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This research explores the development of a participatory governance model for community based waste management systems, aiming to enhance both legal compliance and public social welfare outcomes. Community based waste management (CBWM) plays a critical role in addressing environmental and health challenges, yet its success is often hindered by weak governance structures, limited community involvement, and insufficient regulatory frameworks. The study introduces a governance model that integrates local community participation into decision making processes, encouraging ownership and responsibility among residents. The primary goal is to improve compliance with environmental regulations while promoting social welfare by fostering better public health and community cohesion. A review of literature highlights key theories of participatory governance, focusing on its ability to enhance legal adherence and increase social equity. Previous studies on CBWM demonstrate the potential of community involvement in overcoming barriers to legal compliance, such as weak enforcement and fragmented governance. However, challenges like inadequate infrastructure, socio economic factors, and cultural habits still impede full participation and compliance. The study utilizes a mixed methods approach, including stakeholder analysis, participatory workshops, and regulatory compliance assessments, to evaluate the effectiveness of the model. The results show that communities involved in participatory governance exhibit higher compliance with waste management laws, improved sanitation, and healthier living conditions. Furthermore, the model fosters social capital and community empowerment, contributing to long term sustainability. In comparison to centralized waste management systems, the participatory approach is found to be more adaptable, accountable, and socially accepted. While the model presents several benefits, challenges such as infrastructure limitations and cultural barriers remain. Future research should further investigate how to address these challenges, particularly through technological integration and cross sector collaborations, to ensure the scalability and sustainability of the participatory governance model.

This study investigates the role of knowledge management (KM) capabilities in enhancing managerial decision-making within organizational settings. Using a systematic review approach, ten peer-reviewed journals published between 2019 and 2024 were analyzed to identify key themes, patterns, and empirical findings related to knowledge management implementation and its influence on decision-making processes. The review reveals that strong knowledge management capabilities particularly in knowledge acquisition, storage, sharing, and utilization significantly contribute to improving the accuracy, speed, and strategic quality of managerial decisions. The findings also show that organizations with well-developed knowledge management infrastructures, supported by digital technologies and a culture of knowledge sharing, demonstrate greater adaptability, innovation, and problem-solving effectiveness. This study concludes that knowledge management capabilities are essential for strengthening evidence-based decision-making and enhancing organizational competitiveness. Implications for managers emphasize the need to invest in knowledge management systems and foster collaborative knowledge practices. Suggestions for future research include expanding the scope to cross-industry comparisons and integrating knowledge management with emerging technologies such as AI-based decision support systems..

This study aims to evaluate the financial recording system implemented by Micro, Small, and Medium Enterprises (MSMEs) in the culinary sector, and analyze its impact on business performance. MSMEs are a very dynamic sector and contribute significantly to the national economy, but many of them do not yet have an adequate financial recording system. Good financial recording is key in business decision making, budget planning, and profitability assessment. The population in this study were 370 culinary MSMEs in Harjosari I Village. The research sample was taken at 20%, namely 74 respondents. The study used a quantitative approach with a survey method through the distribution of questionnaires to 74 culinary MSMEs in Harjosari I Village, Medan Amplas. Data analysis was carried out using simple linear regression to see the relationship between the quality of the financial recording system as an independent variable and business performance as a dependent variable. The results showed that the better the financial recording system, the better the business performance, this can be shown by the regression equation, Y = 1.395 + 0.308 + e. The research results indicate that improving accounting literacy and the use of digital technologies, such as MSME bookkeeping applications, are essential. The involvement of local governments and financial institutions is crucial in educating and facilitating digital-based bookkeeping systems for culinary MSMEs to enhance their competitiveness and business sustainability.

