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This research examines the influence of sharia financial literacy on investment decisions in sharia financial products, by considering two moderating variables: perceived quality and religiosity. Quantitative methods were used by collecting data through bold questionnaires via Google Form to 190 respondents who understand sharia financial products. Data analysis was conducted using Structural Equation Modeling based on behavioral finance theory. The research results show that there is a positive influence of sharia financial literacy on investment decisions in sharia financial products. Perceived quality and religiosity do not moderate the influence of financial literacy on investment decisions, but have a direct effect. The implication is that sharia financial literacy influences positive investment decisions. Perceived quality and level of religiosity also influence investment decisions in sharia financial products. These findings are important for the Islamic finance industry in developing effective marketing and service strategies, as well as for educational institutions to increase sharia financial literacy.

Currently, the government is increasingly building PLTMG to fulfill the electricity needs of the society. Beside for fulfill the electricity needs of the Indonesian people, PLTMG also has a negative impact on the society, especially for the community around the PLTMG in the city of Batam. So companies need to conduct studies on environmental impacts, one of which is the impact of the air produced on the surrounding area. The PLTMG industry does not use air pollution control devices, but uses a leanox combustion control system on each gas engine with a chimney outlet that emits SO2 and particulate emissions. The model simulation was carried out using Aermod view software with meteorological data from the affected locations. The results of AERMOD modeling show that the PLTMG industry will have an impact on particulate emissions in the ambient air around the activity location which will spread to the northwest, north, south and east of the activity location. The Aermod Model also shows that current conditions have resulted in dispersion with concentrations below the maximum limit stated in the 2021 Government Regulation. The addition of an emission monitoring system such as CEMS can be used to help monitor the concentration of dispersed emissions. Apart from that, emission control devices such as incinerators or combustion can also be used to reduce the concentration of the emissions used.

The objective of this research is to devise a personalized recommendation system for a freelancing platform to optimize the freelancer project matching process. This enhancement is intended to improve user experience and increase the success rate of projects. The system will recommend projects to freelancers based on their skills and preferences by employing data analysis and machine learning methodologies. The research methodology adheres to the Cross Industry Standard Process for Data Mining (CRISP-DM), incorporating six stages: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The proposed project employs a hybrid recommendation strategy, integrating Content-Based Filtering through KNearest Neighbors (K-NN) and Cosine Similarity, Collaborative Filtering via Singular Value Decomposition (SVD), and recommendations derived from Word2vec. Evaluation metrics such as precision, recall, F1 score, MAP, and MRR are utilized to assess model performance. The results, including precision scores of 0.80 for KNN and 0.728 for SVD, recall scores of 0.60 for KNN and 0.623 for SVD, and F1 scores of 0.69 for KNN and 0.671 for SVD, as well as a MAP of 0.75 and MRR of 0.80 for Word2vec, demonstrate the efficacy of the hybrid recommendation system in delivering accurate and varied project suggestions to freelancers, with a weighted average ensemble learning model emerging as the most effective solution.

This study aims to identify the influence of organizational culture, transformational leadership, and work motivation on the performance improvement of civil servants at the Main Secretariat of the National Civil Service Agency. Data analysis was conducted using Linear Structural Relationship (Lisrel) version 8.80 with Structural Equation Modeling (SEM) method. The choice of using SEM in this research lies in its ability to analyze the pattern of relationships between latent constructs and their indicators, latent constructs with each other, and measurement errors directly. The results of the analysis indicate that organizational culture, transformational leadership, and work motivation significantly contribute to the improvement of civil servants' performance. Managerial implications and recommendations for further research are also discussed.                                                                                                                                                      

