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Education is the main driver of a nation's progress, which is not only related to intellectual intelligence, but also the formation of student character. Unfortunately, currently the world of education is facing serious problems, such as declining interest in learning and increasingly complex external factors in the digital era. This study aims to explore in depth the impact of learning motivation on student academic achievement, identifying obstacles that hinder this achievement. The method used in the current study is a literature study with a qualitative approach. Data were collected through theoretical studies and analysis of various relevant scientific sources, including research journals and textbooks, which were then combined to develop a comprehensive argument. The findings of this study indicate that learning motivation is the main factor that encourages student persistence and consistency in achieving the best learning. Academic success is defined as the result of a complex interaction between internal and external factors, where the existence of a supporting ecosystem such as good learning facilities, a supportive environment, and effective communication between lecturers and students plays a very important role. On the other hand, phenomena such as digital fatigue, low independence, and excessive workload are identified as significant barriers that can reduce academic performance. This analysis concludes that there is synergy in strengthening psychological aspects and creating an adaptable learning environment to maintain the stability of academic achievement amidst global demands.

This study aims to examine the impact of academic burnout on students’ mental health in the context of hybrid learning through a literature review approach. The rapid transformation of learning systems in higher education, particularly the integration of online and offline methods, has increased academic demands and adaptation challenges for students. This condition potentially triggers academic burnout, which is characterized by emotional exhaustion, depersonalization, and decreased academic achievement. This research employs a literature review method by analyzing relevant scientific articles published between 2019-2025 obtained from indexed national journals and open-access sources. The findings indicate that academic burnout is still commonly experienced by students, generally at a moderate level, and has a significant impact on mental health, including increased stress, emotional fatigue, and decreased academic performance. The study also identifies several influencing factors, including internal factors such as self-efficacy and hardiness, as well as external factors such as social support, learning environment, and academic workload. Furthermore, technological developments, particularly Artificial Intelligence, have the potential to be utilized as an early detection and prevention tool for academic burnout. This study implies the importance of developing adaptive learning strategies and psychological interventions to support students’ well-being in hybrid learning environments.

This study aims to investigate the influence of Work Environment, Workload, and Leadership Style on Job Satisfaction among Non -Medical Employees at Daya Medika Clinic in West Jakarta. This study used a Likert-scale questionnaire and involved a sample of 43 employees using a non-probability sampling method and saturated sampling technique. The results of a multiple linear regression analysis using SPSS version 26 indicate that Work Environment has a positive and significant effect on Employee Job Satisfaction, Workload has no significant effect on Employee Job Satisfaction, while Leadership Style has a positive and significant effect on Employee Job Satisfaction. These findings provide insights for Daya Medika Clinic management in improving the quality of the work environment and implementing appropriate leadership styles to enhance employee job satisfaction. These findings have practical implications for improving employee performance and organizational effectiveness, and serve as a reference for further research in the field of human resource management.

This study aims to analyze the effect of work stress and work environment on employee performance with job satisfaction as a mediating variable at PT X. This study uses a quantitative approach with a census method of 198 employees at PT X. Data were collected through an online questionnaire (Google Form) and analyzed using Structural Equation Modeling based on Partial Least Square (SEM-PLS) with the help of SmartPLS 4.0. Based on the results of the analysis that has been done, it was found that work stress has a negative and significant effect on employee performance. Meanwhile, the work environment has a positive and significant effect on employee performance. In addition, work stress has a negative and significant effect on job satisfaction. Then, the work environment has a positive and significant effect on job satisfaction, while job satisfaction has a significant effect on employee performance. In addition, job satisfaction is able to mediate the effect of work stress and work environment on employee performance. This study provides a theoretical contribution to strengthen the understanding of the role of job satisfaction as an important mechanism that connects work stress and work environment with employee performance. Management needs to manage work stress through a balanced workload and system arrangement and create a safe and comfortable work environment to improve employee satisfaction and performance. These findings underscore the importance of job satisfaction as a basis for formulating human resource policies. This study is limited by the number of respondents, which is not fully representative of the entire population due to difficulties in communicating with employees. Furthermore, limited access to the research location, which is located outside of Yogyakarta, resulted in the distribution and collection of questionnaires being conducted only through long-distance communication. Future researchers are advised to add other variables and use research subjects from different industrial sectors to obtain a more comprehensive and comparable understanding.