This study aims to describe the role of the principal in improving the quality of education in Qismul Ali Al-Jam’Iyatul Washliyah. This study uses a qualitative approach with descriptive methods. Data sources were taken by purposive sampling and snowball sampling. Data collection was carried out through observation, interviews, and documentation studies. Data analysis was carried out using data reduction techniques, data presentation, and drawing conclusions. As for checking the validity of the data, namely by using triangulation of methods and sources. The results of the study indicate that there are 2 aspects of improvement carried out by the principal, namely: a) the role of the principal as a leader, namely by guiding and directing educators in creating interesting learning methods, then the principal tries to establish communication with his subordinates through greetings and listening directly to input from teachers and school employees regarding the problems they are facing, in decision making the principal applies a democratic and open system through deliberation and joint decisions, then the principal also becomes a good role model through diligent and disciplined behavior in working. To determine the program's achievement, the principal conducts regular supervision and evaluation of the learning process and learning materials, utilizing the results of this supervision to further improve learning activities through coaching and direction from the principal. b) The principal's role as a manager involves managing the school, starting with planning the school's work program at the beginning of the school year during work meetings involving teaching and administrative staff. The principal also involves teaching and administrative staff in various training activities to support competency. The principal also regularly maintains facilities and infrastructure. The findings of this study indicate that the principal has realized improvements in the quality of education at Qismul Ali Al-Jam'Iyatul Washliyah by implementing several improvement measures.

A single paragraph, maximum 250 words. Abstract content must contain (1) an overview of the object This study aims to identify and analyze various behavioral finance factors that influence investment decisions, especially among the younger generation and individuals who invest. The method used is the Systematic Literature Review (SLR) with data sources from Google Scholar in the period 2020 to 2024. The focus of this study is on factors such as regret aversion, mental accounting, illusion of control, and overconfidence. The results of research from various journals show that these psychological factors have a significant, although varying, influence on investment decisions. Some studies confirm the strong influence of these factors, while others provide different results. Therefore, it is very important for investors and policy makers to understand these dynamics in order to improve the quality of investment decision making.

This study examines the role of management accounting in supporting strategic decision-making in manufacturing companies in Indonesia. With a literature study approach and Systematic Literature Review (SLR), this study analyzes various secondary sources from 2020 to 2025. The results of the study indicate that management accounting functions as the main tool in planning, cost control, performance evaluation, and strategic decision-making. The information generated such as cost data, budgets, and performance reports greatly assists management in choosing effective and responsive strategic alternatives to market dynamics. Case studies of several large manufacturing companies show that the implementation of a good management accounting system can improve operational efficiency, optimize resource allocation, and reduce the risk of failure in decision-making. Management accounting also plays a role in supporting investment and product development to maintain competitiveness in the global market. In conclusion, management accounting is a crucial element that strengthens strategic decision-making, so that manufacturing companies can grow and be sustainable in a competitive business environment.

This study aims to determine the description of job satisfaction in terms of leadership style. The research informants were 5 ASN from the Regional Civil Service Agency. This type of research is a qualitative study with a phenomenological approach. The data collection technique in this study used a semi-structured interview method and previous study literature. The results of the study found a democratic leadership style that could make some ASN feel satisfied. There are several factors that influence it, such as decision making. Therefore, an adaptive, empathetic leadership style that involves employees plays an important role in increasing job satisfaction.

The integration of solar powered IoT irrigation systems in precision agriculture offers a sustainable solution to address water scarcity and enhance crop productivity. By leveraging real time data from soil sensors, weather APIs, and machine learning algorithms, these systems optimize irrigation schedules and improve water use efficiency. This research explores the potential of integrating renewable energy sources, such as solar power, with edge computing in smart irrigation systems to promote sustainable agricultural practices. The study aims to evaluate the performance of the proposed system in terms of water savings, crop yield, energy efficiency, and adaptability to varying climate conditions. Literature Review: Previous studies highlight the importance of smart irrigation systems in reducing water waste and improving crop yield through real time monitoring and automated decision making. However, existing systems often lack the integration of renewable energy and edge computing, which are critical for ensuring sustainability and operational efficiency in rural agricultural settings. The combination of renewable energy with IoT devices offers a promising solution to reduce energy costs and carbon emissions, while edge computing enhances real time data processing, ensuring prompt and accurate irrigation adjustments. Materials and Method: The proposed system integrates solar powered IoT devices, soil moisture sensors, weather data APIs, and edge computing devices to manage irrigation. Machine learning algorithms and evapotranspiration models are used to predict irrigation needs and optimize scheduling based on real time data. The system's performance is evaluated through metrics such as water savings percentage, crop yield improvements, and energy consumption, with a comparative analysis against traditional irrigation methods. Results and Discussion: The results indicate that the system successfully reduces water usage by 30% to 40%, increases crop yield by 25%, and operates with energy autonomy, powered entirely by solar energy. The system's adaptability to varying climate conditions ensures optimal crop growth, even under environmental stresses. The integration of renewable energy and edge computing significantly enhances the sustainability and efficiency of irrigation systems.

