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The era of the Industrial Revolution 4.0 and Society 5.0 brings significant changes in various aspects of life, including education. Islamic educational institutions, as vital entities in shaping the character and knowledge of younger generations, are required to undergo digital transformation to improve governance and management quality. Management Information Systems (MIS) serve as a primary tool that can integrate administrative processes, data management, and decision-making effectively, efficiently, and accountably. This study discusses the optimization of MIS in strengthening the governance of Islamic educational institutions, focusing on the challenges and opportunities faced in this era of advanced technology. The research method employed is qualitative descriptive, reviewing literature and previous studies concerning MIS and the management of Islamic educational institutions amidst digital technological dynamics. The findings indicate that optimizing MIS demands developing human resource capacities, improving technological infrastructure, and fostering an organizational culture adaptive to digital change. Although challenges such as infrastructure limitations, cultural resistance, and data security issues exist, opportunities arising from technologies like cloud computing and big data pave the way for more modern and competitive institutional management. Strengthening governance through MIS not only enhances efficiency but also supports accountability and transparency in line with Islamic values that emphasize honesty and responsibility. Thus, optimizing MIS is a key strategy to ensure Islamic educational institutions can adapt and thrive in the Industrial Revolution 4.0 and Society 5.0 era.

Digital transformation is one of the essential needs in the development of sharia cooperatives in the Industrial Revolution 4.0 era. Rapidly developing information technology requires microfinance institutions such as cooperatives to adapt, in order to remain competitive, efficient, and relevant in meeting the needs of their members. Two main technologies that play an important role in this transformation are big data and cloud computing. This article aims to examine in depth how the use of big data and cloud computing can support the digital transformation process in sharia cooperatives. Using a literature review approach from various scientific sources, this article analyzes the basic concepts, potential benefits, case studies, and challenges of implementing both technologies in the context of sharia-based cooperatives. The results of the study show that big data can improve data-based decision making, risk management efficiency, and personalization of services to members. Meanwhile, cloud computing provides flexibility, cost efficiency, and accessibility of cooperative information systems widely, even in areas with minimal IT infrastructure. However, the success of implementing this technology is greatly influenced by the readiness of human resources, digital infrastructure, and compliance with sharia principles. This article also provides practical recommendations and a further research agenda as a contribution to the development of technology-based sharia cooperatives.    

Digital transformation in Information Technology (IT) governance has become a crucial aspect in improving the efficiency of public services, particularly within the Department of Community and Village Empowerment, Population, and Civil Registration of North Sumatra Province. This study aims to analyze the implementation of digital transformation in IT governance using the COBIT 2019 framework. The research method includes the analysis of regulations, the role of IT, procurement models, implementation methods, and technology adoption strategies applied by the department. The findings show that IT implementation is predominantly strategic in nature, supporting the digitization of population services and enhancing data transparency. The IT procurement model comprises a combination of outsourcing (30%), cloud computing (30%), and insourcing (40%) to balance efficiency and system control. Agile methodology is the most dominant implementation method (50%), followed by DevOps (35%) for maintenance and traditional approaches (15%) for more structured projects. The department primarily adopts a "follower" technology adoption strategy (75%), reflecting a selective approach to digital innovation. Based on COBIT 2019 evaluation, the BAI (Build, Acquire, and Implement) domain is the main focus, with high scores in solution identification and improvement management (90) and change management (100), indicating the department’s readiness to adopt digital systems. However, challenges remain in information security, inter-agency data integration, and human resource readiness. The digital transformation of IT governance at the department has been systematically implemented, supporting the improvement of population service efficiency. Enhancements in security, infrastructure, and the strengthening of IT governance policies are necessary to optimize and sustain digital transformation implementation.

The rapid evolution of digital technology has reshaped workforce training paradigms, with Artificial Intelligence (AI) emerging as a transformative tool. This study investigates the opportunities and challenges of implementing AI-based training systems to enhance workforce skills in the digital era. Data were collected through surveys, in-depth interviews, and focus group discussions involving industry practitioners, AI developers, and workers. The results indicate a training effectiveness average of 70.2% (SD = 9.8) and satisfaction levels averaging 75.4% (SD = 8.5). Logistic regression analysis revealed a significant positive relationship between AI adoption and skill improvement, with a success probability of 68.9%. Despite these promising outcomes, challenges such as limited digital infrastructure, low digital literacy, and resistance to technology adoption persist, particularly in developing regions. This study provides strategic recommendations for inclusive digital transformation, emphasizing collaborative efforts between governments, private sectors, and educational institutions. These findings contribute to theoretical and practical knowledge for advancing AI-based training systems and fostering a sustainable, equitable workforce transformation.

