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This study aims to simulate the M/M/1 queueing system using Python through a Modeling and Simulation approach supported by the Discrete-Event Simulation (DES) method. The objective of the research is to analyze key performance indicators of queueing behavior, including arrival time, service time, waiting time, queue length, and server utilization. The methodology employs DES, which models system behavior based on discrete events such as customer arrivals, service initiation, and service completion. The simulation generates stochastic arrival and service times using Poisson and exponential distributions, respectively. The results indicate that the DES-based M/M/1 simulation accurately reflects theoretical queueing behavior, showing increases in waiting times and queue lengths when arrival rates approach service rates, while server utilization corresponds to system load intensity. The findings demonstrate that DES is an effective approach for analyzing queue performance and can be extended to more complex models such as multi-server systems, priority queues, and predictive simulations using artificial intelligence.

The rapid expansion of e-commerce in Indonesia has resulted in a significant rise in the number of customer reviews, which serve as a valuable source of insight for understanding consumer satisfaction. This study aims to classify or identify sentiments from product reviews on the Tokopedia platform into three categories, using the Support Vector Machine algorithm. The classification method data were ethically collected through web scraping and include review text, ratings, and the number of “likes.”  The preprocessing stage involved several NLP techniques such as pre-procesesing data representation was generated using the Term Frequency–Inverse Document Frequency method, while the issue of class imbalance was addressed using the Synthetic Minority Over-sampling Technique.  Based on the test results, the SVM model achieved an accuracy of 79.48% on the test data using a linear kernel, showing the best performance in classifying positive sentiments. However, the classification of neutral and negative sentiments still requires improvement. This study demonstrates that the combination of the TF-IDF method, additional numerical features, and data balancing techniques can produce an an efficient sentiment analysis model within the e-commerce domain.

This study aims to analyze the influence of proactive behavior on competitive advantage in quail breeder MSMEs in Bendowulung Village, Sanankulon District, Blitar Regency. The background of this research is based on the importance of increasing the competitiveness of MSMEs in the livestock sector in order to be able to survive and develop in the midst of increasingly competitive market competition. The research method uses a quantitative approach with data collection techniques through surveys or questionnaires distributed to quail farming MSMEs. The data were analyzed using statistical methods, including validity tests, reliability tests, classical assumption tests, linear regression tests, and hypothesis tests to determine the significance of the influence of proactive behavior on competitive advantage. The results of the study show that proactive behavior has a positive and significant influence on competitive advantage. These findings indicate that the higher the level of proactive behavior of an individual or organization, the greater their ability to innovate, take initiative, and adapt to changing business environments. Thus, proactive behavior is a strategic factor in strengthening the position of quail breeder MSMEs in the market, increasing revenue, and encouraging sustainable business performance. This research contributes to the development of MSME management theory and practical recommendations for business actors and policy makers.

Economic growth is the process of increasing a country's production capacity to generate goods and services over a specific period, reflecting the income and well-being of its people. This research aims to analyse the influence of labor, exchange rates, and exports on the Gross Domestic Product (GDP) of the manufacturing sector in Indonesia during the period 2010-2024. The method used is multiple linear regression analysis with the Ordinary Least Square (OLS) approach, using secondary data obtained from the Central Bureau of Statistics (BPS) and Bank Indonesia (BI). The research results indicate that all three independent variables, namely labor, exchange rate, and exports, have a positive and significant impact on the GDP of the manufacturing sector, both partially and simultaneously. The coefficient of determination (Adjusted R2) value of 0.9633 indicates that 96.33% of the variation in industrial sector GDP can be explained by these three variables, while 3.76% is influenced by factors outside the model. This research confirms that increased labour productivity, exchange rate stability, and export growth play an important role in strengthening the performance of the manufacturing sector in Indonesia. Therefore, policies focused on improving the quality of human resources, strengthening export competitiveness, and ensuring macroeconomic stability are needed to support the sustainable and globally competitive growth of the manufacturing sector.

