Publication Search

This study aims to analyze various factors influencing the decisions of tobacco farmers in Wuluhan District, Jember Regency, in using the tebasan (bulk sale before harvest), and how this is viewed from the perspective of Islamic economics. The variables examined include income, farming experience, education level, and the perspective of Islamic economics, whose influence on selling decisions was tested using a quantitative approach through Structural Equation Modeling (SEM) with the help of SmartPLS software. The results of the study show that: Income, farming experience, and education do not have a direct significant effect on the decision to sell tobacco .However, these three variables have an indirect effect through the variable of the Islamic economic perspective.The Islamic economic perspective is proven to play a significant role as a mediating variable, influencing farmers' decisions to sell tobacco. In practice, the tebasan system does offer efficiency and certainty for farmers, but it contains elements of uncertainty (gharar) that must be critically reviewed in the context of Islamic sales law.

Accurate wind turbine power curve modeling plays a crucial role in performance evaluation, energy yield estimation, and data-driven control strategies. However, actual power curves often exhibit non-linear behavior influenced by atmospheric variability, measurement noise, and SCADA anomalies, making conventional modeling approaches less effective. This study proposes an optimized logistic power curve model whose parameters are tuned using Particle Swarm Optimization (PSO) to improve predictive accuracy. The analysis uses the Wind Turbine SCADA Dataset from Kaggle, which undergoes extensive preprocessing including physical rule filtering, outlier detection with the Interquartile Range (IQR) method, anomaly removal, and smoothing of the power signal. A three-parameter logistic model is selected due to its ability to capture the typical S-shaped relationship between wind speed and power output. PSO is applied to identify optimal model parameters by minimizing the Mean Squared Error (MSE), utilizing 40 particles over 200 iterations. The optimized model achieves strong predictive performance with RMSE of 404.09, MAE of 179.96, and R² of 0.904 on the test set, indicating that more than 90% of the variability in actual power can be explained by wind speed. Residual analysis reveals heteroscedastic patterns and slight overestimation in mid-range wind speeds, yet overall model consistency remains high. Comparative evaluation against Linear Regression, Random Forest, and logistic modeling using curve_fit shows that the Logistic–PSO approach provides the most accurate and stable predictions. These findings demonstrate that combining logistic modeling with PSO offers an effective and robust method for data-driven wind turbine power curve optimization.

Bridge planning is a fundamental aspect in the development of transportation infrastructure that functions to connect regions, facilitate traffic flow, and support economic and social growth in the community. This study aims to comprehensively examine the stages of bridge planning, from identifying traffic needs and analyzing geotechnical conditions to selecting a structure type, and evaluating technical, economic, and environmental aspects. The methods used include field surveys, traffic data collection, design load analysis, and structural simulation using modeling software. The study results indicate that bridge type selection is not only determined by load capacity and cost efficiency, but must also consider sustainability, aesthetics, and the impact on the surrounding ecosystem. This study emphasizes the importance of integrating technical, social, and environmental aspects in bridge planning, so that the resulting design can provide a safe, efficient, and sustainable solution. Thus, bridge planning is not merely a technical process, but also a development strategy that supports connectivity and community welfare.

This study aims to explore and evaluate the implementation of the Curriculum of Love as a comprehensive preventive approach to addressing bullying in Senior High Schools. Bullying, defined as repeated negative behaviors intended to harm others through verbal, physical, or social actions, has become a serious problem in schools across Indonesia. Its effects on victims include physical and psychological health issues, reduced self-confidence, and in severe cases, suicidal thoughts. The research uses a literature review method, analyzing various academic sources such as journals and scholarly reports because the topic is closely related to theoretical concepts and theological values. The Curriculum of Love is a humanistic, holistic, and transformative educational model that emphasizes love, empathy, care, and compassion as central to all learning activities. Its core values of love, tolerance, and harmony form the foundation for promoting positive behavior. Findings indicate that this curriculum effectively addresses the complex causes of bullying, including individual, family, and social factors, by systematically instilling these core values. Implementation involves cultivating love for God to strengthen moral responsibility, love for fellow humans to foster respect and empathy, and practical activities such as role play, classroom companion programs, peaceful conflict resolution training, and teacher modeling. The Curriculum of Love creates a safe and supportive school environment and serves as an essential preventive and transformative educational strategy.

