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This study aims to explore the implementation of the Balanced Scorecard (BSC) through the digital system "MyCore" in measuring and improving employee performance at Bank BRI Unit Sokaraja Tengah. Using a descriptive qualitative approach, data were collected through semi-structured interviews with key informants, observations of work practices, and analysis of internal documents (performance reports, SOPs). Data analysis was carried out through data reduction, data presentation, and drawing conclusions with verification through source triangulation. The research findings indicate that the "MyCore" system integrates four BSC perspectives (finance, customer, internal business process, learning & growth) with specific performance indicators that affect incentives and career development. The financial and customer perspectives appear to have a strong emphasis, reflected in the direct impact on incentives and bonuses. The implementation of internal business processes is supported by standardization through MyCore and technology adoption. The importance of the learning and growth perspective is realized through regular training programs and bootcamp interventions for low-performing employees, which have proven effective in improving subsequent evaluation scores. In general, the implementation of the BSC via MyCore creates a structured, transparent, and adaptive assessment mechanism, encouraging productivity and professionalism. The implications of this study emphasize the importance of a transparent performance evaluation system that has a direct impact on career development and incentives, while also demonstrating the effectiveness of structured interventions in improving employee performance at the micro banking unit level.

Artificial Intelligence (AI) has become an essential tool in the world of management for decision-making. This article examines the ways in which AI can be used to improve the quality and speed of decision-making, and how AI can improve the operational efficiency of companies. In addition, this article also examines the challenges and opportunities that companies face in adopting AI.In the rapidly evolving digital era, AI has become an essential component of modern business strategies. Today's managers are often faced with the challenge of analyzing very large and complex volumes of data. To make good and timely decisions, AI offers a potential solution with fast and precise data analysis capabilities.The use of AI in decision-making involves machine learning algorithms and models to efficiently process and analyze large amounts of data. This helps managers gain deeper and more accurate insights, enabling more effective decision-making.

The purpose of this journal is because there are still many kindergartens/RAs that do not fully understand the management of learning environments. This paper aims to understand and describe the findings of observations conducted at RA An-Nur Babalan regarding the management system of learning environments. Based on the findings of the study, RA An-Nur Babalan has successfully implemented a learning environment system. The stages of this research are descriptive qualitative research, where researchers try to describe and explain the object of research according to existing knowledge. The methods used in this study are observation and interviews. The data that has been collected is then analyzed through several steps, namely data collection, data reduction, data analysis, and conclusions. The findings of this study indicate that RA An-Nur Babalan can create a learning environment that involves students (invites them into the classroom), encourages them to be independent, and has implemented the process of using the learning environment, as well as applying several principles of the learning environment. This study can be used to support the idea that the learning process, which includes teaching students about their social, emotional, and intellectual environments, has a general purpose of providing a means for them to engage in various activities.

This study aims to identify the optimal model in the integration of philosophical disciplines in the structure of the educational program of “Public Administration” students, as well as explore the features of the management of educational strategies suitable for the training of civil servants. The main focus of this research is: 1) academic management strategies to overcome curriculum overlap due to the dominance of philosophical disciplines in public administration study programs; 2) adaptation of educational programs for public administration students to be in line with the needs of the world of work, both at national and international levels; 3) characteristics of internationalization of public administration education programs, especially in the context of academic mobility and adaptation of the Indonesian public administration system to global standards. This research uses the cultural-historical analysis approach, comparative method, structural-functional method, and expert evaluation to explore and analyze problems and develop solutions. The research findings show that the dominance of traditional philosophy courses in the curriculum is often ineffective in shaping the competencies needed in the world of work. The research identified three main challenges: saturation of the curriculum with theoretical courses, lack of connection between the curriculum and the practical needs of the working world, and low use of English in teaching key courses. To address these issues, this research proposes restructuring the curriculum through the integration of three disciplinary groups: applied logic, cultural studies, and applied political science. In addition, the implementation of a contextualized bilingual learning model is also considered as a solution to improve the relevance of the curriculum. The uniqueness of this article lies in its approach that combines philosophical studies with managerial strategies in curriculum design, complemented by empirical experiences from international and cross-institutional cooperation. This article offers a reinterpretation of the utilization of philosophy as a tool for the development of professional competence in public administration education, not just as an abstract worldview.

