Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Owner : Riset dan Jurnal Akuntansi
Rahma Sari Harahap
Program Pascasarjana Magister Manajemen Universitas Sumatera Utara
Economics, Econometrics & Finance

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Analisis penggunaan metode Altman Z-Score dan Springate untuk mengetahui potensi terjadinya Financial Distress pada perusahaan manufaktur sektor industri dasar dan kimia Sub Sektor semen yang terdaftar di Bursa Efek Indonesia 2000-2020 Rahma Sari Harahap; Iskandar Muda; Rina br Bukit
Owner : Riset dan Jurnal Akuntansi Vol. 6 No. 4 (2022): Artikel Volume 6 Issue 4 Periode Oktober 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/owner.v6i4.1576

Abstract

The objective of the research is to find out the result of predicting bankruptcy, using Altman Z-Score and Springate methods in the manufacturing companies of basic industrial and chemistry sectors, cement sub-sector listed on BEI (Indonesia Stock Exchange) in the period of 2000-2020 and to determine the most accurate predicting method of bankruptcy to be applied in the manufacturing companies in basic industrial and chemistry sectors, cement sub-sector. The research employs descriptive quantitative method. The samples are taken by using purposive sampling method with three manufacture companies in basic industrial and chemistry sectors and cement sub-sector. The data are analyzed by using the accuracy and error levels in each predicting method of bankruptcy, and each method shows different prediction. The result of financial distress prediction, using Altman Z-Score shows that there are 19 financial distress predictions, 26 non-financial distress predictions, and 18 gray area predictions. The result of financial distress prediction, using Springate method shows that there are 22 financial distress predictions and 41 non-financial distress predictions, the result of the calculation in accuracy and error levels, using Springate method, shows that Springate method is the most accurate with the accuracy level of 65.08% and the error level of 34.92% .
Co-Authors Iskandar Muda Rina Br. Bukit