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This research aims to analyze the implementation of da'wah management in community organizations in Kresek District, Tangerang Regency. The research focuses on the application of da'wah management functions including planning, organizing, actuating, and controlling in da'wah activities. The research method used is descriptive qualitative with data collection techniques through observation, in-depth interviews, and documentation. The research subjects were administrators of Islamic community organizations in Kresek District. The results showed that the implementation of da'wah management in community organizations in Kresek District still requires optimization, especially in the aspects of organizing and controlling. Da'wah planning has been carried out well through the preparation of short-term and long-term work programs, but there are still obstacles in organizing human resources and coordination between organizational elements. The implementation of da'wah programs runs smoothly despite challenges in adapting to technological developments. The supervision and evaluation system needs to be improved to ensure the effectiveness of da'wah programs. This research provides recommendations for strengthening organizational management capacity through da'wah management training and developing collaboration between community organizations.

This study explores the integration of Artificial Intelligence (AI) with thermal optimization in Waste-to-Energy (WtE) systems to enhance both energy recovery and emission control. Introduction: The growing need for sustainable urban waste management has highlighted the importance of optimizing WtE systems. AI technologies, including machine learning and deep learning, have shown potential in improving the efficiency of WtE processes, especially in reducing emissions and enhancing energy recovery. Literature Review: Previous research indicates that AI has been successfully applied to various WtE technologies such as pyrolysis, gasification, and incineration, yet the integration of AI specifically for thermal optimization remains underexplored. Most studies focus on predictive models for emission reduction rather than real time thermal optimization. Materials and Method: The study proposes the development of an AI-driven framework that integrates real time data collection from IoT sensors, predictive modeling, and real time control algorithms. The system optimizes key parameters such as combustion temperature and fuel flow to enhance energy recovery and minimize emissions. The method includes data collection from operational WtE plants, followed by model development using machine learning algorithms. Results and Discussion: Initial simulations and pilot testing showed significant improvements in energy efficiency and emission reduction. AI-driven systems outperformed conventional WtE systems by optimizing operational parameters in real time. The study identifies gaps in AI integration for thermal optimization and suggests future research directions, including the integration of AI with smart grids and carbon credit systems for more sustainable WtE operations.

The Internal Quality Assurance System (SPMI) is a strategic mechanism for directing and controlling the quality of education through continuous planning, implementation, evaluation, and follow-up processes. This study aims to describe and analyze the management of SPMI in improving the performance of Vocational High Schools (SMK), with research sites at SMK Bina Teknologi Subang and SMK Al-Mufti Purwadadi. Using a descriptive qualitative approach, this study examines the implementation of management functions based on the PDCA (Plan, Do, Check, Action) cycle within the context of educational quality assurance. The results indicate that the implementation of SPMI contributes positively to improving school performance, particularly in meeting and exceeding the National Education Standards (SNP), as reflected in the school self-evaluation results and recommendations in the education report card. Furthermore, the implementation of SPMI encourages schools to carry out root-cause-based improvements through systematic program planning, activity development, and priority setting. These findings highlight that the success of SPMI is strongly influenced by consistent implementation and the commitment of all school stakeholders. The Novelty of this study lies in the development of a hypothetical SPMI model based on performance management, which is relevant for enhancing the quality and competitiveness of vocational schools in a sustainable manner.

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.

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.

This study aims to design and develop a prototype of an Internet of Things (IoT)-based land watering monitoring system using the ESP8266 module and soil moisture sensor. This system is designed to help farmers manage watering automatically based on soil moisture conditions, so that they can save water and labor. The process at this time begins with a literature study, hardware and software design, to prototype testing on two soil conditions, namely dry and wet. Data from the sensor is sent in real-time to the IoT platform, if the soil is detected dry, the system automatically activates the water pump. The results of the test show that the sensor works accurately in distinguishing soil conditions, and the system is able to water automatically according to needs. Furthermore, this system can also be monitored and controlled remotely via the internet. The conclusion of this study shows that the use of IoT technology is very potential to increase efficiency and effectiveness in agricultural land management.