This study aims to analyze and project consumer prices of cabbage commodities at four levels: Ngawi Regency, Pacitan Regency, East Java Province, and nationally, using the additive Holt–Winters forecasting model. Monthly price data for the period January 2020–December 2024 were used to capture the dynamics of levels, trends, and seasonal patterns that affect price fluctuations. Model performance was evaluated using the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) indicators. The results showed differences in model accuracy between regions. East Java Province produced the best performance with the lowest MAE and RMSE values, indicating a more stable price pattern that was easier for the model to capture. In contrast, Ngawi Regency showed the highest volatility, resulting in greater forecasting errors. Pacitan Regency displayed a relatively consistent seasonal pattern with moderate accuracy, while national data showed smoother fluctuations due to the aggregation effect. Overall, the additive Holt–Winters model is effective for short-term projections in regions with low to moderate variability, but is less optimal in regions with highly volatile price dynamics.

This study aims to analyze the development and scientific relationship between carbon risk perception, behavioral compliance of accountants, and sustainability mindset on the accuracy of carbon performance reporting through a bibliometric approach. This study is driven by the increasing need for accurate carbon reporting amidst global demands for sustainability transparency, as well as the limited understanding of the role of behavioral and psychological factors of accountants in ensuring the reliability of carbon reports. Research data was obtained from two leading scientific databases, namely Scopus and Google Scholar, with the main keywords "carbon risk perception," "behavioral compliance of accountants," "sustainability mindset," and "accuracy of carbon performance reporting." The data selection process was carried out using the PRISMA method to ensure the relevance and validity of the analyzed articles, while bibliometric analysis and visualization were performed using VOSviewer software. The results of the study indicate that the topic related to carbon reporting accuracy has evolved from a technical approach to a behavioral and psychological approach. Network and density visualizations show that behavioral compliance and sus-tainability mindset issues are still new but have high potential for development. Meanwhile, the authors' collaboration map demonstrates the geographic limitations of research, which remains concentrated in developed countries. These findings have important theoretical and practical implications, namely the need to integrate behavioral theory and professional ethics into sustainability accounting research and to en-hance accountants' capacity to understand carbon risks to ensure the accuracy of future sustainability re-porting.

Effective collaboration is a strategic imperative for contemporary organizations, yet its success hinges critically on team dynamics and underlying psychological factors like Trust and Psychological Safety. The purpose of this Systematic Literature Review (SLR) was to synthesize empirical research published between 2020 and 2025 to clarify how these psychological factors influence collaboration and team performance. Following the PRISMA guidelines, a rigorous search on Google Scholar using keywords such as "team performance," "psychological factors," and "collaboration" resulted in the final inclusion of 15 articles for in-depth synthesis. Findings confirm that Trust is the most vital psychological construct, acting as a crucial mediator: it successfully transmits the positive effects of Transactional Leadership on employee performance and, conversely, mediates the detrimental effect of Toxic Leadership leading to Employee Silence. Leadership Soft Skills and Emotional Intelligence are identified as primary antecedents that build perceived trustworthiness, which, in turn, significantly reduces Turnover Intention. The review also highlights emerging contexts: trust is now influenced by Agent-Related Factors in Human-AI Teams (HATs), and unconventional factors like Corporate Comedy are found to positively contribute to Group Cohesion. However, contradictory findings regarding trust's role in Knowledge Sharing suggest a significant research gap. This SLR concludes that building psychological capital is fundamental to effective collaboration and recommends that future research utilize Structural Equation Modeling (SEM) to validate conceptual frameworks and employ mixed-methods approaches to resolve contextual conflicts within the literature.