Human Resource Management (HRM) plays a crucial role in ensuring that a company is able to grow, compete, and sustain its operations in an increasingly dynamic business environment. Effective HRM practices help organizations optimize employee performance, improve productivity, and maintain workforce stability. One of the key aspects of HRM that significantly influences employee performance is workload and job satisfaction. An imbalance in workload or low levels of job satisfaction may lead to decreased motivation, stress, and reduced work performance. This research aims to explore and evaluate the levels of workload and job satisfaction among employees at PT Indomarco Tangerang 1. Understanding these factors is essential to identify potential problems that may affect employee performance and organizational effectiveness. The study employs a quantitative research approach, which involves collecting numerical data that can be statistically analyzed to provide objective and measurable results. Data were gathered through structured questionnaires distributed to employees. A total of 30 employees from various divisions at PT Indomarco Tangerang 1 participated in this study. Statistical analysis was used to assess the relationship between workload and job satisfaction, as well as their overall condition within the company. The findings of this research are expected to provide useful insights for management in developing appropriate strategies to manage workload effectively and enhance job satisfaction. Ultimately, improving these aspects is expected to contribute to higher employee performance and support the long-term success of the company.

This study aims to analyze employee performance and identify factors that need to be considered in efforts to improve employee performance at PT. Bank Negara Indonesia (Persero) Tbk Maumere Branch Office using the Performance Analysis Quadrant (PAQ) method. Data were collected through interviews and questionnaires. Interviews were used to obtain an overview of employee performance which was analyzed descriptively qualitatively, while questionnaires were used to measure aspects of employee knowledge and work attitudes which were then analyzed using PAQ. The results of the study indicate that in general employee performance is in the good category and has been in accordance with the company's operational standards, however there are still obstacles in the aspects of work quality and timeliness, especially during high workloads. PAQ mapping shows that most competency attributes are in Quadrant A (motivation) and Quadrant D (training), so that improving employee performance needs to be focused on strengthening work motivation, improving work processes and environments, and implementing ongoing training.

The increasing demand for real time parallel processing in cloud computing environments necessitates the development of more efficient and fault-tolerant scheduling algorithms. Traditional scheduling methods, such as static algorithms, often fall short when handling dynamic workloads and system failures, leading to increased task latency and reduced system performance. In contrast, adaptive scheduling algorithms dynamically adjust to changes in system conditions and workloads, ensuring timely task completion and optimized resource utilization. This study evaluates the performance of adaptive scheduling algorithms in real time cloud environments, focusing on key factors such as task latency, system resilience, and fault tolerance. Simulation experiments were conducted using cloud computing models that incorporate fault injection scenarios, including network failures and virtual machine crashes. The results show that adaptive algorithms significantly outperform traditional static schedulers in terms of task latency reduction and improved system resilience. These algorithms demonstrated better fault recovery times and ensured consistent real time performance, even under failure conditions. The findings highlight the advantages of adaptive scheduling in cloud environments, particularly for applications requiring rapid data processing and high system reliability. Despite the promising results, challenges remain regarding the scalability and complexity of these algorithms in large-scale cloud systems. Further research is needed to optimize adaptive scheduling algorithms for efficiency, scalability, and comprehensive performance evaluation, taking into account factors such as energy consumption, cost, and reliability. This research contributes to advancing cloud computing infrastructures that can dynamically handle real time tasks and maintain high performance under varying workloads and failures.

This study investigates the integration of high performance communication protocols with adaptive signal processing engines in multi-core systems, aiming to enhance scalability, throughput, and inter-core communication efficiency. The challenges inherent in traditional multi core architectures, such as communication overhead, latency, and scalability limitations, are addressed through the incorporation of Network-on-Chip (NoC) architectures and adaptive signal processing techniques. By using a multi-core digital signal processing (DSP) platform, the study evaluates the performance improvements achieved by this integration under varying workloads and core configurations. The experimental results show a 35% improvement in throughput and a 25% reduction in communication latency, highlighting the effectiveness of adaptive communication protocols in managing data traffic between cores and reducing bottlenecks. The integration of NoC architecture facilitates parallel data transfers, while adaptive signal processing engines ensure that data flows more efficiently across the cores, enhancing system responsiveness, especially under high data rate conditions. Furthermore, the study explores the scalability of the proposed system, demonstrating its ability to maintain high performance as core counts increase. The findings emphasize the potential of combining advanced communication protocols with adaptive signal processing for optimizing multi-core system performance. Practical implications of this research include the design of scalable, flexible, and efficient multi core architectures suitable for complex, data-intensive applications. Future research should focus on further refining communication protocols and exploring additional integration strategies to enhance the adaptability and scalability of multi-core systems in next-generation computing environments.

