Publication Search

This study aims to analyze the effect of stress on emotional eating among whitewater rafting athletes in East Java. Stress, caused by the demands of competition and intensive training, often triggers emotional eating behavior, which involves overeating as a response to negative emotions. This research employs a quantitative approach with a cross-sectional design, involving 68 athletes from the East Java Whitewater Rafting Federation. Data were collected through an online questionnaire using a stress scale and an emotional eating scale. The results show that the majority of athletes (70.6%) experience high levels of stress, and most (39.7%) exhibit moderate levels of emotional eating. Regression analysis indicates a significant positive relationship between stress and emotional eating (p < 0.05), with stress contributing 9.2% to the variation in emotional eating. This study highlights the importance of stress management to prevent emotional eating, which can affect athletes' health and performance. Recommended stress management strategies include emotional regulation training and providing psychological counseling services.

The success of a school is greatly influenced by the role of the principal's leadership in managing educational resources and guiding teachers and school staff towards achieving optimal educational goals. Principal leadership includes the ability to plan, organize, motivate, and direct all potentials in the school to achieve quality education. The principal as a leader is not only tasked with administrative aspects, but also plays an important role in creating a conducive learning climate, supporting innovation in teaching, and improving teacher competence. This article discusses the concept, role, and challenges faced by principals in implementing leadership in schools, as well as strategies that can be applied to improve school performance. With effective leadership, principals are able to bring positive changes to the progress of education in their schools.

This study presents a Quantum Machine Learning (QML) architecture for perfectly classifying the Iris flower dataset. The research addresses improving classification accuracy using quantum models in machine-learning tasks. The objective is to demonstrate the effectiveness of QML approaches, specifically the Variational Quantum Circuit (VQC), Quantum Neural Network (QNN), and Quantum Support Vector Machine (QSVM), in achieving high performance on the Iris dataset. The proposed methods result in perfect classification, with all models attaining accuracy, precision, recall, and an F1-score of 1.00. The main finding is that the QML architecture successfully achieves flawless classification, contributing significantly to the field. These results underscore the potential of QML in solving complex classification problems and highlight its promise for future applications across various domains. The study concludes that QML techniques can offer transformative solutions in machine learning tasks, particularly those leveraging VQC, QNN, and QSVM.

This study explores the integration of artificial intelligence (AI) in education, particularly in supporting personalized learning. AI presents new opportunities through adaptive learning platforms, virtual tutors, and intelligent assessment systems that have the potential to revolutionize teaching and learning methods. By conducting in-depth data analysis, AI can identify student performance patterns and provide tailored recommendations, enabling educators to deliver more targeted interventions. Furthermore, personalized learning plays a crucial role in enhancing student motivation and engagement by customizing learning experiences to meet individual needs and learning styles. This study aims to implement personalized learning strategies in educational settings and offers insights into best practices for their integration. It also examines their impact on student engagement and academic achievement. The findings highlight the importance of personalized learning in fostering an inclusive and effective educational environment. By leveraging AI, educators can optimize learning, empower students, and address achievement gaps. This study provides practical recommendations for educators and policymakers to implement AI-based learning strategies effectively.

The purpose of this study is to identify and analyze trends in the most relevant scientific work being conducted on the topic of foreign direct investment. In addition, an exploration of this topic is carried out in a way that allows the expansion of empirical and conceptual knowledge. A bibliometric analysis was carried out using the Bibliometrix and Biblioshiny software packages on academic articles indexed in the Scopus database. Search criteria were applied, initially resulting in a total of 8,115 articles in the period 2013–2023. Finally, after applying exclusion criteria, a total of 1361 interesting and valid articles were obtained. The results of this study present important relevant topics in the topic of foreign direct investment, provide a quantitative analysis that provides an overview of the research topic on foreign direct investment presenting tables, graphs and maps, and identify key performance indicators for article production and citations. The findings of this study are that articles centered on this concept have gained significant traction, forming the basis for efforts aimed at improving the concept of sustainable investment in the context of the various variables that influence it.