This study analyzes pronunciation learning activities in the English class at SDN 060877 through direct classroom observation techniques. The research aims to understand how teachers organize pronunciation instruction, the strategies applied during learning sessions, and the level of student participation in practicing correct sounds, stress patterns, and intonation. Using a qualitative descriptive approach, data were collected through on-site observations focusing on teaching procedures, interaction patterns, learning media, and students’ responses. The findings indicate that pronunciation learning is integrated into reading and speaking activities, where the teacher models sound, guides repetition drills, and provides corrective feedback. Students demonstrate varied levels of confidence, with some actively engaging in pronunciation tasks while others rely heavily on teacher prompts. Environmental factors, such as limited audio-media tools and large class size, affect the intensity and effectiveness of practice sessions. Despite these challenges, classroom interactions show that learners gradually improve their sound accuracy and rhythm through continuous modeling and peer practice. This study concludes that direct observation provides comprehensive insights into real classroom dynamics, revealing both the strengths and areas needing improvement in pronunciation teaching. Recommendations are offered to enhance instructional techniques, learning materials, and student engagement.

This study aims to analyze the influence of policy effectiveness and efficiency on public trust and the use of the Trans Siginjai public transportation system in Jambi City. The research background stems from the low public interest in using Trans Siginjai services since its operation in 2017, as reflected in the relatively small number of daily passengers. This research employs a quantitative method with an explanatory approach. Primary data were collected through a Likert-scale questionnaire distributed to 100 respondents determined using the Slovin formula, while secondary data were obtained from official documents and local media publications. Data were analyzed using the Structural Equation Modeling–Partial Least Squares (SEM-PLS) method with the assistance of SmartPLS 4 software. The results show that both effectiveness and efficiency have a positive and significant effect on public trust, while trust significantly influences the level of Trans Siginjai usage. These findings emphasize that the success of public transportation policy depends not only on operational efficiency but also on the government’s ability to build public trust through consistent and high-quality service delivery.

This research seeks to examine the influence of digital competency on employee performance, with employee engagement serving as a mediating variable at the Jakarta Mampang Prapatan Tax Office (KPP Pratama). The research employed a quantitative methodology utilizing Structural Equation Modeling (SEM) with Smart PLS, derived from data collected from 106 employees. The findings indicate that digital competency significantly influences employee engagement, which in turn positively affects employee performance. Digital competency also has an indirect effect on how well employees do their jobs by making them more engaged. These results validate that enhancing employee digital competency must be succeeded by bolstering employee engagement to achieve optimal performance improvement. This research makes an empirical contribution to the literature regarding digital competency and work engagement within the public sector and presents practical implications for enhancing human resource capacity to facilitate the modernization of tax services.

This study aims to thoroughly examine the triadic relationship among the Internalization of Aswaja An-Nahdliyah Values, the Pedagogic Competence of Ustadz/Ustadzah, and the Academic Supervision by the Kyai at the Salafi Sunanul Huda Islamic Boarding School in Sukabumi Regency. The research urgency is based on the vital role of the pesantren (Islamic boarding school) as a fortress of moderate ideology and the existence of a research gap that has not holistically integrated these three variables within the specific Salafi-Nahdliyyah context of the locus. The Aswaja An-Nahdliyah values central to the internalization process include Tawasuth (moderation), Tasamuh (tolerance), I'tidal (justice/firmness), Tawazun (balance), and Amar Ma'ruf Nahi Munkar (enjoining good and forbidding wrong). This internalization is carried out through the formal curriculum (teaching Kitab Kuning using the Sorogan and Bandongan methods) and the non-curricular aspects (Kyai/Ustadz role-modeling and pesantren living values). The study utilizes a qualitative approach with a Case Study design. Data collection employs Method Triangulation involving In-depth Interviews (Kyai, Ustadz, Students), Limited Participatory Observation (learning processes and cultural activities), and Document Study (Lesson Plans, curriculum, and supervision reports). Data analysis employs the interactive model of Miles, Huberman, and Saldana (Data Condensation, Data Display, and Conclusion Drawing). The research findings are expected to formulate the Integrated Model of Triguna Santri in Aswaja An-Nahdliyah Internalization, which synergizes traditional pesantren methods with culture-based quality assurance. Practically, these findings will provide blueprints for quality assurance (Cultural-Authoritative Academic Supervision) and recommendations for pedagogical strategies for Ustadz/Ustadzah to enhance the transfer of values from the cognitive level to the affective and behavioral domains. This model is expected to become a benchmark for developing educator competence and strengthening religious moderation in similar pesantren.