This study aims to assess the growth rate of harvested area and rice production in Bengkulu Province during the 2019–2024 period and to examine spatial variation across districts as a basis for regional agricultural policy planning. The data used are secondary, consisting of a series of spatial and temporal data on harvested area and rice production; the analysis method includes calculating the compound annual growth rate (CAGR) for each indicator and examining temporal and spatial patterns across districts. The analysis results indicate a negative growth rate in the rice sector, with a relatively larger contraction in harvested area compared to production, accompanied by fluctuations and differences between years, indicating heterogeneity in agricultural performance at the district level. These findings have clear policy implications: the need for agricultural land protection measures, improvement and maintenance of irrigation infrastructure, increased farmer access to technology and markets, and the implementation of indicator-based growth rate monitoring to determine intervention priorities. To strengthen the policy base, recommended further research includes field verification and combined (quantitative-qualitative) studies to identify local factors driving the observed trends and fluctuations.

Digital information literacy and digital informal learning are especially fundamental in improving the efficiency of teachers instruction within a context of limited resources such as Islamic secondary schools of Southern Pakistan. This paper examines how digital competencies (ex: information literacy, technology use, and communication) and digital informal learning (e.g.: self-directed learning thru online platforms) make teachers able to deliver engaging lessons, manage classrooms, and encourage student-centered learning. Although interest in digital education is increasing, little research has considered such aspects in rural to Islamic schools. In a quantitative research, 450 teachers of Islam secondary schools and Southern Punjab comprised the purposive sample in which the structured questionnaires were administered and assessed using SPSS v 22, descriptive statistics, correlation and multiple linear regression. Results have shown that increased digital capabilities lead to a strong increase in instructional effectiveness, whereas digital informal learning brings cultural awareness and invention of new practices in teaching. A combination of these factors enhances the delivery of the lesson, student participation, and classroom management. The research suggests considering digital competency training and informal learning materials as part of teacher development companies in order to improve educational performance in the under-resourced Islamic schools.

This study aims to analyze and explain in greater detail the influence of service quality in managing the Business Identification Number (NIB) through the Online Single Submission (OSS) system on public satisfaction at the Investment and One-Stop Integrated Service Office (DPMPTSP) of Gresik Regency. A quantitative research method was employed, using a structured survey design and distributing questionnaires to 105 respondents who had directly utilized and experienced the OSS service. Service quality was measured using the SERVQUAL dimensions tangible, reliability, responsiveness, assurance, and empathy while public satisfaction was assessed based on indicators derived from the Regulation of the Minister of Administrative and Bureaucratic Reform No. 14 of 2017. The collected data were analyzed using simple linear regression to identify the extent of the relationship between variables. The results indicate that service quality has a positive and significant effect on public satisfaction. This means that better, more consistent service quality will increase user satisfaction. The findings confirm that strengthening service quality is essential for improving overall public service performance, especially in digital-based licensing systems.

This study evaluates the impact of TATO, ROA, DER, stock returns, and firm size on company value (PBV) for 28 infrastructure companies listed on the Indonesia Stock Exchange (IDX) during 2021–2023. The background to this research is the crucial role of the infrastructure sector amid government budget dynamics that affect corporate performance and investor perception. The results show that ROA, DER, and stock returns have a significant positive effect on company value. This indicates that high profitability, optimal debt management, and good stock returns send positive signals to the market. Conversely, TATO was found to have a significant negative effect, reflecting that inefficiencies in asset management can reduce investor confidence. Meanwhile, firm size had no significant impact on company value. This study recommends that investors use ROA, DER, and stock return as key indicators in decision-making. At the same time, companies are advised to optimise profitability and debt management to enhance their value in the eyes of investors.

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.

