (institutional ownership) has no significant effect even though it has a negative sign in predicting corporate financial distress. Keywords: Financial Distress, Good Corporate Governance (GCG), Financial Ratio, Logistic Regression

Item Type: Thesis (Undergraduate)
Subjects: 600 - TECHNOLOGY > 650 - 659 MANAGEMENT & PUBLIC RELATIONS > 658 - GENERAL MANAGEMENT > 658.15 - FINANCIAL MANAGEMENT
Divisions: Bachelor of Management
Depositing User: KHUSNUL INTAN SAFITRI
Date Deposited: 22 Apr 2021 08:23
Last Modified: 22 Apr 2021 08:23
URI: http://eprints.perbanas.ac.id/id/eprint/7750

Actions (login required)

View Item View Item