Edge-Internet of Things (Edge IoT) systems are increasingly integral to applications that require real time signal processing, particularly where low latency and energy efficiency are critical. This paper explores the design and performance evaluation of a heterogeneous microprocessor architecture aimed at optimizing energy consumption and real time performance. The heterogeneous architecture integrates multiple types of cores, such as Central Processing Units (CPUs), Digital Signal Processors (DSPs), and Graphics Processing Units (GPUs), to allocate tasks based on computational demand. The proposed design significantly reduces energy consumption, particularly during high-performance tasks, while maintaining real time processing guarantees. Simulation-based performance evaluation was conducted to assess the energy efficiency, latency, and overall system performance under varying workloads, including real time Digital Signal Processing (DSP) benchmarks. The results showed that the heterogeneous architecture outperformed traditional homogeneous processors, demonstrating up to a 19-fold improvement in energy efficiency. Furthermore, the system reduced latency by up to 45% in real time applications, making it particularly suitable for Edge IoT environments such as industrial automation and smart healthcare, where both performance and energy efficiency are critical. Despite some trade-offs in task scheduling complexity, the heterogeneous design was able to balance power consumption and computational performance effectively. The findings suggest that this architecture can serve as a foundation for future Edge IoT systems, providing significant advantages in terms of energy efficiency, real time processing, and scalability. Future work will focus on further optimization of the architecture and exploring its application across various IoT environments.

In high-performance computing (HPC) environments, the need to balance memory efficiency and query performance is crucial for ensuring optimal system performance. Traditional data structures, such as B-trees and hash tables, often prioritize either memory usage or query speed, leading to suboptimal performance in memory-constrained systems. This paper proposes a hybrid data structure that combines the strengths of multiple traditional data structures to optimize both memory usage and query processing speed. The proposed hybrid structure integrates cache-conscious algorithms, dynamic memory allocation, and compression techniques for intermediate query results. The approach is evaluated through extensive benchmarking tests comparing it to standard data structures like B-trees and hash tables under various workloads. Results show that the hybrid data structure reduces memory overhead by up to 30% while maintaining query processing speeds up to 1.5 times faster than conventional methods. Furthermore, the hybrid structure demonstrates robust performance across different types of queries, including both point and range queries, ensuring versatility and efficiency. The findings indicate that this hybrid approach provides a promising solution for HPC systems, where both memory efficiency and query speed are essential. Future research can explore extending the hybrid structure to distributed systems and emerging technologies, further improving its scalability and adaptability to new computational paradigms.

Academic stress has become a significant psychological issue among university students, particularly during periods of high academic pressure such as examinations, intensive coursework, and academic performance demands. Excessive academic stress may negatively affect students’ psychological well-being, learning motivation, and academic performance. This study aims to explore in depth the experiences of academic stress and psychological responses among students during periods of high academic pressure. A qualitative descriptive approach with a phenomenological perspective was employed to capture students’ lived experiences. Data were collected through in-depth semi-structured interviews with six student participants selected using purposive sampling. The data were analyzed using thematic analysis, involving open, axial, and selective coding to identify emerging themes. The findings reveal that the main sources of academic stress include excessive academic workload, time management difficulties, high self-expectations, and external academic pressures. Students experienced varying levels of stress ranging from mild to severe, manifested through psychological responses such as anxiety, emotional instability, mental fatigue, decreased concentration, and reduced motivation. The study also found that students applied diverse coping strategies, including adaptive strategies such as time management, seeking social support, and self-reflection, as well as maladaptive strategies such as procrastination and emotional withdrawal. These findings highlight that academic stress is a complex and subjective experience influenced by individual perceptions and coping capacities. The study implies the importance of supportive academic environments and accessible mental health services in higher education institutions to promote students’ psychological well-being and resilience. The results may serve as a reference for developing preventive and promotive mental health programs for students facing academic stress..    