This study explores the integration of AI-driven process optimization in Waste-to-Energy (WtE) systems to enhance urban sustainability. The research focuses on designing a gasification-based WtE system, incorporating AI predictive control to optimize energy conversion processes. The AI system adjusts operational parameters in real-time, improving energy conversion efficiency by 25% and reducing carbon emissions by 40%. Additionally, the system's waste-to-energy conversion rate is projected to increase by 20%, and operational costs are expected to decrease by 30%. Data collection and analysis are carried out using advanced sensors to monitor key parameters such as temperature, gas composition, and energy output, which are then processed by machine learning algorithms for predictive analysis. The results show that the AI optimization significantly enhances system performance, offering a sustainable solution for urban waste management. The study highlights the technical and operational challenges of integrating AI into existing WtE systems, including the need for infrastructure upgrades and scalability considerations. It also discusses the socio-economic impacts, including job creation, reduced energy costs, and improved public health. The findings demonstrate the potential of AI-based WtE systems in reducing waste, generating clean energy, and mitigating climate change, positioning them as a viable solution for sustainable urban development.

This article examines the crucial role of eco-leadership in achieving a sustainable and environmentally friendly economy, particularly within the dynamic context of the digital age and industry 4.0. In this era, the pressure on companies to integrate environmentally friendly initiatives into their corporate social responsibility (CSR) programs is increasing, supported by government policies and regulations in Indonesia. This article highlights that the effectiveness of environmental protection and sustainable corporate performance can be measured through various practices such as waste management, pollution control systems, recycling, and environmental impact mitigation. In conclusion, environmentally oriented leadership plays a central role in promoting more responsible business practices and behaviors, which are essential for reaching sustainability targets and realizing an economy that is not only financially profitable but also responsible for environmental preservation.1

The farmer's chicken supply chain is a complex system that involves various stages starting from selecting chicken seeds, rearing, feeding, health management, to distribution of the final product to the market. Distribution Channels are closely related to the Supply Chain process, both of which are important in a business, both large and small businesses. The aim of this research is to determine the Broiler Chicken Supply Chain at Kemiri Village Broiler Farms, Jenangan District, Ponorogo Regency. The research method used is observation, interviews and documentation. This broiler farm is under contract with PT. Bintang Tama to supply feed, vitamin medicine, chicken seeds, and also chicken brokers/collectors. Chicken seeds come from PT.Bintang Tama Sentosa after which the chickens are bred for 28 days to 35 days according to the contract with the broker/collector, in 1 harvest/livestock from 3000 seedlings to harvest, the estimated death is 200 deaths, this process cannot be separated from the control carried out by the livestock manager. Chicken farming here is managed well, starting with providing different feeds. Meat chicken seeds are fed with the types of feed, namely pre starter, starter, and finisher, this feed is given at 3 different/not the same age periods for the chickens in 1 harvest. Pak Endra's Farm – Agent – Broiler Chicken Entrepreneur – Market/Restaurant – Final Consumer.

Occupational safety and health (K3) is an important factor in ensuring the physical and mental health of workers and creating a safe work environment. This research discusses the implementation of K3 management to minimize work hazards, especially those caused by developments in industrial technology and the use of hazardous materials such as asbestos. As a destructive material, asbestos can cause serious diseases such as lung and pleural cancer if not managed properly. Referring to the K3 management system policy in the Minister of Manpower Decree No. 05 1996, this research emphasizes the important role of company management in integrating K3 into the operating system. It is hoped that the results of this research can serve as a guide for the business world to identify hazards, assess risks, and implement control measures to create a safe and secure work environment.

