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Journal : MANAJEMEN

Determinasi Kinerja Keuangan di Perusahaan Sektor Property & Real Estate Periode 2019-2023 Anandyaningsih Risnika Putri; Almira Santi Samasta; Vicky Oktavia; Suhita Whini Setyahuni
MANAJEMEN Vol. 5 No. 1 (2025): MEI : MANAJEMEN (Jurnal Ilmiah Manajemen dan Kewirausahaan)
Publisher : LPPM Politeknik Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/manajemen.v5i1.911

Abstract

This study's goal is to ascertain the connection between liquidity ratio (CR), asset management (TATO), capital structure (DAR) and firm size on financial performance, The property & real estate firms that were listed between 2019 and 2023 on the Indonesia Stock Exchange (IDX). The study's sample, which was 52 companies in a period of (5) periods with a total of 260 data. The multiple regression analysis is used in this study method with the type of panel data with the Random Effect Model (REM) method. According to the study's findings that asset management has a favorably and significantly effect on financial performance, capital structure has a negatively and significantly effect on financial performance, but liquidity ratio and firm size have no effect on financial performance.
Analisis Financial Distress: Altman, Grover, Dan Springate Pada Perusahaan Tekstil dan Garmen di Bei Periode 2019-2023 Rahma Fadila Rahayu; Vicky Oktavia; Linda Ayu Oktoriza; Maria Safitri
MANAJEMEN Vol. 5 No. 1 (2025): MEI : MANAJEMEN (Jurnal Ilmiah Manajemen dan Kewirausahaan)
Publisher : LPPM Politeknik Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/manajemen.v5i1.918

Abstract

This study examines the differences in bankruptcy prediction results using three financial distress models, namely Altman Z-Score, Grover, and Springate. The object of research is textile and garment companies listed on the Indonesia Stock Exchange during the 2019-2023 period. A total of eight companies were selected as samples through purposive sampling technique. The data used is secondary data in the form of financial statements. Data processing was carried out by calculating each model using Microsoft Excel, while statistical testing was carried out through the Shapiro-Wilk and Kruskal-Wallis tests with the help of SPSS version 26 software. The analysis results show that there are significant differences between the three models in predicting potential financial difficulties. The Grover model shows the highest accuracy rate of 100%, followed by the Altman model at 87.50%, and the Springate model at 37.50%.