Aquaculture is a vital sector in global food production, providing essential protein sources. However, the industry faces significant challenges, including high energy consumption and environmental impact. The integration of renewable energy, particularly solar power, with automation and IoT systems offers a promising solution to enhance energy efficiency, sustainability, and productivity in aquaculture operations. This study aims to evaluate the effectiveness of solar powered autonomous systems in reducing energy usage, improving operational efficiency, and promoting environmental sustainability in aquaculture. Literature Review: Recent research has explored various technologies, such as Digital Twins (DTs) and Precision Fish Farming (PFF), which integrate IoT sensors for real time monitoring and optimization of fish farming operations. The combination of Artificial Intelligence (AI) and the Internet of Things (IoT), known as AIoT, has further advanced the industry by enabling automated decision making and predictive analytics. Solar power integration with IoT systems has been shown to significantly reduce operational costs, minimize carbon emissions, and enhance the sustainability of aquaculture practices. These advancements have the potential to address the challenges of energy consumption and environmental degradation in the industry. Materials and Method: This research utilizes a hybrid solar powered IoT system for aquaculture, integrating solar panels, IoT sensors, and automated control systems. The system monitors key water quality parameters, such as pH, dissolved oxygen, turbidity, and temperature, to maintain optimal conditions for aquatic life. Data is collected through IoT sensors and analyzed through a cloud-based platform. A pilot study is conducted on a small scale aquaculture farm to evaluate the system's performance, including energy consumption, water quality management, and fish health. Energy savings, operational efficiency, and environmental impact are assessed. Results and Discussion: The integration of solar powered IoT systems significantly reduced energy consumption compared to traditional systems, with a notable decrease in grid electricity reliance. The system successfully maintained optimal water quality conditions, enhancing fish health and growth. Solar powered systems proved reliable, even in regions with variable sunlight, and demonstrated improvements in operational efficiency through automation. The environmental benefits were evident, with a reduction in carbon emissions and lower operational costs. The study highlights the feasibility of solar powered IoT systems as a sustainable solution for modern aquaculture operations.

Introduction: Achieving carbon neutrality in industrial systems is essential for mitigating climate change and promoting sustainability. The increasing demand for energy optimization and carbon emission reduction has driven the development of advanced technologies, particularly hybrid machine learning (ML) models. These models, combining ensemble learning and reinforcement learning (RL), offer significant promise in optimizing industrial processes, reducing energy consumption, and improving environmental performance. This study explores the application of hybrid ML models in achieving carbon neutral goals through dynamic process optimization and energy control in industrial settings. Literature Review: Hybrid ML models integrate different machine learning techniques to handle complex and dynamic environments effectively. Ensemble learning methods, such as boosting, bagging, and stacking, combine multiple algorithms to improve predictive performance and robustness. Reinforcement learning (RL), on the other hand, enables real time decision making and adaptation based on trial and error interactions with the environment. In energy optimization, these models are used to reduce energy intensity and carbon emissions, enhancing overall operational efficiency. Previous studies have demonstrated the effectiveness of ML models in energy management, but challenges such as data quality, model integration, and computational complexity remain. Materials and Method: The study applies hybrid ML models combining ensemble learning and RL to optimize energy consumption and minimize carbon emissions in industrial processes. Data from real time sensors and operational parameters are used to train the models. The ensemble learning component improves the accuracy of energy predictions, while RL ensures dynamic process adjustments in response to fluctuating energy demand. The models were tested in various industrial settings, including manufacturing processes, smart grids, and microgrid systems. Performance metrics such as energy efficiency, carbon emissions reduction, and operational costs were evaluated to assess the effectiveness of the models.  Results and Discussion: The hybrid ML models achieved significant reductions in energy intensity (15-20%) and carbon emissions (18-25%). The real time adaptability of the RL component allowed the models to adjust energy consumption patterns dynamically, improving energy efficiency and reducing waste. The models demonstrated their ability to adapt to varying operational conditions, ensuring optimal energy use. A cost-benefit analysis showed that the hybrid models provided substantial energy savings and reduced operational costs, with a return on investment (ROI) of 30-35% within the first year of deployment. However, challenges such as computational complexity and data quality issues were identified, highlighting the need for further refinement in model development.