Applying ergonomic principles in work tool design for manufacturing industries is a crucial factor in improving productivity while maintaining worker health. This research aims to analyze the effectiveness of adaptive work tool design models based on cognitive and physiological ergonomic principles, identify interaction patterns between workstation design and operational performance, and develop a conceptual framework for integrating ergonomic principles into production cycles. The research method adopts a cognitive-physiological approach with qualitative analysis of human-machine interactions, biomechanical simulations using digital human modeling, and muscle load measurements through electromyography. Implementation was conducted using a participatory ergonomics approach and IMU sensor-based real-time monitoring systems. Results show that using materials with controlled deformation capabilities (15-20%) in work tools reduces muscle work by up to 27%, while adaptive automation system integration improves assembly accuracy by 18%. Workstations with ergonomic adjustments increase assembly speed by an average of 12%, and low-cost ergonomic interventions effectively improve productivity by 11-15% in resource-limited environments. Longitudinal analysis reveals that evidence-based ergonomic investments yield a 230% ROI through increased productivity, reduced injury compensation costs, and decreased employee turnover. IMU-based posture monitoring systems integrated with adaptive feedback loops reduced musculoskeletal disorder incidents by up to 41%. In conclusion, ergonomic optimization based on cognitive-physiological principles creates synergy between production efficiency and worker well-being, making it an essential component in achieving sustainable productivity.

Healthcare waste (HCW) is a significant environmental and public health concern due to its hazardous nature, particularly the presence of emerging pollutants such as pharmaceuticals, heavy metals, and pathogens. The improper disposal and management of healthcare waste contribute to pollution and pose long-term risks to both human health and ecosystems. This study examines the toxicity risks associated with HCW in areas near healthcare facilities with inadequate waste management practices, showing an increase in toxicity risks by 22% to 30%. The research develops a cumulative risk assessment model that integrates human exposure with ecological risks, considering both direct and synergistic effects of pollutants. The model incorporates various components, including pollutant analysis, bioaccumulation mapping, and long-term exposure modeling, to assess the environmental and health risks of HCW. The findings highlight that inadequate waste management leads to significant pollutant accumulation in local ecosystems, with direct implications for biodiversity and human health. Additionally, the study emphasizes the benefits of applying the One-Health approach, which considers the interconnectedness of human, animal, and environmental health, offering a more integrated understanding of the risks posed by HCW pollutants. The research advocates for the incorporation of the One-Health model in healthcare waste management policies to mitigate risks and improve sustainability. Future studies should refine the cumulative risk assessment model and expand it to encompass other environmental waste sources, providing a more comprehensive understanding of pollutant impacts and advancing mitigation strategies.

The rapid advancement of deep learning technologies has significantly transformed healthcare analytics, particularly in medical data prediction and classification. This study proposes a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) framework for multi-modal healthcare data analysis, integrating medical imaging, structured electronic health records (EHRs), and IoT-generated time-series physiological signals. The proposed architecture combines spatial feature extraction through CNN with temporal dependency modeling via LSTM to enhance predictive accuracy and clinical decision support. A quantitative experimental design was employed, utilizing multi-source healthcare datasets that underwent preprocessing, normalization, and feature engineering prior to model training. The performance of the hybrid model was evaluated using Accuracy, Precision, Recall, F1-Score, AUC-ROC, and Mean Absolute Error (MAE), and compared with conventional machine learning models and standalone deep learning architectures. Experimental results demonstrate that the proposed CNN–LSTM model achieves superior performance, with improved classification accuracy and reduced prediction error, while maintaining strong generalization capability. The findings indicate that integrating spatial and temporal feature learning significantly enhances disease detection, risk stratification, and personalized treatment planning. This approach supports the development of intelligent clinical decision support systems and scalable smart healthcare environments. The proposed framework offers a reliable and efficient solution for advanced healthcare analytics in IoT-enabled systems.