Nephrotic syndrome is a group of diseases characterized by massive proteinuria that causes hypoalbuminemia, resulting in hyperlipidemia, edema, and various complications. One of the etiologies of nephrotic syndrome itself is primary and secondary glomerulonephritis in the form of infection, malignancy, connective tissue disease, drugs or toxins and due to systemic diseases. The incidence of nephrotic syndrome cases in adults does not have a significant difference between genders, where the cases are 3 per 100,000 population. The broad clinical manifestations of nephrotic syndrome require health workers to conduct anamnesis, physical examination, and supporting examinations carefully. When nephrotic syndrome has been established, management will be carried out. Management that can be given to this disorder is non-pharmacological such as a low protein and salt diet and pharmacological especially for the underlying disease. Non-specific treatment to reduce proteinuria, control edema, and treat complications that may occur. The prognosis for nephrotic syndrome depends on the underlying cause.

Automatic Identification System (AIS) is a communication technology that plays an important role in improving operational safety and efficiency in the shipping industry. AIS allows ships to exchange real-time data on identity, position, speed, and direction, which helps prevent collisions and facilitates maritime traffic management by port authorities. In addition, AIS functions in search and rescue operations by providing accurate information on the location of ships in trouble. In terms of security, AIS allows monitoring of suspicious ships, thus helping in preventing illegal activities in the waters. This study aims to design and develop a prototype AIS receiver based on LoRa, Arduino, and LCD HMI. The LoRa module was chosen because of its ability to transmit data over long distances with low power consumption, which is suitable for the maritime environment. Arduino is used as the main microcontroller to control the system, while the LCD HMI serves as the display interface for the received data. After the hardware and software design was completed, the system was tested through functional testing and performance measurements using a spectrum analyzer to evaluate the strength of the LoRa signal at various distances. The test results show that the AIS receiver is able to receive data well up to 15 meters on land and 13 meters at sea, with a delay of 100 milliseconds. System performance degrades at longer distances due to environmental interference and signal attenuation. These findings provide insight into the effective limits of LoRa communication in maritime applications and can be used as a reference for frequency testing and optimization of LoRa-based long-range communication systems.

Efficient and accurate fuel management systems are becoming increasingly important as energy needs and operational complexity increase in various industrial sectors. This study aims to design and implement a fuel flow monitoring and control system using a variable control valve. This system allows real-time monitoring of the level and flow of fuel in the service tank on the ship, as well as automated control. In its implementation, ultrasonic sensors, control valves are combined with LM2596 connected to Arduino nano for data collection, analysis and visualization. The test results show that this system is able to provide accurate data on the flow and level of fuel in the service tank on the ship by displaying the measurement results on the LCD and providing warnings via a buzzer. The LCD display shows the reading of the fuel level and valve opening in the tank. At a fuel level of 0 - 25% the valve will open 100% and requires an average filling time of 25 seconds, At a fuel level of 25% - 50% the valve will open 75% and requires an average filling time of 27 seconds, At a fuel level of 50 - 75% the valve will open 50% and requires an average filling time of 30 seconds, At a fuel level of 75 - 99% the valve will open 25% and requires an average filling time of 32 seconds.

Effective financial management is a crucial aspect in ensuring the sustainability and growth of an organization, including in the context of social and profit organizations (SOPI). The Revenue and Expenditure Budget Plan (RAPB) is the main instrument in financial management, which not only functions as a guideline for allocating resources, but also as a strategic tool in achieving organizational goals. This study uses a library research method to explore how systematic budget planning can improve financial efficiency and ensure transparent and accountable use of funds. This study highlights the importance of preparing formal documents such as annual work plans, budget work plans, and RAPB in ensuring that organizations can manage resources in a more structured and measurable manner. By applying analysis to various literature sources, this study identifies steps in preparing an effective RAPB, including revenue estimation, expenditure allocation, and budget evaluation and control mechanisms. The results of the study show that a well-prepared RAPB can help organizations set priorities, measure performance, and avoid waste of resources. In addition, RAPB also acts as an internal communication tool that clarifies the direction and goals of the organization to all stakeholders. With a strict evaluation system, organizations can ensure that the budget used has an optimal impact on achieving the vision and mission that have been set.