Indonesia is predicted to have the threat of demographic bonus while also having the opportunity to take advantage of this threat through the Prakerja program. Since 2020 the Prakerja program has been running and there are still many numerical achievements that need to be realized to avoid the threat of demographic bonus and in line with the vision of Indonesia emas 2025. PT Generasi Anak Muda Berkarya with HiColleagues brand is a startup moving in the field of Education Technology and IT Service in sustainable digital transformation that is committed to realizing the vision of Indonesia emas 2045 through implementation of the Prakerja program. Learning Management System (LMS) platform according to the Prakerja standard is a mandatory requirement that the training institution must have to become the Prakerja partner. This research aims to produce the Learning Management System (LMS) prototype design according to the Prakerja standard, giving a good experience to participants in completing a series of training class mechanisms, support the participant graduation ratio, and increase brand positioning of HiColleagues as the Prakerja partner. Designing a Learning Management System (LMS) prototype applies the Design Thinking method through the 5 phases, namely Empathize, Define, Ideate, Prototype, & Test. As well as using Figma as a design tool and Maze as a Usability Testing. This Learning Management System (LMS) prototype design succeeded in getting good feedback from users with 100% succession rate although there are minor improvisations on the user interface as a form of alignment. 

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 implementation of a quality management system in educational institutions is a strategic step in ensuring the quality of the process and sustainable learning outcomes. However, in reality, many madrasas still face obstacles in implementing the system effectively and comprehensively. This study aims to analyze in depth the quality management system implemented at MTs Negeri 2 Musi Banyuasin, including planning, implementation, evaluation, and strengthening strategies. The research method used is qualitative descriptive with a case study approach, where data is collected through observation, documentation, and in-depth interviews with relevant parties in the institutional structure of the madrasa. The results of the study indicate that the quality management system in this madrasa has adequate structural devices and formal documents, but its implementation is still administrative, not fully integrated into the work culture, and not supported by digitalization of information systems and optimization of stakeholder participation. Strengthening is needed in the aspects of technical training, utilization of technology, and instilling a culture of quality so that the system built can run sustainably and have a real impact on improving the quality of education.

Introduction: The integration of Digital Twin (DT) technology and the Internet of Things (IoT) into Building Energy Management Systems (BEMS) offers a transformative approach to optimizing energy consumption in buildings. This study explores the development of a Digital Twin based BEMS prototype, which leverages real time data collection, predictive analytics, and machine learning to enhance energy efficiency, reduce costs, and support sustainability goals in modern buildings. The research also addresses key gaps in current energy management systems, including real time adaptive control and integration with smart grid platforms. Literature Review: Previous research highlights the limitations of traditional BEMS, which often rely on static control strategies and lack real time adaptability. Recent advancements, including predictive maintenance and machine learning integration, have improved energy optimization. However, challenges such as data interoperability, scalability, and cybersecurity remain. This review consolidates current approaches and identifies opportunities for enhancing BEMS through the integration of DT technology, IoT, and machine learning. Materials and Method: The methodology employed involves the design of a Digital Twin based BEMS prototype, incorporating IoT sensors for real time data collection on variables such as HVAC load, occupancy, and environmental factors. The system uses time series forecasting and adaptive control strategies to optimize energy consumption. A case study building is used for validation, with performance metrics such as energy savings, CO₂ footprint reduction, and peak load reduction assessed to evaluate the system's effectiveness. Results and Discussion: The results demonstrate a significant reduction in energy consumption (up to 50%) compared to traditional BEMS, along with improved forecasting accuracy and sustainability performance. The prototype achieved a high R² score in predicting energy usage, validated through real world application in the case study building. The economic feasibility analysis showed substantial cost savings and a strong return on investment, making the system a financially viable solution for energy efficient building management.

Improving the quality of education is a strategic demand in responding to global dynamics and community demands for the quality of educational institutions, including madrasahs. MTsN 1 Ogan Komering Ilir as one of the formal Islamic educational institutions strives to build a structured quality management system to improve the academic quality and character of students. This study aims to analyze the implementation strategy of quality improvement management at MTsN 1 Ogan Komering Ilir, identify the obstacles faced, and explore strategic opportunities that can be utilized in the quality improvement process. This study uses a descriptive qualitative method with a case study approach, and data were collected through observation, documentation studies, and in-depth interviews with four main informants. The results of the study indicate that madrasahs have implemented quality management strategies through data-based planning, implementation of teacher capacity building programs, strengthening learning, and periodic quality evaluations. However, there are still obstacles such as limited human resources, lack of quality literacy, and limited use of information technology. On the other hand, there are opportunities such as support from national policies, commitment from madrasah leaders, and stakeholder participation that can be maximized to strengthen the quality system in a sustainable manner.