This study aims to analyze the influence of leadership style, work environment, and workload on employee performance at PT BFI Finance Indonesia Tbk, Semarang Branch, using the Job Demands–Resources (JD-R) Theory as its underlying framework. The JD-R model posits that employee performance and well-being depend on the balance between job demands and job resources. The research employed a quantitative explanatory approach involving 56 employees from the Central Operation division, selected through purposive sampling. Data were collected using a Likert-scale questionnaire and analyzed using multiple linear regression with SPSS version 21. The results reveal that leadership style and work environment have positive and significant effects on employee performance, while workload has a significant negative effect. The coefficient of determination (R²) of 0.673 indicates that the three variables collectively explain 67.3% of employee performance variation. Respondents perceived that communication and support from leaders were strong, and social relations in the workplace were positive, although workload and performance targets were considered relatively high. These findings reinforce the JD-R Theory (Bakker & Demerouti, 2017), showing that leadership and work environment function as job resources that enhance motivation and performance, whereas excessive workload represents job demands that may hinder employee outcomes if not properly managed. Practically, organizations in the financial services sector should maintain a balance between job demands and job resources to achieve sustainable employee performance improvement.

This study investigates the impact of intrinsic motivation, workload, and competence on job satisfaction, exploring its implications for employee performance, with job satisfaction serving as a mediating variable. A quantitative approach was employed, utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) for data analysis collected via questionnaires. The results reveal that intrinsic motivation has a positive but insignificant impact on job satisfaction and performance. Workload significantly improves job satisfaction but does not affect performance, while competence significantly enhances both job satisfaction and performance. Additionally, job satisfaction positively affects employee performance. The mediation analysis reveals that job satisfaction mediates the relationship between competence and workload on performance, but does not mediate the relationship between intrinsic motivation and performance. These findings highlight the critical roles of competence and job satisfaction in improving employee performance, suggesting that intrinsic motivation and workload may require additional factors, such as compensation and work environment, to be more effective.

This study aims to comprehensively analyze the influence of workload and work environment on employee performance at PT Bintang Matrik Indonesia, Bekasi City, both partially and simultaneously. The background of this research lies in the importance of optimal human resource management to enhance company effectiveness and efficiency. An unbalanced workload can lead to physical and mental fatigue, reducing motivation and productivity, while an unsupportive work environment may decrease employee comfort and job satisfaction. This study uses a quantitative research method with the Slovin sampling technique and data collection through questionnaires distributed to company employees. Data analysis was conducted using classical assumption tests and multiple linear regression to examine the relationships between variables. The results indicate that both partially and simultaneously, workload and work environment have a positive and significant effect on employee performance. Therefore, the company should pay greater attention to workload balance and create a safe, comfortable, and supportive work environment to improve employee performance and loyalty.

This research aims to analyze the partial and simultaneous influence of Organizational Culture (X_1), Discipline (X_2), Leadership (X_3), and Workload (X_4) on Employee Performance (Y) at PT. PELINDO III (Persero) Tanjung Emas Branch Semarang. Utilizing a quantitative associative approach, data were collected from 50 employee respondents and analyzed using multiple linear regression. The analysis confirmed that X_1, X_2, and X_3 positively and significantly influence Employee Performance, while Workload (X_4) significantly influences performance negatively (\beta = -0.091). Organizational Culture (X_1) was identified as the most influential factor (\beta = 0.461), followed by Leadership (X_3, \beta = 0.313) and Discipline (X_2, \beta = 0.149). The results highlight the critical need for a strong organizational culture and effective leadership in overcoming the inevitable challenges posed by workload pressure in the demanding port environment. The model demonstrated a strong fit, explaining approximately 68.5\% of the variation in Employee Performance. Managerial implications suggest prioritizing culture reinforcement and leadership development to mitigate the negative impact of high operational workload.

The Gas and Steam Power Plant (PLTGU) utilizes exhaust heat from gas turbines to produce steam, which is then used to drive steam turbines. One of the critical processes in this system is seawater desalination, which requires reliable measuring instruments to ensure the continuity and quality of the water supply. The Differential Pressure Flow Transmitter type Azbil JTD920S is used to measure fluid flow rates at four main points: Sea Water Flow (feed), Distillate Water Flow, Condensate Water Flow, and Sea Water to Ejector Condenser Flow. A decline in transmitter performance may occur due to environmental factors, corrosion, and high workload, making periodic preventive maintenance (PM) essential. This study aims to analyze the transmitter’s performance by comparing PM data with the manufacturer’s maximum specifications using literature studies, direct observation, and interviews. The calculation results show that the highest performance levels are found in the Distillate Water Flow (73.53%) and Sea Water to Ejector Condenser Flow (73.87%) lines, while the lowest is in the Condensate Water Flow (49.00%). These findings emphasize the importance of close monitoring of high-performance transmitters to prevent premature failure and maintain the efficiency of the desalination process.