The need for an efficient system to manage academic works in digital format is growing in universities, including at Universitas Islam Negeri Sumatera Utara (UINSU). Despite previous developments in digital repository systems, many academic institutions, including UINSU, still face challenges related to data management, security, and accessibility. This study aims to develop a web-based repository system for UINSU using the Waterfall method, to improve the storage, management, and accessibility of academic resources. A structured quantitative approach was adopted, focusing on the development and implementation of the repository system. The Waterfall methodology was chosen due to its step-by-step approach, ensuring a thorough and organized development process. The implementation of the system resulted in an organized, user-friendly platform where students, faculty, and staff can upload, manage, and access academic documents efficiently. The system features a clear interface for searching, uploading, and managing documents, with administrative controls for approving and maintaining submissions. The repository system significantly improves data management at UINSU, providing a long-term solution for archiving academic work. Continuous evaluation and system upgrades are essential to ensure it adapts to future needs and technological advancements.

This study aims to analyze the implementation of the SPIRIT model of problem-based biology learning (SSIPBL) on the respiratory system material at Muhammadiyah 1 Sragen High School in the 2024/2025 academic year and to determine whether this model can improve students' learning outcomes. The research type used is quantitative with an experimental design. Data collection was carried out through learning outcome tests, observations, and interviews. Based on the t-test results, a significance value (sig.) of 0.198 was obtained, which is greater than the 0.05 value, indicating that there is no significant difference between the experimental group using the SSIPBL model and the control group using conventional learning methods. Factors affecting the ineffectiveness of this model's implementation include teacher readiness, limited time, lack of student involvement, and inadequate infrastructure. The results of this study show that the implementation of the SPIRIT SSIPBL model on the respiratory system material does not significantly improve students' learning outcomes. Therefore, it is recommended to improve supporting aspects, such as teacher training, better time management, and increasing student motivation and involvement in problem-based learning. Indicates that the implementation of the SPIRIT model of Socio-Scientific Problem-Based Learning (SSIPBL) can significantly improve students' learning outcomes on the respiratory system material senior High School for the. These results suggest that SSIPBL has the potential to enhance students' understanding through a problem-based approach that connects scientific phenomena with social issues, and its implementation in the field met expectations.

The authors of the article have chosen a company acting as an agent for a container shipping line because the company seeks to decrease its service failures and reduce the chaotic nature of its activities by systematizing them from a scientific point of view and refining its operations at the managerial level. Employees of the company are responsible for activities such as a search for customers, price offers, contacting clients, the conclusion of contracts, coordination of cargo transportation, document control, invoicing and payment control. Proper execution of these operations ensures the quality of services provided by the container line agent. The learning organization concept, situational management theory and total quality management theory are applicable to the management of the personnel activity process in the line. In terms of management functions, planning is more suitable for activities such as searching for customers, price offers, conclusion of contracts and invoicing; organizing is more required when searching for customers, contacting them and concluding contracts; leading is more suitable for activities such as contact with clients, conclusion of contracts and payment control; control is more required when contacting customers, coordinating cargo transportation, invoicing and controlling payment. A conceptual approach that theoretically reveals the principles and possibilities of the company’s activities in the container shipping line can serve as the basis for future empirical research to identify problems in its personnel activity management.

This research develops a prototype of an automatic watering device based on the Internet of Things (IoT) and a soil moisture sensor to improve the efficiency of watering crops in agricultural fields. The main problem addressed is the consistency and efficiency of watering in large agricultural fields, where traditional management is prone to human error and inefficient water use. The developed prototype uses an ESP8266 microcontroller (NodeMCU) as the brain of the system connected to a Wi-Fi network, allowing remote monitoring and control via the Blynk application. A soil moisture sensor is used to detect soil conditions in real-time, triggering watering only when needed. This helps optimize water use and increase agricultural productivity sustainably. This research outlines the methodological steps from design, manufacturing, to implementation of the prototype in the field. Evaluation of the results shows that the system successfully regulates watering effectively based on soil conditions, with positive responses from farmers as end users.