The development of information technology requires public institutions to provide accessible and transparent information services. Polsek Kota Kisaran still faces limitations in delivering information to the public through digital media. This study aims to design and implement a profile website as a public information medium that supports service transparency. The research uses a qualitative descriptive approach with data collection through observation, informal interviews with police officers, and documentation. System development includes requirement analysis, system modeling using Unified Modeling Language (UML), interface design, and website implementation. The results indicate that the developed website is able to present structured information such as institutional profiles, organizational structures, SKCK procedures, SPKT services, news, and activity documentation. The implementation of this website facilitates public access to police information and improves the effectiveness of information dissemination. This study is expected to support digital-based public services at the local police level and strengthen public trust through transparent information delivery.

Chronic kidney disease is an increasingly prevalent health issue that requires more precise clinical data-based early detection methods to enable timely and appropriate treatment. This study focuses on developing a predictive model for chronic kidney disease using the Light Gradient Boosting Machine (LightGBM) algorithm and enhancing its performance through hyperparameter optimization with the Grey Wolf Optimizer (GWO). The dataset used originates from public sources and undergoes several preprocessing steps, including missing value imputation, categorical feature encoding, outlier handling, initial feature selection, and stratified data splitting to maintain model quality. Three modeling approaches were evaluated: LightGBM with default parameters, LightGBM enhanced using Random Search, and LightGBM optimized with GWO. The experimental results indicate that the baseline model already performs well, Random Search improves accuracy and F1-score, and GWO achieves the highest AUC-ROC value despite requiring longer computation time. Significance testing through cross-validation shows that the performance differences among the three models are not statistically significant, suggesting that the observed improvements are not strong enough to determine a definitively superior optimization method. The feature importance analysis highlights that clinical indicators such as creatinine levels, glomerular filtration rate, blood pressure, and urine protein contribute most prominently to the prediction. Overall, the study demonstrates that LightGBM is a reliable model for early detection of chronic kidney disease, and hyperparameter optimization still offers added value that can support the development of AI-based clinical decision-support systems

Civil engineering infrastructure development plays a vital role in driving economic progress and enhancing the quality of life within communities. The success of infrastructure projects depends not only on budgetary and technological factors but also on the quality of human resources (HR) involved in every project phase, from planning to maintenance. This literature review highlights that skilled and competent HR is a critical factor in achieving project success, particularly amidst increasing complexity and the challenges posed by globalization. Key issues faced by the sector include a shortage of skilled labor, high turnover rates, and a misalignment between educational outcomes and the skills required in the field. Additionally, technological advancements, such as the adoption of Building Information Modeling (BIM) and Artificial Intelligence (AI), demand continuous skill enhancement to adapt to the growing automation of industry processes. Effective HR management—encompassing ongoing education, fair incentive systems, and the integration of technology into HR practices—is essential for boosting productivity and mitigating risks during project execution. A comprehensive approach, including a structured HR management system, is required to ensure the sustainability and quality of infrastructure development. This study aims to provide an in-depth understanding of the critical role of HR management in the civil engineering sector and proposes practical recommendations for improving HR quality to meet the evolving demands of the construction industry.  

The implementation of patient safety culture in hospitals remains a significant challenge, often leading to adverse events. Establishing a strong patient safety culture requires effective interprofessional collaboration among healthcare professionals to deliver patient-centered care. However, factors such as organizational distrust and job dissatisfaction continue to hinder collaborative efforts and negatively affect the quality of care and patient safety outcomes.This study aims to examine the influence of organizational trust and job satisfaction on patient safety culture, with interprofessional collaboration serving as an intervening variable at MP hospital.  This quantitative associative research used a causal approach involving 93 inpatient nurses as respondents. Primary data were obtained through questionnaires using an ordinal scale based on a 4–1 Likert scale. Data processing employed the three-box method, and data analysis was conducted using Structural Equation Modeling (SEM).The results revealed that organizational trust, job satisfaction, and interprofessional collaboration simultaneously and partially influence patient safety culture. Moreover, interprofessional collaboration was found to mediate the relationship between organizational trust, job satisfaction, and patient safety culture.The study concludes that enhancing patient safety culture can be achieved by strengthening organizational trust and job satisfaction through effective interprofessional collaboration. Hospitals should develop supportive systems that foster care and concern among staff, enhance conflict management, improve performance appraisal mechanisms, and promote open, effective communication across all professional groups involved in patient care. These strategies can create a safer, more collaborative, and high-quality healthcare environment