This study explores the application of green hydrogen technology for industrial decarbonization, focusing on its techno-economic and environmental feasibility. A quantitative approach was used, incorporating system modeling of a solar-based hydrogen production system combined with electrolyzers. The techno-economic assessment involved calculating the Levelized Cost of Hydrogen (LCOH), estimating capital and operational expenditures (CAPEX and OPEX), and evaluating the system's energy efficiency and hydrogen output. The environmental impact was analyzed using Life Cycle Assessment (LCA), comparing the carbon footprint of green hydrogen with fossil-based hydrogen. The results reveal that green hydrogen can reduce carbon emissions by up to 60% compared to fossil hydrogen, primarily due to the use of renewable energy for production. Additionally, the study found significant improvements in energy efficiency as electrolyzer performance and solar capacity increased. The LCOH is expected to decrease steadily as solar panel and electrolyzer prices continue to fall, enhancing the competitiveness of green hydrogen in the energy market. The findings also highlight the potential for heavy industries, such as cement and steel production, to transition from fossil fuels to green hydrogen, contributing to a cleaner industrial energy mix. This transition presents both environmental and economic benefits, with long-term savings from reduced fossil fuel dependency and lower production costs.

A study was conducted to identify the relationship between height and weight. A researcher claimed that on average, when height increases, weight increases. This is called the Benn parameter. Weight can be adjusted for height using the Benn parameter (kg/mB), where B is the power that minimizes the correlation with height. To investigate how the Benn parameter changes across age and differs between genders. Using linear regression. Multilevel modeling was used to develop a history showing how Benn's parameters change with age from childhood through mid-adulthood and into older age. The data used information from a sample of 40 adults and 40 children under five. Height was measured in centimeters, weight was measured in kilograms. At alpha equal to 0.05 (α=0.05), the hypothesis is that there is a relationship between height and weight. This is the data, which is height and weight. And here is the hypothesis.  (Hnull) there is no relationship between height and weight, ρ equals 0. And ,, there is a relationship between height and weight, ρ does not equal 0. And we test to claim that .

The improvement of performance for Micro and Small Enterprises (MSEs) is a must to achieve business performance growth. To achieve business performance successfully, the MSEs partly need to investigate factors that influence it. This study aims to examine whether or not financial access, digitalization adoption, product innovation, and market orientation influence MSEs' business performance. The source of data was obtained by distributing questionnaires to 135 women who engaged in MSEs in Belitung Regency as one of the main locations of women MSEs in Indonesia. These data were then analyzed statistically by applying the Partial Least Square-Structural Equation Modeling (PLS-SEM. The main findings of this research are: (i) the path coefficient of the variables financial access, product innovation, and market orientation has a positive and significant effect, (ii) the path coefficient of digitalization adoption has a positive but not significant effect on MSE business performance. The results of this research provide input for women's MSEs in Belitung Regency to be able to improve their market orientation to overcome marketing obstacles that may be experienced and to improve the business performance of women's MSEs in Belitung Regency.

This research aims to analyze the effect of using Web Wordwall in training students' computational thinking skills in mathematics learning with a qualitative approach. The research subject is the Director General of Teachers and Education Personnel, while the object is education that is liberating and pro-student. Data obtained from online and offline information sources is recorded in a structured manner, then analyzed to be synthesized into a systematic conceptual framework. Conclusions are drawn by taking the essence of the conceptual framework that can answer the research questions posed. The research method used is a case study with a focus on participatory observation, in-depth interviews and document analysis. Data was collected through literature study and analysis of learning materials. Data analysis was carried out using an inductive approach, by looking for patterns of findings and main concepts from the data collected.

This research aims to analyze the effect of using Web Wordwall in training students' computational thinking skills in mathematics learning with a qualitative approach. The research subject is the Director General of Teachers and Education Personnel, while the object is education that is liberating and pro-student. Data obtained from online and offline information sources is recorded in a structured manner, then analyzed to be synthesized into a systematic conceptual framework. Conclusions are drawn by taking the essence of the conceptual framework that can answer the research questions posed. The research method used is a case study with a focus on participatory observation, in-depth interviews and document analysis. Data was collected through literature study and analysis of learning materials. Data analysis was carried out using an inductive approach, by looking for patterns of findings and main concepts from the data collected.

