STRUKTUR CORPORATE GOVERNANCE DAN KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN: PERBANDINGAN MODEL LOGISTIK DAN NEURAL NETWORK

STRUKTUR CORPORATE GOVERNANCE DAN KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN: PERBANDINGAN MODEL LOGISTIK DAN NEURAL NETWORK

The main objective of this study was to examine the impact of corporate gover-nance structure and the performance of the firms to timelines in Indonesian Stock Exchangeusing two alternative methods, Logistic Regression and Neural Network. This study com-bined corporate governance structure and timel...

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Main Author: Tri Gunarsih
Format: Article
Language:English
Published: Universitas Merdeka Malang 2017-03-01
Series:Jurnal Keuangan dan Perbankan
Subjects:
corporate governance structure, timelines, financial performance, neural network
Online Access:http://jurnal.unmer.ac.id/index.php/jkdp/article/view/965
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spelling doaj-c49623c67a454faeb28bd221c630ba002020-11-24T23:03:22ZengUniversitas Merdeka MalangJurnal Keuangan dan Perbankan1410-80892443-26872017-03-01142177190678STRUKTUR CORPORATE GOVERNANCE DAN KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN: PERBANDINGAN MODEL LOGISTIK DAN NEURAL NETWORKTri Gunarsih0Jurusan Manajemen Fakultas Ekonomi UTYJl. Glagahsari No.63 YogyakartaThe main objective of this study was to examine the impact of corporate gover-nance structure and the performance of the firms to timelines in Indonesian Stock Exchangeusing two alternative methods, Logistic Regression and Neural Network. This study com-bined corporate governance structure and timelines study. Samples in this study were publiccompanies listed in Indonesian Stock Exchange. The dependent variable was timelines proxiedby dummy variable, 1 if companies published financial reporting before 120 days after De-cember 31 and 0 otherwise. Governance structures are proxied number of the Board ofDirectors and number of the Board of Commissioners. The results of the study showed thatthe prediction accuracy of logistic regression is 61.2% while Neural Network is more than96%. This suggested that Neural Network predicts more accurately than logistic regression.http://jurnal.unmer.ac.id/index.php/jkdp/article/view/965corporate governance structure, timelines, financial performance, neural network
collection DOAJ
language English
format Article
sources DOAJ
author Tri Gunarsih
spellingShingle Tri Gunarsih
STRUKTUR CORPORATE GOVERNANCE DAN KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN: PERBANDINGAN MODEL LOGISTIK DAN NEURAL NETWORK
Jurnal Keuangan dan Perbankan
corporate governance structure, timelines, financial performance, neural network
author_facet Tri Gunarsih
author_sort Tri Gunarsih
title STRUKTUR CORPORATE GOVERNANCE DAN KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN: PERBANDINGAN MODEL LOGISTIK DAN NEURAL NETWORK
title_short STRUKTUR CORPORATE GOVERNANCE DAN KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN: PERBANDINGAN MODEL LOGISTIK DAN NEURAL NETWORK
title_full STRUKTUR CORPORATE GOVERNANCE DAN KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN: PERBANDINGAN MODEL LOGISTIK DAN NEURAL NETWORK
title_fullStr STRUKTUR CORPORATE GOVERNANCE DAN KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN: PERBANDINGAN MODEL LOGISTIK DAN NEURAL NETWORK
title_full_unstemmed STRUKTUR CORPORATE GOVERNANCE DAN KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN: PERBANDINGAN MODEL LOGISTIK DAN NEURAL NETWORK
title_sort struktur corporate governance dan ketepatan waktu penyampaian laporan keuangan: perbandingan model logistik dan neural network
publisher Universitas Merdeka Malang
series Jurnal Keuangan dan Perbankan
issn 1410-8089
2443-2687
publishDate 2017-03-01
description The main objective of this study was to examine the impact of corporate gover-nance structure and the performance of the firms to timelines in Indonesian Stock Exchangeusing two alternative methods, Logistic Regression and Neural Network. This study com-bined corporate governance structure and timelines study. Samples in this study were publiccompanies listed in Indonesian Stock Exchange. The dependent variable was timelines proxiedby dummy variable, 1 if companies published financial reporting before 120 days after De-cember 31 and 0 otherwise. Governance structures are proxied number of the Board ofDirectors and number of the Board of Commissioners. The results of the study showed thatthe prediction accuracy of logistic regression is 61.2% while Neural Network is more than96%. This suggested that Neural Network predicts more accurately than logistic regression.
topic corporate governance structure, timelines, financial performance, neural network
url http://jurnal.unmer.ac.id/index.php/jkdp/article/view/965
work_keys_str_mv AT trigunarsih strukturcorporategovernancedanketepatanwaktupenyampaianlaporankeuanganperbandinganmodellogistikdanneuralnetwork
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