This study aims to analyze and describe the implementation of performance management at CV Nuansa Warna Tanjungpinang Branch. The type of research used is descriptive research with a qualitative approach. Data collection techniques are carried out through observation and in-depth interviews. The sample used in this research is a purposive sample with the informant, SPV, Mr. Riyanto Setiyawan . Data analysis was carried out using triangulation through the steps of reduction, presentation and conclusion. The results of this study found that the implementation of performance at CV Nuansa Warna Tanjungpinang Branch has been implemented quite well. This includes the stages of planning, monitoring, evaluation, and follow-up. However, there are some obstacles, such as CV Nuansa Warna facing unique challenges in implementing performance management, including limited resources, and structured formal systems. Implemented strategies include technical training, KPI implementation, and CRM system development. This study concludes that effective performance management can improve productivity, service quality, and competitiveness of the company, although it requires continuous improvement to face the existing challenges.

This study aims to determine how factors like profitability, capital structure, cash management, and company size affect the financial performance of manufacturing companies in the food and beverage subsector that are listed on the Indonesia Stock Exchange (IDX) between 2019 and 2023. Analysis is essential. The Smart PLS technique and secondary data from the financial statements of seven companies selected through purposive selection are used in the quantitative methodology of this study. Financial performance is evaluated using Tobin's Q and EPS, and the independent factors that are looked at include ROE, DER, quick ratio, current ratio, and total assets. The study's findings indicate that while business size has no discernible effect on financial performance, return on investment (ROE) has a strong positive influence. Nevertheless, capital structure (DER) has a negative impact on financial performance while company size has a positive one; neither effect is statistically significant. Additionally, cash management has a little negative impact on financial success, but business size has a positive and significant influence. However, there is a small but favorable correlation between firm size and financial performance.

This research seeks to explore how Part-Time Work and Time Management influence students' academic performance. A quantitative methodology was employed to investigate the relationship between the independent variables, part-time work and time management, and the dependent variable, academic achievement. The study focused on students from Universitas PGRI Wiranegara during the 2021–2024 period who are actively engaged in part-time work. The sample was selected using a probability sampling method, ensuring every student in the population had an equal chance of inclusion. Data collection was conducted through a questionnaire, which underwent validity and reliability testing.  The findings revealed that part-time work significantly affects academic performance, with both positive and negative outcomes, depending on how well students manage their time. Additionally, effective time management proved to be a crucial factor in enhancing academic performance, even when students juggle their time between work and study. Further analysis indicated that both variables collectively have a meaningful impact on academic achievement. This research underscores the critical role of time management skills for students balancing work and study and highlights the importance of institutional support in helping students maintain this balance. 

Graphene is a two-dimensional lattice made of a single carbon atom and has extraordinary mechanical, electrical and thermal properties. These properties make it a very important material for a variety of applications, including energy management and electronics. This research adopts a systematic literature review approach to evaluate the role of graphene in improving battery performance and environmental sustainability. The results show that graphene significantly improves the performance of lithium-ion and lithium-sulfur batteries as well as sodium and magnesium-based batteries. In addition, graphene also has great potential for environmental applications such as water purification and pollutant adsorption. However, challenges such as production costs, toxicity, and scalability still need to be overcome for wider adoption.

The research analyzes to understand the influence of financial intelligence, financial literacy, business innovation and risk management on the financial performance of MSMEs in Surabaya. MSMEs are an important sector in the Indonesian economy, but many MSME actors still experience resistance, especially in terms of financial management. Data was collected through questionnaires from 60 respondents who are MSME actors in Surabaya, using a quantitative approach.  The research results show that the majority of MSME players have limited understanding of financial management, including financial recording and reporting. Even though financial literacy and financial intelligence are recognized as important, the results of statistical analysis show that these two variables do not have a significant influence on the financial performance of MSMEs partially. However, training and education related to financial literacy is still needed because it has great potential to increase the financial resilience of MSMEs in the long term. This research also highlights that business innovation and the application of risk management can help MSMEs face market dynamics and economic challenges. Overall, this research provides an illustration that MSMEs need additional support, both through training and the use of technology, to be able to increase their competitiveness and business desires.