Employee performance is one of the most important factors that determine the achievement of company goals. In the modern world of work, workload and work environment are two factors that are most often considered in influencing employee performance. As a company engaged in the service sector. As a company engaged in the field of supporting services for the oil and gas industry, PT Supraco Indonesia requires high-performing employees to provide the best service to its clients. This study aims to determine how much influence motivation and service levels have on customer satisfaction in participating in computer training. The research method used is a quantitative approach with data collection techniques using random sampling or purposive sampling, where the entire population of 56 respondents was used as a sample. The data collection instrument used a questionnaire with a Likert scale. Data analysis was carried out using SPSS 27 software with multiple linear regression techniques. The results of the study show that the company size variable in particular, Workload (X1) has a significant effect on Employee Performance with a significant t-value on the level of work environment (X2) also has a significant effect with a significant t-value simultaneously, both have a significant effect on employee performance with a calculated F-value. Meanwhile, the coefficient of determination value shows that the influence of workload and work environment on employee performance is significant.

This study analyzes the inclusive education policy in Surabaya and its impact on the performance of elementary school educators. Using a descriptive qualitative approach, data were collected through observation, interviews, and questionnaires, then analyzed using source triangulation. The findings reveal that educators show strong commitment and apply various learning strategies to accommodate students with special needs. However, significant challenges persist, including limited facilities, a shortage of qualified personnel, and insufficient specialized training. In addition, factors such as high workload and social stigma hinder the effective implementation of inclusive education. Despite these obstacles, the policy demonstrates promising potential through systemic support, collaboration with parents, and the contribution of special assistant teachers. To achieve greater effectiveness, improvements in school infrastructure, continuous professional development, and more inclusive educational environments are essential. Strengthening stakeholder cooperation between schools, local governments, and communities will further enhance the sustainability and success of inclusive education in Surabaya.

This study is motivated by the importance of balancing work and personal life (work life balance) to enhance employee performance and well-being. The research aims to analyze the influence of leadership style, workload, and work environment on the work life balance of employees at PT Bina Bangun Perkasa Kediri. A quantitative approach was applied using purposive sampling, with all 35 permanent employees selected as respondents. Data were collected through observation, interviews, and questionnaires, and analyzed using classical assumption tests and multiple linear regression. The findings reveal that leadership style and work environment significantly affect work life balance, while workload has no significant effect. Simultaneously, the three variables show a significant effect on work life balance. These results provide theoretical implications regarding the crucial role of leadership and workplace conditions in supporting employees’ work life balance, as well as practical implications for company management to foster a healthy work environment and effective leadership to improve employee well-being

The purpose of this study was to analyze the effect of mental workload on employee performance, the effect of work stress on employee performance, the work environment on employee performance and to analyze the effect of mental workload, work stress, and work environment simultaneously on the performance of employees of PT. Nutrisius Sari Persada. This research design uses quantitative methods with an associative approach and data collection techniques of library research and field research. Data analysis techniques using descriptive statistical analysis techniques using data processing tools Structural Equation Modeling (SEM) with SmartPLS software by testing mental workload variables (X1), work stress (X2), work environment (X3) and employee performance (Y). The results of this study indicate that the mental workload variable (X1) on employee performance (Y) has a T-test value of (2.013> 1.96) and P values of (0.045 < 0.05), the work stress variable (X2) has a T-test value of (10.237> 1.96) and P values of (0, 000 < 0.05), the work environment variable (X3) has a T-test value of (2.013> 1.96) and P values of (0.045 < 0.05), so it can be concluded that the mental workload variable (X1), work stress (X2) and the work environment (X3) have an influence on employee performance (Y). While simultaneously mental workload (X1), work stress (X2) and work environment (X3) variables on employee performance (Y). The results of the analysis of the coefficient of determination (R2) obtained a value (Adjusted Rsquare) of 0.973, meaning that all independent variables are declared strong with a value of 97% and the remaining 3% is influenced by other variables outside the Mental Workload, Work Stress and Work Environment variables.