Madrasas and Islamic boarding schools are Islamic educational institutions that have a strategic role in shaping the character, morals, and competencies of students. In addition to carrying out the formal learning process, these two institutions are also centers for moral, spiritual, and social development. In their operations, madrasas and pesantren manage various administrative activities, such as student data collection, attendance recording, grade processing, teacher data management, lesson schedule preparation, and delivery of academic information to related parties. However, many institutions still use manual systems that rely on notebooks or separate applications that are not integrated. This condition poses a number of obstacles, including the high risk of recording errors, duplicate data that is difficult to track, the slow process of recapitulation of grades and attendance, and delays in the delivery of academic information. In addition, manual processes cause administrative management to be less efficient and prone to data loss. As the need for fast, accurate, and accurate information increases, technological solutions are needed that are able to integrate all administrative and academic processes in one centralized system. Web-based information systems are an effective alternative to improve work efficiency, minimize errors, and facilitate access to information for teachers, students, and guardians. With the implementation of a well-managed system, madrasas and Islamic boarding schools are expected to improve the quality of services and support a more modern, structured, and sustainable learning process.

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.

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.

Islamic education has a very important role in shaping the character and morals of individuals, as well as in developing quality human resources. Evaluation of Islamic educational institutions is one of the most crucial aspects in efforts to improve the quality of Islamic educational institutions as a whole. This article discusses the importance of institutional evaluation in Islamic education to measure the extent to which institutions can fulfill the vision, mission, and goals of Islamic education. Evaluation does not only cover academic aspects, but also character, morals, management, curriculum, human resources, facilities, and relations with the community. In addition, this article also identifies the basic principles in evaluating Islamic educational institutions, namely objectivity, transparency, and justice. This study uses a library research method by collecting and analyzing related literature, such as books, scientific journals, and academic articles. The results of the study indicate that evaluation of Islamic educational institutions functions as a tool for continuous improvement, supports accountability, and adapts the curriculum and learning methods to the needs of the times. In addition, the role of leaders in the evaluation process is vital to ensure the successful implementation of the evaluation. It is hoped that this article can contribute to the development of an effective and efficient institutional evaluation system in Islamic education.    

Improving the quality of education is a strategic challenge for every educational unit, including private elementary madrasahs that carry the Integrated Islamic approach. MIS IT Nurul Ikhwan Cahaya Ananda Palembang as a basic educational institution based on Islamic values ​​and technology, faces various dynamics in managing quality management, ranging from limited resources to the complexity of implementing an internal quality assurance system. This study aims to describe in depth the management strategies applied in improving the quality of education, as well as identifying the challenges and solutions faced by madrasahs in the implementation process. The research method used is descriptive qualitative with data collection techniques in the form of observation, documentation, and in-depth interviews with key informants. The results of the study indicate that madrasahs have implemented quality management through strategic planning, strengthening teacher capacity, integrating technology in learning, and community involvement. Despite challenges such as budget limitations and imbalances in HR competencies, madrasahs are able to present solutions based on collaboration and innovation that are oriented towards the sustainability of education quality.

The world of education has undergone a major shift as a result of advances in information and communication technology. This study compares conventional and digital learning methods for distance learning (PJJ) across the board, with the aim of finding out what is effective, what is not effective, and how the two methods affect student learning outcomes and experiences. Conventional learning, which relies on direct interaction between teachers and students, emphasizes elements such as giving feedback, easy to do, structured, and routine. It has the advantage of being able to facilitate direct interpersonal communication, provide intensive supervision and guidance, and create a competitive learning environment. However, this method has some limitations, especially in terms of time and space flexibility. It is also not able to meet the learning needs of individuals in large groups. On the other hand, digital learning offers greater flexibility, access to a wide range of educational resources, and increased interactivity through the use of online collaboration tools, e-learning platforms, and video conferencing. The use of technology allows learning content to be presented in a systematic, structured and engaging manner, increasing student motivation and participation. In addition, it allows materials to be tailored to each student's learning style and conditions, and supports collaborative and independent learning. Challenges include the possibility of misuse of technology, limited access in some areas, lack of direct social interaction, and reliance on digital infrastructure and capabilities. The research results indicate that digital learning generally enhances student learning outcomes more significantly compared to conventional learning, especially in terms of distance learning (PJJ). Digital strategies such as structured instructional design, integration of practical experiences, motivational support, and time management have been shown to improve student interaction, understanding, and independence. However, digital and conventional learning methods can complement each other to achieve optimal effectiveness. The application of these strategies not only boosts students' academic performance but also equips them with the essential skills to tackle future challenges. 