The research departs from the phenomenon of the development of Islamic boarding school education models with varying names and styles. Islamic boarding schools are faced with two important problems in adapting to the demands of the times, namely the problem of developing Islamic boarding school governance without abandoning tradition and the Islamic boarding school's identity in producing a generation with good morals. The research objectives are to identify the management of Sufistic curriculum development in Islamic boarding schools including; 1) Curriculum planning, 2) Curriculum organization, 3) Curriculum implementation, 4) Curriculum evaluation and 5) Impact of Islamic boarding school management in developing the Sufistic curriculum at Al-Istiqomah Islamic Boarding School and Al-Falah Biru Islamic Boarding School, Garut Regency. The research framework departs from George R. Terry's (1973) management theory, namely four management functions, namely: 1) Planning, 2) Organizing, 3) Actuating, 4) Controlling. The curriculum theory uses the Ralph W curriculum development model. Tyler curriculum development is carried out in systematic stages, namely; Objectives, Selecting Learning Experiences, Organizing Learning Experiences, Evaluation. Developing the Islamic boarding school curriculum has an impact on the morals of the students, as according to Sheikh Musthafa Al-Ghalayini, the implications of Sufistic moral values contribute to shaping behavior. This study uses a qualitative approach using the Ethnography method. Data collection techniques are carried out through interviews, observations and documentation analysis. The data analysis technique uses the Miles and Huberman analysis technique. While the validity test is carried out with data validity by conducting tests; credibility, transferability, dependability, and confirmability. The results of the study found that the management of the development of the Islamic boarding school curriculum in preparing a generation with Sufi morals: First, the Islamic boarding school curriculum is included in the traditionalist model of the school, namely by showing its traditional and school character. Second, the organization of the curriculum content consists of the contents of the curriculum, data, concepts, generalizations, and subject matter at the Islamic Boarding School. Third, Curriculum development is categorized as a grass roots model where there are initiatives and efforts coming from below, namely ustadz and Islamic boarding schools in developing a curriculum that is designed by themselves to produce a generation with Sufi morals. Fourth, Curriculum evaluation refers to the Objective Model Evaluation model (objective model) carried out at the end of curriculum development, this assessment activity is often called summative evaluation. Fifth, The impact of curriculum management on the level of morals is shown by the nature of istiqomah, self-control, prioritizing Islamic and basyariyah brotherhood, tolerance, honesty, sincerity, istiqomah, patience, gratitude, politeness and helping each other. Sixth, Traditionalist Hypothetical Management Model of the School.

This study explores the potential and challenges of the Treasury Single Account (TSA), which the cur-rent government of Nigeria has recently fully implemented to drive economic growth and development. The government aims to close gaps and plug leaks in government funds while ensuring a robust finan-cial management system to guarantee transparency and efficiency in the administration of public fi-nancial resources. The paper provides a conceptual understanding of TSA and discusses its anticipated benefits to Nigeria’s economy, particularly in the context of financial management and control. Key benefits include reducing the cost of government borrowing, ensuring optimal utilization of govern-ment financial resources, and consolidating various government accounts into one unified account. The study also examines the structure of the TSA system and its various accounts, including the TSA pri-mary account. In addition, the paper highlights the goals of the TSA, such as improving accountability and reducing corruption. After discussing the potential and challenges associated with implementing the TSA, the study concludes that political will, integrity, and commitment are crucial for overcoming these challenges. Successful implementation of the TSA system requires addressing identified obstacles to realize the anticipated benefits, which would significantly enhance the efficiency of financial man-agement in Nigeria.