The selection system at Bina Negara Gubug Vocational School Jl. KH. Hasan Anwar No.9 Gubug currently processes data on the criteria for each student for each type of scholarship. It does not yet have a database system but uses a computerized system with Microsoft Excel, so there are often delays in the selection process in preparing the selection report for scholarship recipients. This research uses the Research and Development (R & D) development model by Borg and Gall with 6 steps of development, namely Research and Information Collecting, Planning, Develop Premilinary Form of Product, Premilinary Field Testing, Main Product Revision, Main Field Testing. The scholarship selection decision support system application product uses the SAW (Simple Additive Waighting) method. Visual Basic 6.0 development software and Microsoft Access database. This system can provide a useful solution for the decision-making system for selecting scholarship recipients for schools so that a better and faster selection can be achieved.      

This study was conducted because the author saw the facts at PT Pelita Mulia Bersinar Each employee has different knowledge that is adjusted to their level of education, this is a determinant for the placement and success of the goals of the targets to be achieved by the company; The experience of employees certainly varies according to how long they have worked in the field which will indirectly form different thought patterns. In addition, it will also affect decision making to achieve the best quality of livestock production; The variety of employee socialization styles with partner farmers who have their own characteristics and different socialization models; and The achievement of livestock production quality in a company is fluctuating which is influenced by different employee competencies, in this case, influenced by different levels of employee knowledge and experience. The purpose of this study is to study, find out, and analyze the influence of employee knowledge on the quality of livestock production; the influence of experience on the quality of livestock production; and the influence of employee knowledge and experience on the quality of livestock production. While the method used in this study is an explanatory survey with a quantitative approach, while the technical data analysis, namely descriptive statistics Analysis and Inductive Statistics (Inferential) with correlation and multiple regression analysis tools. The results of the study and discussion show that employee knowledge has a positive effect on the quality of livestock production; experience has a positive effect on the quality of livestock production; and employee knowledge and experience have a positive effect on the quality of livestock production.

Teachers provide dedication to students to convey knowledge. In addition, teachers also play a role in educating, guiding, and training students so that they can understand the material being taught. Teachers have a very significant role in creating a superior and quality generation. The Principal at SDN Weetame does not utilize the application in the process of selecting qualified and competent teachers or instructors. Researchers observed and designed A selection support system for determining the best instructors implementing multi-attribute-based decision-making method, namely the WP (Weighted Product) method. The outcomes of this study reveal that SPK application can be used easily and produce decisions quickly so that the Principal can make the right choice.

Students who excel academically as well as non-academically in the classroom and at school. High achieving students are very difficult to find because there is no system that can assess student talent in the classroom. Thus, there is a need for a computer-based system that can facilitate teachers in identifying outstanding students. . The system is an application that is made, SPK using the WP method. With the application of the following method, the best option can be determined from various choices and their features through the weighing process. Thus, the results of this research can help teachers and principals at SDN Daha Walu in obtaining the highest score ranking based on the system that can be used as a reference for decision making.

This research aims to analyze the concept of digital leadership, challenges, and opportunities faced by organizational leaders in the technological era. The method used is a literature study with a qualitative approach to explore the definition, characteristics, and strategies of digital leadership. The results showed that digital leadership requires adaptability to technology, data-based decision making, and innovation in managing virtual teams. The main challenges faced are resistance to change and gaps in access to technology, while the main opportunities are the utilization of technologies such as AI and big data.