This research examines employees of Perum Jasa Tirta I Semarang. This research aims to determine the influence of cyberloafing and leader member exchange on innovative work behavior through employee performance. The research method in this research is a quantitative research method. The population in this study was all employees with a total of 10 employees who worked at Perum Jasa Tirta I Semarang, while the sample in this study was 180 respondents. Determining the sample size used a non-probability sampling technique because the population was relatively small, so the technique taken was saturated sampling (census). Data analysis in this research used the SmartPLS version 3 program. The data analysis technique used was the Structural Equation Modeling (SEM) equation model. The results of the analysis and discussion show that the perceived quality variable influences Cyberloafing, influences Innovative Work Behavior, Leader Member Exchange influences Innovative Work Behavior, Cyberloafing influences Employee Performance, Leader Member Exchange influences Employee Performance, Employee Performance influences Innovative Work Behavior, Cyberloafing influences on Innovative Work Behavior is partially mediated by Employee Performance, and Leader Member Exchange influences Innovative Work Behavior of Perum Jasa Tirta I Semarang employees which is partially mediated by Employee Performance.

This research was motivated by the phenomenon of guest repurchase intention allegedly due to the quality of service, brand preferences, and prices at Warung Nasi Kelok Desa Talogondan. This study aims to analyze the role of satisfaction in mediating the effect of service quality, brand preference, and price on repurchase intention in Warung Nasi Kelok Talogon Village and Padang Pariaman Regency. This type of research is quantitative research with a causal associative approach. The population in this study is rice stall consumers who have visited Warung Nasi Kelok Talogon Village and Padang Pariaman Regency with a sample of 222 respondents. The research instrument used in this study was a questionnaire (questionnaire) arranged according to the Likert scale. Instrument trials use validity tests, reliability tests. Data analysis technique using Structural Equation Modeling with Partial Least Square (SEM-PLS). The result of the study is that there is a positive and significant influence between service quality variables and consumer satisfaction variables. There is a positive and significant influence between brand preference variables and consumer satisfaction variables. There is a positive and significant influence between price variables and consumer satisfaction variables. There is a positive and significant influence between the consumer satisfaction variable and the repurchase intention variable. There is an influence of customer satisfaction as a positive and significant mediating variable between service quality and repurchase intention. There is an influence of consumer satisfaction as a positive and significant mediating variable between brand preference for repurchase intention and path coefficient. There is an influence of consumer satisfaction as a positive and significant mediating variable between price and repurchase intention and path coefficient.

Objective – This research clarifies the factors that encourage creative economic inclusiveness for MSME actors by examining the effect of optimizing MSME empowerment, the role of digital technology literacy and ease of access for MSME actors. This research also examines analysis direct influence optimization empowerment on digital technology literacy and ease of access, the influence of digital technology literacy on ease of access and the mediating role of digital technology literacy and ease of access. Design/methodology/pe approach – Data was taken from an online questionnaire of respondents, namely MSME actors in Purwakarta Regency. Partial least squares structural equation modeling and mediation analysis using the bootstrap method. Findings – Optimizing empowerment and ease of access has a significant direct impact on the inclusiveness of the creative economy. Both optimizing empowerment and digital technology literacy have a direct, positive and significant influence on ease of access. Optimizing empowerment has a positive effect on digital technology literacy. Mediation analysis revealed that ease of access was unable to mediate the influence between optimizing empowerment and inclusiveness of the creative economy and between digital technology literacy and inclusiveness of the creative economy. Research limitations/implications – This research focuses on three factors that encourage creative economic inclusiveness of MSME actors in Purwakarta Regency. Originality/value – This study offers new insights into the factors that encourage the inclusiveness of the creative economy of MSME players. These findings reveal the importance of optimizing MSME empowerment and encouraging digital technology literacy for creative economic inclusivity among MSME players.