This study aims to outline how aqeedah and moral values are applied in the learning process of fourth-grade students at MI Ridogalih, examine the strategies teachers use to internalize these values, and identify factors that support or hinder the process. Using a descriptive qualitative method, the research gathered data from the Aqeedah–Akhlaq teacher, instructional documents, and records of the school’s religious activities. Data collection was conducted through guided interviews and document review, and the analysis followed the Miles and Huberman interactive model. The results show that the incorporation of aqeedah and moral education is implemented through consistent religious habituation, exemplary behavior demonstrated by teachers, and the integration of Islamic principles into classroom instruction. Contributing factors include the strong religious environment of the school and active parental engagement, while obstacles stem from the influence of digital media and the varied backgrounds of students’ families. The study concludes that combining habituation practices, teacher role modeling, and value integration plays a significant role in reinforcing students’ Islamic character development.

This study aims to examine customer segmentation through K-Means clustering from a customer data management perspective, emphasizing the interpretive value of analytical results rather than solely their computational outcomes. The research addresses a critical issue in contemporary data-driven organizations, where customer analytics is often reduced to technical modeling without sufficient translation into managerial insights. To respond to this gap, the study adopts a qualitative interpretive approach embedded within a quantitative clustering process, positioning clustering as part of a broader information management cycle. The empirical analysis is based on the Mall Customers Dataset obtained from Kaggle, consisting of 200 customer records with numerical attributes representing age, annual income, and spending score. Quantitative processing using K-Means clustering was employed to identify customer segments, while qualitative interpretation was applied to analyze the managerial meaning of each cluster. Data interpretation was supported by analytical documentation, visualization outputs, and reflective analysis of cluster characteristics. The findings reveal four distinct customer segments with different behavioral and economic profiles, each carrying specific strategic implications for customer relationship management and marketing decision-making. The study demonstrates that the primary value of clustering lies not merely in segment formation, but in its ability to transform raw customer data into actionable managerial knowledge. In conclusion, this research contributes to customer analytics literature by integrating data mining techniques with qualitative interpretation, offering a more human-centered and decision-oriented framework for customer data management. Future research is encouraged to extend this approach using organizational case studies or participatory decision-making contexts.

Objectives: This study aims to analyze the direct and indirect effects of Servant Leadership on lecturers’ Job Performance through the mediating variables of Job Satisfaction, Employee Engagement, and Organizational Citizenship Behavior (Organizational Citizenship Behavior). The study also seeks to identify which mediating variable has the strongest influence in explaining the relationship between leadership and performance among lecturers in private universities. Methodology: This study applies a causal quantitative approach using a survey method with a sample of 155 lecturers from Information Technology study programs at private universities in West Java. Data were collected through questionnaires and analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS) to test ten research hypotheses and evaluate the mediating effects among variables. Findings: The results show that Servant Leadership has a positive influence on Job Satisfaction, Employee Engagement, and Organizational Citizenship Behavior, but does not directly affect Job Performance. Among the mediators, only Organizational Citizenship Behavior significantly mediates the relationship between Servant Leadership and Job Performance, indicating that lecturers’ voluntary behavior plays a key role in improving performance. In contrast, Job Satisfaction and Employee Engagement do not act as significant mediators. Conclusion: The findings highlight that leadership effectiveness in higher education depends on fostering Organizational Citizenship Behavior rather than relying solely on satisfaction or engagement. The study introduces the concept of Emphatic Leadership, which emphasizes empathy, accountability, and humility as essential values for leaders in academic environments. This approach offers practical insights for developing participative and humanistic leadership models to enhance lecturers’ academic performance.

