Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal Universal Business and Management Review
Saiful Bahri
Universitas Wahid Hasyim, Indonesia
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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The Impact of Russian-Ukrainian War towards Abnormal Stock Return And Trading Volume Activity Andre Putra Pratama; Saiful Bahri
Universal Business and Management Review Vol 1 No 1 (2024): June 2024 : Universal Business and Management Review
Publisher : Faculty of Economics and Business, Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31942/av2cj764

Abstract

This study aims to determine the impact of the events of the Russian and Ukrainian wars by looking at market reactions using 2 measurement variables, namely Abnormal Return and Trading Volume Activity. This study uses a quantitative approach with secondary data taken from the IDX and Yahoo Finance websites. The population in this study were energy sector companies that were listed on the Indonesian Stock Exchange before the events of the Russian and Ukrainian wars on February 24, 2022. Meanwhile, the sample used in this study were energy sector companies that met predetermined criteria totaling 34 companies. Data collection techniques in this study used literature and documentation. Meanwhile, data analysis techniques used paired sample t-test and Wilxocon signed rank t-test. The results of this study indicate that (1) There are significant differences in the Average Abnormal Return (AAR) of energy sector companies listed on the Indonesia Stock Exchange in the period before and after the Russian and Ukrainian wars. (2) There are significant differences in the Average Trading Volume Activity (ATVA) in energy sector companies listed on the Indonesia Stock Exchange in the period before and after the Russian and Ukrainian wars.
The Role of Compensatory Justice and Physical Work Environment in Influencing Employee Job Satisfaction Shinta Devi Sukowati; Saiful Bahri
Universal Business and Management Review Vol 1 No 2 (2024): December 2024: Universal Business and Management Review
Publisher : Faculty of Economics and Business, Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31942/hdj18y15

Abstract

This study aims to determine the effect of compensation justice and physical work environment on the job satisfaction of employees of the Agriculture and Plantation Service of Central Java Province, Indonesia. This study uses a quantitative research approach. The population in this study amounted to 594 people and the sample studied was 86 respondents using a simple random sampling technique. The analysis tool uses statistical software with SPSS version 22. Data analysis uses multiple linear regression analysis. Partially, the compensation fairness variable has a significant effect on employee job satisfaction, as well as the physical work environment has a significant effect on employee job satisfaction. This shows that compensation fairness and physical work environment provide a positive contribution to employee job satisfaction. Further findings show that compensation fairness and physical work environment provide a high contribution to job satisfaction.
Analysis of Insurance Company Bankruptcy Predictions Listed on the Indonesian Stock Exchange from 2020 To 2023 Eva Umiyatul Hidayah; Saiful Bahri
Universal Business and Management Review Vol 2 No 2 (2025): December 2025: Universal Business and Management Review
Publisher : Faculty of Economics and Business, Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31942/6crbte95

Abstract

This study examines the accuracy of bankruptcy prediction models applied to insurance companies listed on the Indonesia Stock Exchange during the 2020–2023 period. The research aims to compare the predictive performance of the Altman Z-Score, Springate, and Zmijewski models in identifying potential financial distress. A quantitative approach is employed using secondary data derived from annual financial statements of insurance firms. The sample consists of eight companies selected through purposive sampling. Data analysis involves normality testing and non-parametric statistical analysis using the Kruskal–Wallis test, supported by accuracy level evaluation through Type I error analysis. The findings indicate a statistically significant difference in bankruptcy prediction results among the three models. The Zmijewski model demonstrates the highest predictive accuracy, followed by the Altman Z-Score and the Springate model. These results suggest that the Zmijewski model is more reliable for predicting bankruptcy risk in insurance companies during periods of economic uncertainty. This study contributes to financial distress literature by providing empirical evidence on the comparative effectiveness of bankruptcy prediction models and offers practical implications for investors, managers, and regulators in assessing corporate financial health.
Co-Authors Andre Putra Pratama Eva Umiyatul Hidayah Shinta Devi Sukowati