The development of technology is something that cannot be separated from humans at this time, it is based on technology that is increasingly growing. But on the problems faced in the search for facilities and services private tutoring is still an information manual so that it is difficult for the community to find facilities and services for private tutoring especially in non-academic fields. Then it needs to be specifically designed as a search system for facilities and private tutoring services through web-based media. Thus the community is not difficult to find a place or non-academic field private tutoring services because in this system there is a latitude of maps that will show the location and there are display fees and online payments via a bank account. In designing the system the author observes the company and the community as well as a bibliography that aims to be a benchmark. The author uses the Business Model Canvas (BMC) method with the support of system requirements elicitation, as well as modeling the Unified Modeling Language (UML) system to visually implement the Hypertext Preprocessor (PHP) program language with the MySQL database as a database server. With the design of a search system for facilities and private tutoring services, it can make it easier for people to find effective and efficient facilities or services in non-academic fields.

Energy efficiency is a critical concern in wireless sensor networks (WSNs) due to the limited power resources available in sensor nodes. Prolonging network lifespan while ensuring reliable data transmission is essential for successful deployment in various applications, such as environmental monitoring, military operations, and industrial automation. This paper presents a mathematical model designed to optimize energy consumption across various nodes in WSNs. By implementing simulations and analyzing data from these models, the study demonstrates significant improvements in extending network lifespan while maintaining reliable data throughput. The findings contribute valuable insights into energy management for large-scale sensor deployments.

Power systems are critical infrastructure that face significant challenges due to increasing demand and inherent complexity. Predicting failures in power systems is crucial for enhancing grid reliability, minimizing downtime, and optimizing maintenance processes. This study evaluates various deep learning models, specifically convolutional neural networks (CNN), recurrent neural networks (RNN), and transformer models, for predicting power system failures. By analyzing these models’ performance metrics on historical power grid data, the study provides insights into the strengths and weaknesses of each approach. The findings contribute to the development of more robust predictive models for power system reliability.

Software Modeling is a scientific discipline for studying forms of software modeling that are used as part of the software development stages in a structured and object-oriented manner. This software engineering modeling is presented in Requirements Analysis and described using the Unified Modeling Language (UML) method. UML (Unified Modeling Language) is a visual modeling method used as a means of designing object-oriented systems. UML diagrams that are often used are Use Case Diagrams, Activity Diagrams, Sequence Diagrams, Class Diagrams, Statemachine Diagrams and Component Diagrams. There are several applications that support UML creation, one of which is Draw.io. Draw.io is a website specifically designed for depicting UML diagrams online. It has a very responsive display and is integrated with Google's file storage service, namely Google Drive, so draw.io is an alternative for creating UML diagrams in a shorter time. On this basis, in the Community Service (PkM) program activities on this occasion, UML creation activities were carried out using the draw.io application and assistance in using UML in analyzing needs is one of the right solutions for solving problems in order to expand knowledge, simplify and improve the quality of education. and will overcome problems, time and socio-economic

This research examines the employees of UKM Batik Lasem Sekar Mulyo, Rembang. This research aims to determine the influence of the role of core self-evaluation and empowering leadership on employee creativity through knowledge sharing. The research method in this research is a quantitative research method. The population in this study were all employees with a total of 95 employees who worked at UKM Batik Lasem Sekar Mulyo, Rembang, while the sample in this study was 95 respondents. Determining the sample size used a non-probability sampling technique because the population was relatively small, so the technique taken was saturated sampling (census). Data analysis in this research used the SmartPLS version 3 program. The data analysis technique used was the Structural Equation Modeling (SEM) equation model. The results of the analysis and discussion show that the quality perception variable influences Core Self-Evaluation and influences Employee Creativity, Empowering Leadership influences Employee Creativity, Core Self-Evaluation influences Knowledge Sharing, Empowering Leadership influences Knowledge Sharing, Knowledge sharing influences Employee Creativity, Core Self-Evaluation has an effect on Employee Creativity, partially mediated by Knowledge sharing, and Empowering Leadership has an effect on Employee Creativity in Employees of UKM Batik Lasem Sekar Mulyo, Rembang, which is partially mediated by Knowledge sharing.