The company must be able to make the right policies so that the company can maintain its survival, so that the company can compete with competing companies and gain the trust of consumers. One of the important factors in achieving goals is HR (Human Resources) which has a very important role in determining the success of a company. This research aims to analyze the effect of work-life balance on job satisfaction and employee performance. This type of research uses quantitative research with a questionnaire instrument. The results of descriptive analysis show that all indicators of work-life balance, job satisfaction, and employee performance are in the “Good Enough” category, indicating that respondents' perceptions of work-life balance, job satisfaction, and employee performance still need to be improved. Validity and reliability tests show that the instruments used are valid and reliable. The results of structural model testing show that work-life balance has a significant and strong effect on employee performance (O=0.822; p<0.001) and job satisfaction (O=0.677; p<0.001), while job satisfaction also affects performance (O=0.367; p=0.006). In addition to the direct effect, there is also a significant indirect effect of work-life balance on performance through job satisfaction (O=0.249; p=0.011). Work-life balance improves employee performance, both directly and through increased job satisfaction, so companies are advised to create policies that support work-life balance in order to create a productive and sustainable work environment.

The growth in the number of vehicles in Surabaya has led to increased traffic congestion, particularly on the Perak Timur–Perak Barat road section, which serves as a major distribution route to the port and industrial areas. Problems arise at U-Turn points, where vehicle accumulation hampers traffic flow. This study analyzes traffic volume, travel time, queue length, and queue ratio at two U-Turn points on this section. The method used was a field survey with direct observation of vehicle volume every 15 minutes, vehicle classification, and queue length. Traffic volume was calculated using the Passenger Car Equivalent (PCE) factor based on the 1997 MKJI standards. The study results show that at Point 1, east–west direction, the highest queue ratio occurred on Tuesday from 11:00 to 12:00 (p = 4.84), while the lowest was on Sunday from 06:00 to 07:00 (p = 0.21). At Point 2, west–east direction, the highest queue ratio occurred on Tuesday from 08:00 to 09:00 (p = 6.18), and the lowest from 06:00 to 07:00 (p = 0.41). These findings indicate that during peak hours, traffic congestion increases (p > 1), causing long queues, particularly in the west–east direction in the morning. The performance of the U-Turn on the Perak Timur–Perak Barat road section needs improvement, with recommendations such as temporarily closing U-Turns during high volumes, providing alternative U-Turn lanes, and adding signs to minimize the potential for vehicle conflicts.

This study aims to see the effect of Debt to Equity Ratio (DER) and Return on Assets (ROA) on Stock Price in PT. Wilmar Cahaya Indonesia, Tbk which is listed on the IDX during the period 2015–2022. The data used in this study is in the form of the company's annual financial statements obtained through secondary sources. This study uses a quantitative approach with multiple linear regression analysis methods, while data processing is carried out using the SPSS application. The results of the study show that partially the Debt to Equity Ratio (DER) variable has a negative effect on the Share Price, while the Return on Assets (ROA) does not have a positive effect on the company's Share Price. However, the results of the simultaneous test show that DER and ROA together have a positive and significant influence on the Stock Price. These findings provide an idea that the combination of capital structure and profitability remains an important indicator in assessing the performance of a company's shares even though their partial relationships show different tendencies. In addition, this research can be a reference for investors in considering the company's fundamental condition before making investment decisions, as well as provide additional insights for management in managing the capital structure more optimally.

This study aims to analyze the effect of Environmental, Social, and Governance (ESG) on the financial performance of mining companies listed in the Jakarta Islamic Index (JII70) for the 2020–2024 period, with the Debt to Equity Ratio (DER) as a control variable. The findings show that, partially, the Environmental variable has a positive but insignificant effect on ROA, indicating that efforts in energy efficiency, waste management, and emission reduction have not yet been fully reflected in short-term profitability. In contrast, the Social variable has a significant effect on ROA, emphasizing that companies’ engagement in building stakeholder relationships, protecting employee rights, and implementing social responsibility programs contribute substantially to financial performance. The Governance variable also has a significant effect on ROA, highlighting the importance of good governance practices, transparency, and accountability in enhancing profitability. Meanwhile, the control variable DER shows no significant effect on ROA. Simultaneously, ESG performance has a significant effect on ROA, proving that integrated ESG implementation supports the profitability of mining companies. These findings confirm that ESG is not only a compliance measure with sustainability principles but also a long-term business strategy that strengthens companies’ competitiveness and serves as a crucial consideration for investors in making investment decisions.