The existence of gender equality within the organization of the Student Executive Board of the Mulawarman University Student Family which is seen based on reality and what factors influence the achievement of gender equality in the Ministry of Gender within the BEM KM Mulawarman University. This type of research is descriptive qualitative with research data sources of primary data and secondary data. The data analysis techniques used are data collection, data reduction, data presentation and drawing conclusions, and the theories used by the author are Gender theory by Edward Wilson and Feminism theory by Naomi Wolf. The results of this study explain that the reality of gender equality that occurs in the Mulawarman University BEM KM organization in the 2023/2024 BEM KM management has increased towards the involvement of women as leaders and in decision making. In addition, the factors that influence the achievement of gender equality in the gender ministry in the BEM KM organization at Mulawarman University can be seen based on the success and achievement of work programs carried out by the Ministry of Gender. These work programs encourage gender equality awareness and participation through education, empowerment, and overcoming barriers to achieving equality in the organization and ensuring that opportunities are effectively utilized by all parties.

The purpose of this study was to determine how brand image, product quality, online promotion, and product trust level influence consumer decisions to purchase products at CV. Tenun Mulia Gemilang. This study used a questionnaire distributed through social media in the form of Instagram and Whatsapp. This study involved 100 people who were selected randomly. Multiple linear regression analysis was used to analyze the data to evaluate the model between the established variables. The results showed that brand image, product quality, online promotion and product trust level have a significant influence on consumer purchasing decisions for woven products. This study suggests that business actors pay attention to brand image, product quality, and online promotion to increase customer trust and ultimately influence their purchasing decisions. Thus, CV. Tenun Mulia Gemilang can increase consumer product purchasing decisions.

Excessive sugar consumption has become a serious public health problem. Increasing patterns of food and drink consumption in line with changes in modern lifestyles have contributed to an increase in the prevalence of non-communicable diseases such as obesity, type 2 diabetes and cardiovascular disorders. This study analyzes and analyzes the use of Artificial Intelligence (AI), especially Deep Learning techniques and Neural Network algorithms, in the classification of sugar content in sweetened drinks. The Systematic Literature Review (SLR) method was used to filter relevant studies published between 2020-2024. The study results show that AI is able to provide more efficient and accurate solutions than manual methods. However, although the literature results show great potential, the application of AI in sugar content classification still requires further empirical research. This study emphasizes the importance of developing AI models tailored to the characteristics of sweetened drinks to support consumer decision making regarding healthier drink choices.

In the era of artificial intelligence (AI), technology is growing rapidly and changing the way businesses are run. AI enables automation, big data analysis, and increased operational efficiency. However, this development also raises various ethical issues that companies need to pay attention to so as not to harm consumers, society, and the environment. This study explores the paradigm of artificial intelligence in the context of business ethics, focusing on its impacts, challenges, and potential benefits in the business world. This study uses a systematic literature review approach from various reputable sources. The article criteria include literature published from 2019 to 2024 with the theme of business ethics in the AI era, and other articles relevant to this study. Based on the search, 15 articles were determined that were relevant to the predetermined criteria. The results of the study found that in this study, AI is not only a technical tool to improve operational efficiency, but is also able to redefine business ethics in the modern era. AI offers great potential to overcome traditional ethical challenges and create new paradigms in business decision making. However, this opportunity is also accompanied by significant challenges, such as algorithmic bias, data privacy, and lack of regulation. This discussion will review the role of AI in business ethics, the benefits it brings, the challenges it faces, and the steps that can be taken to optimize the ethical use of AI.

This article discusses the development of accounting information systems to improve efficiency and accuracy, focusing on a case study of the implementation of accounting program changes. Previous studies have shown that effective accounting information systems can significantly improve the quality of accounting and managerial information. The implementation of accounting program changes often involves the integration of information technology to improve the process of financial reporting, internal control, and analysis of company performance. Previous studies have shown that companies that adopt information technology in their accounting systems have a competitive advantage in managing and analyzing financial information more efficiently. Important factors in the development of accounting information systems are the need to ensure data accuracy, reporting speed, and real-time availability of information for internal and external stakeholders. This study also explores the positive impact of the use of accounting information systems on the company's operational efficiency and strategic decision making. Successful implementations show that modern accounting information systems are able to integrate various business functions, such as finance, inventory, and manufacturing, to improve the coordination and effectiveness of the organization as a whole. Thus, the development of accounting information systems not only improves the company's internal processes but also enhances the company's adaptability to rapid and complex changes in the business environment. This study provides a strong theoretical foundation for understanding the importance of information technology integration in the context of accounting program changes to achieve higher efficiency and accuracy goals.