The Family Welfare Empowerment (PKK) is a vital community organization with a significant role in addressing social issues. One such issue is the increasing number of juvenile delinquency cases in schools, which has become a major concern for both educational institutions and parents. Schools must be proactive in monitoring their students to address this problem effectively. However, traditional manual monitoring processes are inefficient and time-consuming. To overcome this, there is a need for an efficient, user-friendly, and multi-user monitoring system that enables both schools and parents to access information about their children's behavioral violations. This student violation monitoring system is designed to be web-based, utilizing UML (Unified Modeling Language) for system design and employing the Waterfall development method. The goal of this system is to provide an effective solution for managing and tracking student violations, allowing for better control and prevention of delinquent behavior within the school environment. By implementing this system, both school authorities and parents will be able to collaborate more effectively in monitoring and addressing student behavior.

The rapid development of financial technology has transformed transactional behavior, particularly among Generation Z. Easy access through mobile banking, particularly BCA Mobile, has made financial activities more practical but also poses risks of consumptive behavior due to low financial literacy and self-control. This study aims to analyze the influence of Financial Literacy, Lifestyle, and Locus of control on Financial Behavior, with Financial technology as a moderating variable. The research population consists of Generation Z users of BCA Mobile in Surabaya. A total of 147 respondents were selected using purposive sampling based on specific criteria. Data were collected through questionnaires and analyzed using the Partial Least Squares–Structural Equation Modeling (PLS-SEM) approach. The findings show that Financial Literacy and Locus of control have a significant positive effect on Financial Behavior, while Lifestyle has a significant negative effect. Furthermore, Financial technology is proven to moderate the influence of Financial Literacy and Locus of control on Financial Behavior, but not the relationship between Lifestyle and Financial Behavior.  

The rapid growth of online paylater services has raised concerns about their impact on students’ financial behavior, particularly given the increasing prevalence of consumptive lifestyles and limited financial literacy. This study investigates the influence of Lifestyle (X1) and Financial Literacy (X2) on the use of online paylater systems (Z) and their implications for Spending Behavior (Y) among students of the Faculty of Economics and Business at Dian Nuswantoro University. The study population consisted of 2,100 students from the 2021 and 2022 cohorts, with a sample of 117 respondents determined using the Slovin formula. The sample was selected purposively based on the criteria of being 18–24 years old and active users of paylater services. Primary data were collected through an online questionnaire employing a 5-point Likert scale and analyzed using SmartPLS 3.2 with the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. The results reveal that Lifestyle has a significant positive effect on both Spending Behavior and Paylater use, while Paylater use itself also positively influences Spending Behavior. In contrast, Financial Literacy shows no significant effect and does not mediate the relationships. The novelty of this study lies in integrating Lifestyle, Financial Literacy, Paylater adoption, and Spending Behavior into a single explanatory model, thereby offering new insights into the financial decision-making patterns of Generation Z students in the context of digital financial services.

This study investigates the influence of service quality and product quality on marketing performance, with market penetration and product innovation serving as intervening variables in expedition companies. Guided by the Service-Dominant Logic (SDL) framework, the research underscores the role of value co-creation between companies and customers in driving competitive advantage. Using a quantitative approach, data were collected from employees involved in operational and marketing functions and analyzed through Structural Equation Modeling (SEM). The findings indicate that service quality and product quality do not significantly affect market penetration. Conversely, market penetration positively influences product innovation, which in turn strongly enhances marketing performance. However, when not managed effectively, market penetration can negatively impact marketing performance. These results highlight the need for companies to adopt integrated and innovative strategies that align with customer value creation to achieve sustainable improvements in marketing performance within the expedition industry.

This research explores the impact of stock returns, financial literacy, and risk perception on investment decisions among Generation Z investors who use the Ajaib application in Indonesia. The study is driven by the increasing involvement of young digital investors and the growing importance of financial knowledge, risk awareness, and return expectations in shaping their behavior. A total of 250 respondents were surveyed, and the data were processed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that stock returns (β = 0.436, p < 0.001), financial literacy (β = 0.429, p < 0.001), and risk perception (β = 0.209, p = 0.002) each exert a positive and significant influence on investment decisions. The model explains 68% of the variance in investment decisions (R² = 0.626), confirming the robustness of the proposed framework. These results suggest that Gen Z investors with higher financial literacy, stronger risk awareness, and favorable return expectations are more likely to make confident and deliberate investment choices. The study contributes theoretically to behavioral finance literature and provides practical insights for improving financial literacy programs, enhancing investor education, and designing fintech features that foster trust. The findings can also inform policymakers in creating targeted initiatives to encourage responsible investment behavior among younger generations in Indonesia.