This study aims to develop a color detection application based on microcontrollers as an intelligent solution for visual identification. The application is designed to accurately detect and identify color spectrums using a color sensor integrated with a microcontroller. A project management approach in informatics engineering was applied to ensure the effective design and implementation of the system. A qualitative descriptive method was employed in this research, including data collection through device testing and interviews with potential users. The results demonstrate that the application can recognize colors with high accuracy, making it applicable across various fields such as industry, education, and assistive technology. Supporting factors for the application's success include hardware and software compatibility, while the main challenges involve the impact of light intensity on sensor performance. Further development is recommended to enhance the application’s performance in more diverse operational environments.

Organizational structure plays a crucial role in enhancing the operational effectiveness of an organization or company. In the context of a five-star hotel, a clear and appropriate organizational structure helps improve coordination between departments, clarifies employees' roles and responsibilities, and optimizes operational processes. This study aims to determine the extent of the influence of organizational structure on operational effectiveness in five-star hotels. The research method employed is quantitative, using simple linear regression analysis. The findings indicate that organizational structure has a significant impact on the operational effectiveness of hotel employees. Specifically, the organizational structure, along with the work environment and shared motivation, contributes to 73% of the impact on employee performance.

Educational supervision is a training process that aims to improve the quality of learning and teacher performance. Implementation of supervision requires certain techniques that are tailored to the needs, conditions, and characteristics of the school. There are three main categories in supervision techniques, namely individual techniques, group techniques, and a combination of both. Individual techniques include classroom observation, personal conversations, and class visits, which aim to provide direct guidance to teachers. This technique is effective in identifying specific problems faced by teachers and providing solutions directly. Supervision groups include workshops, discussion groups, and joint training, which aim to improve teacher competence through collaboration and sharing experiences. This technique encourages innovation in teaching and creates a culture of learning among educators. In addition, a combination of individual and group techniques, such as mutual observation or project-based training, can provide more comprehensive results. The application of supervision techniques must be carried out in a planned and sustainable manner with the principles of involvement, openness, and training. Effective supervision also requires technological support to facilitate data collection and evaluation, such as using learning videos or analytical software.

The A* Algorithm is a path-finding algorithm that primarily uses weighted graphs and focuses on the heuristic values of nodes. However, while effective in generating a near-optimal path in a static environment, the traditional algorithm faces limitations in navigating dynamic environments, often resulting in collisions due to its inability to recognize dynamic and moving obstacles. This limitation makes it inefficient especially in complex environments with real-world scenarios. To address these limitations, an Enhanced A* Algorithm is proposed. This algorithm utilizes Navigation Mesh data structure to generate a more optimal route with local path planning and to dynamically adjust the parameters in two-dimensional non-grid environments. The performance of the algorithms was evaluated using 12 benchmarks, each corresponding to a distinct test case and levels of complexity. Then, in terms of dynamic obstacle avoidance, a comparison between the Enhanced A* Algorithm and the traditional algorithm was conducted. Statistical analyses were also performed to assess the consistency and validity of the findings. The results demonstrated that the Enhanced A* Algorithm successfully avoided all dynamic obstacles and moving objects encountered along the path in all distinct test cases. In contrast to the traditional algorithm, which achieved an average obstacle avoidance rate of 8.33%, the enhanced algorithm consistently demonstrated a 100% average obstacle avoidance rate. The enhanced algorithm outperformed the traditional A* algorithm in generating a path in a complex environment by exhibiting optimal dynamic obstacle recognition and avoidance. The Enhanced A* Algorithm is subsequently applied to autonomous vehicle parking, following standard parking restriction laws.

Power system protection plays a crucial role in maintaining the reliability and security of electricity distribution. This study discusses the analysis of coordination between overcurrent relays (OCR) and ground fault relays (GFR) on the Miwon Substation power line. The study aims to determine the optimal setting values ​​for OCR and GFR, so that they can detect and disconnect short circuit faults quickly and accurately. The approach used includes theoretical calculations and simulations to evaluate relay performance under various fault conditions. The results of the study reveal that with appropriate settings, the relay can operate selectively and efficiently, reducing the impact of disturbances and maintaining the stability of the power system.