The advancement of networking and communication technologies has escalated the IoT and edge computing integration by leaps and bounds. This paper provides a review of the current trends, technologies and issues concerning IoT and edge computing. Looking at the key application areas of smart cities, healthcare, industrial IoT and smart grids this paper demonstrates how edge computing solves the problems of cloud computing such as latency, bandwidth and privacy. The survey also reveals present day constraints such as the lack of standards for scalability, integration problems, and lack of strong data protection measures. This work can be considered as a reference source for researchers and practitioners since it reveals the relationship between IoT and edge computing and gives an idea of further advancements.

Digital transformation has become a key driver of business competitiveness in the modern economy. This study explores how companies leverage digital technologies such as artificial intelligence, big data analytics, and cloud computing to improve operational efficiency and customer engagement. By analyzing case studies of leading global firms, the research highlights best practices and challenges in digital adoption. The findings suggest that businesses that embrace digital transformation gain a strategic advantage in an increasingly digitalized marketplace.

Internet Network is one of the fields in informatics and electronics engineering which is now growing rapidly due to the issue of the industrial revolution 4.0 which is increasingly closely related to Cloud computing technology and the Internet of Things. Without resources and knowledge about computer networks, the Internet of things and Cloud computing are quite impossible to design. Computer networks give birth to internet access which is very much needed by every agency and even the entire community in the world. Especially in educational institutions such as Madrasah Aliyah (MA) Raden Fatah, which is located in Kalasan, Yogyakarta when in the era of the Covid-19 pandemic, it faces the challenge of disruption from offline learning to online learning. To answer the demands of the times, MA Raden Fattah is very enthusiastic in developing its institution towards a quality smart school. The network infrastructure available at MA Raden Fattah has not been optimized, so through this service, network design and management are carried out so that the need for access points that help students and teachers can be met. This service has succeeded in increasing the number of access points, optimizing the management of internet network resources at MA Raden Fattah, and improving the quality of teaching and learning services at the institution

As industries increasingly integrate cloud-based Industrial Control Systems (ICS), the cyber threat landscape expands. While cloud computing offers scalability, cost efficiency, and remote accessibility, it also introduces security vulnerabilities that adversaries can exploit. This study explores AI-driven threat detection models, encryption techniques, and best practices to enhance ICS resilience. Key security measures, including intrusion detection systems, anomaly detection, and robust encryption mechanisms, are analyzed to mitigate cyber risks. The findings highlight the effectiveness of AI-based security solutions in identifying and preventing attacks, ensuring the reliability and integrity of ICS in cloud environments.  

Task scheduling in cloud computing environments is a crucial aspect in optimizing resource allocation and improving system efficiency. This research aims to analyze trends in task scheduling algorithms in cloud computing using a Systematic Literature Review (SLR) approach on various scientific publications published between 2018 and 2025. The results of the study show that Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Genetic Algorithm (GA) algorithms are the most commonly used methods in solving task scheduling problems. PSO stands out as an effective algorithm due to its ability to find global optimal solutions, handle non-linear and multimodal problems, and its efficiency in managing computational resources. Additionally, various studies have shown that optimization of scheduling algorithms can be achieved through a combination or modification of existing methods to improve system performance. This study provides in-depth insights into the development of scheduling algorithms in cloud computing and opens up opportunities for further research in developing more innovative and adaptive approaches.

The rapid growth of information technology, including cloud computing, the Internet of Things, and artificial intelligence, is driving increased energy consumption and carbon emissions in the technology sector. A report by the International Energy Agency (IEA) projects that global data center electricity consumption will more than double, reaching approximately 945 TWh by 2030, or about 3% of global electricity consumption. A Deloitte study even estimates that data centers could contribute around 4% by 2030, primarily driven by the growing use of artificial intelligence. Beside physical infrastructure, software also significantly contributes to energy consumption, necessitating Green IT and Green Software approaches to reduce environmental impact. This research aims to identify and classify energy metrics used in the literature, analyze the trade-offs between energy consumption and system performance, and summarize relevant best practices for application in industrial settings. This research uses the Systematic Literature Review (SLR) method, referring to the Kitchenham protocol. The search was conducted on the IEEE Xplore, ACM Digital Library, ScienceDirect, SpringerLink, and arXiv databases for articles published between 2021 and 2025 that included empirical data or conceptual models related to the energy efficiency of information systems. From the screening process, a number of articles were obtained and analyzed thematically. The research results show that energy metrics vary from hardware-based measurements (power meter) to estimation models (GSMM, GSMP). A trade-off was also found between energy savings and performance, necessitating a multi-objective optimization approach. This research contributes by providing a framework for classifying energy metrics, visualizing measurement method trends, and offering methodological recommendations that can be integrated into industrial practice. The implications of this research are to support digital sustainability efforts while simultaneously reducing the organization's operational costs.

