预计破产的公司注册在印尼证券交易所

Melati Eka Putri, Auliffi Ermian Challen
{"title":"预计破产的公司注册在印尼证券交易所","authors":"Melati Eka Putri, Auliffi Ermian Challen","doi":"10.46367/jas.v5i2.425","DOIUrl":null,"url":null,"abstract":"This study aims to examine the potential for bankruptcy of companies with three analytical models, namely Altman Z-Score, Springate S-Score, and Zmijewski X-Score, and assess the level of accuracy of the three models. Each model uses ratio analysis with the elements of assets, debt, capital, and company profits. This study uses a sample of coal mining companies listed on the Indonesia Stock Exchange (IDX) during the 2014-2018 period. The sampling technique in this study used purposive sampling and obtained 24 sample companies. This study uses secondary data, namely the company's financial statements obtained from IDX's official website. This study calculates financial ratios, compares the scores of the three bankruptcy prediction models, and tests the model's accuracy. The results of this study show that of the three models, the Springate S-Score model is the most accurate in predicting bankruptcy, with an accuracy rate of 83.33%, as evidenced by two companies that were delisted from the IDX. This study can be used as a reference and as material for consideration in making investment decisions for companies and investors.","PeriodicalId":352818,"journal":{"name":"JAS (Jurnal Akuntansi Syariah)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediksi Kebangkrutan Pada Perusahaan Yang Terdaftar Di Bursa Efek Indonesia\",\"authors\":\"Melati Eka Putri, Auliffi Ermian Challen\",\"doi\":\"10.46367/jas.v5i2.425\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to examine the potential for bankruptcy of companies with three analytical models, namely Altman Z-Score, Springate S-Score, and Zmijewski X-Score, and assess the level of accuracy of the three models. Each model uses ratio analysis with the elements of assets, debt, capital, and company profits. This study uses a sample of coal mining companies listed on the Indonesia Stock Exchange (IDX) during the 2014-2018 period. The sampling technique in this study used purposive sampling and obtained 24 sample companies. This study uses secondary data, namely the company's financial statements obtained from IDX's official website. This study calculates financial ratios, compares the scores of the three bankruptcy prediction models, and tests the model's accuracy. The results of this study show that of the three models, the Springate S-Score model is the most accurate in predicting bankruptcy, with an accuracy rate of 83.33%, as evidenced by two companies that were delisted from the IDX. This study can be used as a reference and as material for consideration in making investment decisions for companies and investors.\",\"PeriodicalId\":352818,\"journal\":{\"name\":\"JAS (Jurnal Akuntansi Syariah)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JAS (Jurnal Akuntansi Syariah)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46367/jas.v5i2.425\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JAS (Jurnal Akuntansi Syariah)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46367/jas.v5i2.425","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究旨在通过Altman Z-Score、Springate S-Score和Zmijewski X-Score三种分析模型来考察企业破产的可能性,并评估三种模型的准确性。每个模型都使用资产、债务、资本和公司利润等要素的比率分析。本研究使用了2014-2018年期间在印度尼西亚证券交易所(IDX)上市的煤矿公司样本。本研究的抽样方法采用有目的抽样,共获得24家样本公司。本研究使用二手数据,即从IDX官网获得的公司财务报表。本研究计算财务比率,比较三种破产预测模型的得分,并检验模型的准确性。本研究结果表明,在三种模型中,Springate S-Score模型预测破产的准确率最高,准确率为83.33%,两家从IDX退市的公司证明了这一点。本研究可为企业和投资者在进行投资决策时提供参考和参考资料。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediksi Kebangkrutan Pada Perusahaan Yang Terdaftar Di Bursa Efek Indonesia
This study aims to examine the potential for bankruptcy of companies with three analytical models, namely Altman Z-Score, Springate S-Score, and Zmijewski X-Score, and assess the level of accuracy of the three models. Each model uses ratio analysis with the elements of assets, debt, capital, and company profits. This study uses a sample of coal mining companies listed on the Indonesia Stock Exchange (IDX) during the 2014-2018 period. The sampling technique in this study used purposive sampling and obtained 24 sample companies. This study uses secondary data, namely the company's financial statements obtained from IDX's official website. This study calculates financial ratios, compares the scores of the three bankruptcy prediction models, and tests the model's accuracy. The results of this study show that of the three models, the Springate S-Score model is the most accurate in predicting bankruptcy, with an accuracy rate of 83.33%, as evidenced by two companies that were delisted from the IDX. This study can be used as a reference and as material for consideration in making investment decisions for companies and investors.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信