Research on national banking using the Altman’s Z-Score analysis technique has been relatively extensive, but studies focusing specifically on banks indexed to SRI-KEHATI remain limited. The SRI-KEHATI Index is known as a benchmark for companies with strong sustainability, social responsibility, and good governance practices. This study aims to analyze the health trends of banks listed in the SRI-KEHATI Index during the 2015–2024 period by applying the second modified Altman’s Z-Score model (1993), which is widely recognized as a reliable indicator for assessing a company’s financial stability and risk of bankruptcy. The findings indicate that the overall Altman’s Z-Score trend of major banks within the SRI-KEHATI Index shows stability and a consistently healthy financial condition throughout 2015–2023. However, in 2024 there is a notable decline that requires further examination to determine whether it is caused by market fluctuations, structural challenges, or accounting adjustments. Despite this decrease, the overall financial health of the banks remains categorized as very good according to Altman’s model. The average Z-Score for all four banks analyzed is 6.457, which is well above the threshold of 2.6, indicating no significant bankruptcy risk. When evaluated individually, BMRI stands out as the healthiest with a Z-Score of 13.879, followed by BBNI with 5.971, BBRI with 3.175, and BBCA with 2.801. These results confirm that all four banks remain in a safe financial zone during the 2015–2024 period. Furthermore, the study’s four hypotheses are proven, reinforcing the argument that SRI-KEHATI indexed banks maintain strong financial resilience even amid post-Covid-19 challenges.

This study explores the key determinants of field engineer efficiency in the field service industry by analyzing the impact of self-efficacy, resource management, and time management on operational performance. Employing a quantitative research approach, data were collected using saturated sampling from 102 field engineers and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The measurement model showed robust psychometric properties, satisfying the thresholds for convergent validity, discriminant validity, and internal consistency reliability. The structural model results indicate that all three independent variables significantly influence field engineer efficiency. Self-efficacy was found to have the strongest effect (? = 0.421, p < 0.001), followed by resource management (? = 0.347, p < 0.001) and time management (? = 0.289, p < 0.001). The model accounts for 68.7% of the variance in field engineer efficiency, reflecting strong explanatory power and predictive accuracy. Among these variables, self-efficacy emerged as the most dominant factor, suggesting that field engineers' belief in their ability to perform tasks is a critical driver of operational success. High self-efficacy enhances motivation, resilience, and effective problem-solving under pressure, making it essential in dynamic and unpredictable field environments. Resource and time management also play crucial roles in supporting engineers' ability to complete tasks efficiently by ensuring optimal allocation of tools, equipment, and time. The findings provide practical implications for field service organizations aiming to improve workforce performance. Investing in training programs that strengthen self-efficacy, combined with systematic improvements in resource and time management practices, can significantly enhance operational outcomes. By prioritizing these factors, organizations can boost engineer efficiency, reduce operational costs, and improve service delivery, ultimately gaining a stronger competitive advantage in the industry.

With an emphasis on work engagement as a mediating variable, this study intends to investigate the effects of career development and work-life balance on job satisfaction among nurses in Kubu Raya, West Kalimantan. Using a quantitative methodology, structured questionnaires were used to gather data from 223 nurses, and SmartPLS software assisted in the analysis of the data using Structural Equation Modeling (SEM). Purposive sampling was used in the study, and one of the selection factors was the length of employment. The results show that work-life balance also has a positive and significant impact on work engagement, and career growth has a positive and large impact on work engagement. Furthermore, work-life balance and career advancement both directly, favorably, and significantly impact job satisfaction. Job satisfaction has been demonstrated to be favorably and significantly influenced by work engagement, which acts as a meaningful mediator. Furthermore, through work engagement, career development and work-life balance both have a positive and statistically significant mediation effect on job satisfaction.