The term "cloud computing" refers to the delivery of numerous services via the Internet. Because of providers that provide cloud services, users can store files and media on faraway servers and subsequently access the items online. Due to the lack of location requirements, this enables anyone to watch them remotely. This design is currently beginning to be implemented in the sphere of education, particularly in universities. In order to determine the factors influencing the adoption of cloud computing in education, previous academics have employed the technology adoption theory, which is discussed in this study. The purpose of this study, which is a systematic literature review, is to identify and assess knowledge gaps about the factors impacting the adoption of cloud computing in education. To fill in any gaps and add to the body of knowledge already in existence, this study will therefore enhance the information by offering a complete examination of the material that is already available.

Pengembangan sistem operasi pada platform terdistribusi, terutama dalam konteks Cloud Computing, memainkan peran penting dalam mengelola sumber daya komputasi secara efisien. Manajemen terdistribusi mengacu pada penggunaan terintegrasi dari berbagai komponen di berbagai lokasi, menghadirkan tantangan yang signifikan dalam mengelola dan memantau sumber daya yang tersebar. Komputasi awan menawarkan solusi infrastruktur fleksibel yang memungkinkan pengguna mengakses sumber daya komputasi tanpa memerlukan manajemen infrastruktur fisik. Penelitian ini bertujuan untuk mengoptimalkan manajemen terdistribusi dalam sistem operasi komputasi awan dengan memanfaatkan algoritma pembelajaran mesin untuk meningkatkan efisiensi alokasi sumber daya dan meningkatkan keamanan data. Pengumpulan data dilakukan melalui metode observasi sistematis dan tinjauan pustaka. Temuan menunjukkan bahwa penerapan algoritme prediktif di lingkungan cloud secara signifikan mengurangi waktu respons dibandingkan dengan metode manual dan memperkuat perlindungan data melalui deteksi intrusi yang ditingkatkan. Selain itu, sistem berbasis pembelajaran mesin memungkinkan skalabilitas yang lebih baik dan adaptasi yang lebih cepat terhadap permintaan sumber daya dinamis tanpa waktu henti sistem. Makalah ini menyumbangkan wawasan berharga dalam mengoptimalkan kinerja komputasi awan melalui manajemen sumber daya terdistribusi yang ditingkatkan.

This research aims to analyze the influence of the application of information technology on increasing the efficiency of business processes in the banking sector. In an increasingly competitive and dynamic business environment, operational efficiency is one of the keys to success for banks. The application of information technology through various digital systems, such as Internet Banking, Mobile Banking, and cloud computing-based platforms, has been proven to speed up transactions and reduce operational costs. Apart from that, automating business processes through ERP and CRM also increases accuracy and makes data-based decision making easier. However, the implementation of this technology faces challenges, such as limited technical skills and organizational cultural resistance. However, proper use of IT can increase productivity, customer satisfaction and strengthen the bank's competitive position. This research provides insight into the importance of IT investment in supporting digital transformation and operational efficiency in the banking sector.

Digital transformation in village governance has become a primary strategy for enhancing efficiency and effectiveness in human resource (HR) management. This study aims to analyze the implementation of digital technology in village government HR management and its impact on productivity and administrative efficiency. Employing a systematic literature review method, this research examines implementation trends, success factors, challenges, and optimal strategies for digitalization in HR management at the village level. The findings indicate that the adoption of technologies such as electronic Human Resource Management (e-HRM), cloud computing, and village information systems contributes to faster administration, increased accountability, and optimized performance of village officials. However, challenges remain in technology adoption, including low digital literacy among village officials, limited information and communication technology (ICT) infrastructure, as well as regulatory and policy constraints. To overcome these hurdles, a comprehensive strategy is required, encompassing capacity building through training, strengthening digital infrastructure, and fostering collaboration among central government, village governments, and the private sector. With appropriate policy implementation, the integration of digital technology in village-level HR management can improve public service quality and support more modern and responsive governance.