This community service activity aims to strengthen teachers' capacity to manage deep learning through the utilization of artificial intelligence (AI) in elementary school classrooms. The rapid development of AI technology provides opportunities for teachers to design more personalized learning, conduct assessments efficiently, and make data-driven learning decisions. The program is implemented in three stages: preparation, execution, and evaluation. The preparation stage includes the development of training modules and mapping relevant AI applications to support deep learning. The execution stage consists of workshops, hands-on practice using AI applications, and collaborative development of teaching materials by teachers. Evaluation is conducted through reflective assessments, task performance evaluations, and follow-up interviews. The results of the activity show significant improvements in teachers' understanding of AI-based deep learning management, including the ability to use AI for lesson planning, formative assessment, and analyzing students' learning progress. Teachers also reported increased confidence in integrating AI into teaching activities and recognized the benefits of AI in promoting students' higher-order thinking skills. This program demonstrates that strengthening teachers' competencies in utilizing AI can enhance the quality of deep learning management in elementary schools.

This research is motivated by the importance of managerial skills in improving business productivity and efficiency, particularly in the entrepreneurial sector, which faces the challenges of competition, market changes, and limited resources. The objective of this study is to analyze the role of managerial skills development and its contribution to optimizing entrepreneurial performance. The method used is a Systematic Literature Review (SLR), which examines various relevant scientific publications and then categorizes the findings to obtain a comprehensive overview of effective strategies for improving managerial competency. The results indicate that technical skills, human relations skills, and conceptual skills play a significant role in supporting decision-making processes, resource management, and adapting business strategies to business dynamics. The findings also indicate that training, mentoring, continuous learning, and the use of technology are development strategies capable of significantly increasing productivity and efficiency. The implications of this research emphasize that improving managerial skills is a strategic necessity for entrepreneurs to strengthen competitiveness, increase operational effectiveness, and promote business sustainability. Furthermore, this research provides a basis for the development of more structured training programs and supporting policies to strengthen the managerial capacity of entrepreneurs.

Vocabulary acquisition is fundamental to language proficiency, yet retention remains a persistent cognitive challenge for students. Conventional rote-learning strategies often fail to facilitate long-term recall. This study examines the effectiveness of the keyword technique in improving students’ vocabulary mastery. Employing a quantitative quasi-experimental design, the research involved 48 students selected through cluster random sampling. The samples were separated into two groups: an experimental group of 26 students (taught by using the keyword technique) and a control group of 22 students (taught by using conventional strategy). Data were collected using a validated multiple-choice vocabulary test administered before and after the treatment. This result validates a notable difference in outcomes where the experimental group demonstrated better performance; consequently, the alternative hypothesis (Ha) is accepted, leading to the rejection of the null hypothesis (H0). These findings confirm that the Keyword Technique significantly enhances vocabulary mastery by leveraging acoustic and imagery associations. Consequently, this strategy is recommended to foster more effective vocabulary retention.

This study aims to analyze the influence of transactional leadership, servant leadership, and work integrity on employee performance at PT. Istana Argo Kartika (Sanken) Surabaya Branch. The research applies a quantitative approach with an associative design to examine the relationships among variables. The population consists of all permanent employees, and because the total number is limited, a saturated sampling technique was used so that every employee could serve as a respondent. Data were collected through structured questionnaires and later analyzed using multiple linear regression to determine both partial and simultaneous effects. The findings reveal that transactional leadership, servant leadership, and work integrity each have a positive and significant impact on employee performance when tested individually. In addition, the combined influence of all three variables also shows a significant contribution to overall performance levels. These results suggest that firm direction, supportive service-oriented leadership, and strong adherence to integrity can effectively improve employee outcomes. Therefore, this study is expected to provide useful insights for management in designing leadership development programs and strengthening human resource strategies.