The Cuckoo Search Algorithm (CSA), while effective in solving complex optimization problems, faces limitations in random population initialization and reliance on fixed parameters. Random initialization of the population often results in clustered solutions, resulting in uneven exploration of the search space and hindering effective global optimization. Furthermore, the use of fixed values for discovery rate and step size creates a trade-off between solution accuracy and convergence speed. To address these limitations, an Enhanced Cuckoo Search Algorithm (ECSA) is proposed. This algorithm utilizes the Sobol Sequence to generate a more uniformly distributed initial population and incorporates Cosine Annealing with Warm Restarts to dynamically adjust the parameters. The performance of the algorithms was evaluated on 13 benchmark functions (7 unimodal, 6 multimodal). Statistical analyses were conducted to determine the significance and consistency of the results. The ECSA outperforms the CSA in 11 out of 13 benchmark functions with a mean fitness improvement of 30% across all functions, achieving 35% for unimodal functions and 24% for multimodal functions. The enhanced algorithm demonstrated increased convergence efficiency, indicating its superiority to the CSA in solving a variety of optimization problems. The ECSA is subsequently applied to optimize earthquake evacuation space allocation in Intramuros, Manila.

Signature verification is crucial for confirming the authenticity of identities in both administrative and financial transactions, where signature forgery can lead to significant security risks. The Harris Corner Detector Algorithm is a widely used method for feature extraction in image processing; its application spans various domains, such as detection of signature forgery. While effective in identifying key features, noise significantly affects performance, especially with impulse noise like salt-and-pepper noise commonly found in signature images. To solve this problem, this study enhances the Harris Corner Detector Algorithm by applying a median filter before gradient calculation. This method removes noise without sacrificing the integrity of key features important in signature forgery detection. The study evaluates the original and the enhanced algorithm using standard image quality metrics. Peak Signal-to-Noise Ratio (PSNR) surged from an average of 13.6 dB to 43.28 dB, the Structural Similarity Index (SSIM) improved significantly from 78% to 94%, and the Mean Squared Error (MSE) dropped substantially from 16.74 to 3.84. These advancements resulted in a more reliable algorithm, exhibiting excellent resistance to noise while maintaining image structure, making the enhanced algorithm highly effective for accurate signature forgery detection.

This research aims to evaluate the impact of time management and activeness in organizations on the academic achievement of Economics Education students at PGRI Wiranegara University. Using a quantitative approach, data was collected through questionnaires given to 60 students and analyzed using the multiple linear regression method. The results of the analysis show that there is a significant positive relationship between good time management and active participation in organizations on student academic achievement. These findings emphasize the importance of personal discipline and extracurricular activities in supporting academic success.

Human resources that are kinejaa person includes the mind and physical power that become an important element in an organization. In other words, the success of an organization depens largely on the performance of its employees, but in reality in schools employee performance is stil relatively low, this can be seen from the less effective working hours (not on time), and responsibility for tasks that are still lacking. Therefore, the principal and researchers are trying to find out what most affects the motivation and discipline of employees, so that employees performance problems that often occurin the organization or institution in the school can be solved, if it can not be resolved at least thereis an improvement in performance. This study aims to find out the influence of improving human resource performance through motivation and discipline in the work environment and to find out whether there are inhibitory factors and support the improvement of human resource performance through motivation and discipline in the work environment. Respondents in this study were selected using the proposiv sample method by distributing questionnaires to as many as 53 employees. It can be explained that the positive is claused by the work environment, discipline and work motivation. There is a significant positive influence of the work environment, discipline, and work motivation together on the performance of Human Resources.

This study aims to identify the influence of work facilities, workspace layout, and team building on employee performance. Using descriptive quantitative research methods, this study involved employees from two companies: PT Borobudur, Prambanan, and Ratu Boko Temple Tourism Park and PT Naisha Inspirasi Muslimah Yogyakarta. The sample consisted of 80 people, with 40 employees from each company. Data were collected through questionnaires distributed in the form of a paper survey. Analyses were conducted using Statistical Product and Service Solutions (SPSS) version 23.0 to test validity, reliability, multicollinearity, basic assumptions, and multiple linear regression. The research findings show that (1) work facilities have a positive and significant effect on employee performance, (2) work layout has a negative and insignificant effect, (3) team building has a positive and significant effect, and (4) the three variables simultaneously have a significant effect on employee performance.