As cloud computing advances, organizations' IT infrastructure and application deployment processes are moving to the cloud because cloud computing provides everything as a service over the Internet. The performance of a cloud-based application is based on proper datacenter selection and workload distribution within the selected datacenter. Service broker policies are used for suitable datacenter selection, and load balancing algorithms(LBA) are applied to distribute workloads. This paper is to evaluate the effect of a proposed service broker policy (PSBR) on the performance of cloud-based applications with LBA. To achieve the objective, the behavior of the TikTok application was modeled using the worldwide users’ statistics on the cloud simulation framework, namely CloudAnalyst. As a result, the average response time and data center processing time are measured. Next, the PSBR provides better results than the existing service proximity-based policy. This paper supports cloud service providers' benefits, from coordination between data center configuration, data center selection, and workload distribution to cloud users' identification of the appropriate procedures for their organization or application. PSBR with Active Monitoring had the best average response time of 75.1 ms, while SPR consistently exhibited higher average times across all algorithms, with the highest being 84.5 ms for Round Robin. Under the PSBR policy, Throttled had the lowest average processing time (4.67), while Round Robin had the highest (5.72). Similarly, under the SPR policy, Throttled maintained its efficiency with the lowest average (4.8), while Round Robin showed the highest (5.79).

This study examines the adoption of cloud computing in Small and Medium Enterprises (SMEs) with a focus on analyzing trends, theories, and factors influencing adoption during the period from 2011 to 2020. Using a systematic literature review approach, this research analyzes 76 articles published during this period, aiming to provide a deeper understanding of data analysis techniques, cloud computing services commonly studied, and key factors driving or hindering adoption. The findings reveal that the most frequently used analysis techniques are Partial Least Squares Structural Equation Modeling (PLS-SEM) and interpretative analysis. The most analyzed cloud computing service is Software as a Service (SaaS), while the primary factor driving adoption is cost savings. This study also identifies that the majority of studies are not based on clear theoretical frameworks, and research has been predominantly focused in the Asian region. The findings offer insights for future research on developing cloud computing implementation in SMEs, as well as factors to consider in accelerating the adoption of this technology among SMEs globally.

This work investigated how artificial intelligence (AI) and cloud computing are related to cost control in smart manufacturing. It aims to show how these technologies improve manufacturing environments' decision-making and cost efficiency for better management accounting. The study thoroughly examined the literature for the qualitative research methodology. The cloud computing benefits from lowering operating costs, the use of AI in predictive maintenance, and the incorporation of these technologies into management accounting systems are only key area and trends from the thematic analysis. According to the results, offering scalable and flexible computing resources enabled companies to quickly adjust to shifting demands of the market, cloud computing greatly reduced costs. Yet, the study also emphasized the difficulties in the management of the resources, such as the possibility of inefficiencies and higher expenses due to inefficient resource distribution. Also, AI technologies enhance the efficiency and accuracy of accounting procedures, freeing up professionals for the concentration on strategic duties such as financial analysis and decision support. The report suggested that to reduce and avoid inefficiencies, businesses should carefully manage their cloud resources. For the improvement of operational efficiency and decision-making, businesses were required to include AI-driven solutions into their management accounting systems. The study also found that enterprises should give priority to implementing cloud computing and AI technologies to stay competitive in the quickly shifting smart manufacturing market. These technologies provide a substantial area for innovation in cost management.

This article discusses the importance of innovation in management control systems in the digital era. During the pandemic, significant shifts occurred in business, education, and public services, pushing organizations to adopt new technologies such as artificial intelligence (AI) and cloud computing to enhance efficiency and competitiveness. The article also addresses challenges companies face in managing cybersecurity risks, data privacy, and the need for robust regulations to protect personal information. Additionally, digital technologies like e-learning play a crucial role in facilitating the learning and personal development process, especially during the pandemic. Collaboration between sectors and nations is key to addressing these global challenges.

Optimizing Windows-based operating systems for databases in Cloud and Edge Computing environments is very important to increase data management efficiency and performance. In this study, we discuss ways to optimize Windows in both environments. In the Cloud environment, the main focus is on data management using services such as Google Drive, while in the Edge environment, optimization is carried out using Windows IoT Core and Windows IoT Enterprise. Of these two, we optimize Windows IoT Enterprise more because it is more directed towards Edge computing. Our research results show that by implementing the right optimization and efficient performance results, database performance can be significantly improved, which provides great benefits for individual users and society

Technological developments in the digital world have now begun to increase the use of operating systems such as Android which are often used on electronic devices such as smartphones and tablets, penetrating various fields of human life. The use of these devices is essential in facilitating various tasks, especially digital ordering and transactions. This integration provides better transaction protection, more effective usage, and benefits and convenience. Cloud computing makes it easy and efficient to integrate digital ordering applications into payment systems. Observations show that these integrations provide user convenience and purchase trends, assist marketing strategies, and generate more accurate business decisions. If carefully developed and implemented, this integration has great potential to change the way business is done in the digital age.