Character education is an essential aspect of Islam in shaping individuals with noble morals. Hadith, especially those compiled in Arbain an-Nawawi, contains many moral values that can be applied in daily life. This study aims to identify moral values in Arbain an-Nawawi, analyze how to implement them in education, and examine the challenges and solutions in their application. This research uses content analysis to examine the hadiths in Arbain an-Nawawi.The findings reveal that the moral values in these hadiths fall into three main categories: (1) Morals toward Allah, such as sincerity (ikhlas) and trust in God (tawakal); (2) Morals toward others, such as honesty and compassion; and (3) Morals toward oneself, such as self-reflection and anger management. These values can be taught through exemplary behavior, habituation, self-reflection, and storytelling. However, there are several challenges in implementing hadith-based character education, such as a lack of understanding among educators regarding hadith, an education system that prioritizes academics over character development, and the influence of modern culture and technology. To address these challenges, teacher training, the strengthening of character-based curricula, and the use of technology as a learning medium are necessary. This study is expected to provide insights for the educational sector in strengthening students’ character based on Islamic teachings.    

The development of digital technology has brought a significant transformation in the field of education, particularly in learning processes. Traditional teaching methods are now shifting toward more flexible, interactive, and accessible digital systems. This article discusses various strategies for integrating technology into learning in the digital era, including the use of Learning Management Systems (LMS), the application of Artificial Intelligence (AI), and the development of multimedia-based interactive learning content. Furthermore, strengthening digital literacy among teachers and students is a key focus in ensuring the successful implementation of technology in education. This study employs a literature review method by summarizing various scholarly sources and previous research findings. The results indicate that the appropriate application of technology in education can enhance learning effectiveness, promote student independence, and foster 21st-century skills. However, challenges such as unequal access to technology and the lack of teacher training remain obstacles that need to be addressed. Therefore, collaboration between educational institutions, the government, and the community is essential to create an inclusive and sustainable digital learning ecosystem. This article is expected to contribute to the development of adaptive learning strategies aligned with technological advancements and the needs of the times.    

This study examines the extent to which the compatibility between a student's major and their interests affects their learning experience at Universitas Negeri Medan (UNIMED), particularly in the Accounting Department. The findings indicate that many students feel that their major aligns with their interests, which in turn boosts their enthusiasm for learning. However, some students choose their major due to parental pressure or promising job prospects, which ultimately leads to difficulties in their studies. Additionally, students face various challenges in the learning process, ranging from heavy academic workloads, difficulties in understanding certain subjects, to the pressure of managing time between classes and other activities. These challenges are exacerbated by the demands of mastering accounting technology and adapting to an Outcome-Based Education system. To overcome these obstacles, students employ various strategies, such as improving time management, seeking additional learning resources, joining academic communities, and securing scholarships or part-time jobs for those experiencing financial constraints. This research confirms that the alignment of a major with a student's interests significantly influences their academic success. Therefore, it is essential for the university to provide better guidance in major selection and offer enhanced academic support to help students adapt more easily and succeed in their studies.

In the current digital era, SMEs in the culinary sector face challenges in adopting technology to improve operational efficiency. One solution to address this issue is the use of a simple and cost-effective QR Code-based application. This study aims to develop and implement siMenu, an application that provides table, order, and product management solutions without integrating complex digital payment systems. The method used is Project-Based Learning (PBL), which allows the development of technical skills while designing a sustainable business model through Business Model Canvas (BMC). The results show that siMenu successfully improved operational efficiency for SMEs, reduced ordering errors, and provided an easy-to-adopt solution with low implementation costs. However, challenges in application development and building user trust remain obstacles. The conclusion of this study is that simple digital solutions like siMenu can help SMEs in the culinary sector digitally transform and stay competitive in an increasingly evolving market.  

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.