Harnessing the Power of AI and Cloud Computing for Next-Generation Web Development: A Focus on Data-Driven Generative AI

Generative AI is transforming the art and science of web engineering by automating content generation, design and development through models like GAN, VAE or Transformers. These models can produce authentic text like a writer and other media, including images, so developers would save more time in web development and improve creativity and scalability. From automated web design and content personalization to adaptive user interface or code optimization, the uses of generative AI could be limitless. Integrating AI with web engineering allows developers to generate dynamic and tailored user interface applications that adapt to the unique requirements of each user. Nevertheless, issues like data quality, bias and ethical considerations require ongoing attention to ensure responsible AI usage. Overall, generative AI can revolutionize web development for a future of innovation and more intelligent, efficient, user-centric web applications.

The rapid development of generative artificial intelligence (generative AI) has reshaped the landscape of digital entrepreneurship, particularly in value and ethics-based markets such as the halal lifestyle economy. This study examines how generative AI influences the communication practices of digital entrepreneurs operating in halal sectors including fashion, culinary businesses, health, and finance. Using a qualitative case-study approach and thematic content analysis, the research identifies three major shifts. First, the emergence of hybrid communication models that combine human creativity with AI-generated content. Second, changes in the frequency, style, and tone of brand messages tailored to value-driven Muslim audiences. Third, new dynamics in audience interaction, trust-building, and the management of authenticity within AI-assisted communication environments. The theoretical contribution of this study is the introduction of the “faith-aligned automation” model, which illustrates how AI technologies can be utilized without compromising religious and cultural values. The practical implications are directed at content strategists, platform developers, and halal business practitioners seeking to maintain ethical integrity while adopting automation. This study also outlines its limitations and proposes future research directions, particularly concerning AI governance in digital economies that are sensitive to identity.

This paper explores horizontal scaling of PHP MVC applications with session preservation for enhanced availability and resource efficiency. It covers theoretical aspects of MVC architecture, PHP in web development, session handling, and horizontal scaling methods, including load balancers, Docker, and Kubernetes. The practical methodology details environment setup, application development, session management, Dockerization, Kubernetes integration, and horizontal scaling configuration. Performance testing reveals significant improvements, showing a response time decrease from an unresponsive state at 1000 RPS (5111 ms) to 32 ms at 2500 RPS with horizontal scaling. The study contributes insights and practical guidance for highly available and scalable web applications.

Generative artificial intelligence (Generative AI) is one of the most disruptive technologies in the global digital economy. Its presence not only brings opportunities for innovation, but also poses geopolitical challenges, especially in the context of the fragmentation of the global digital economy known as the splinternet. Indonesia, with the largest digital economy potential in Southeast Asia, risks becoming a passive consumer of foreign technology that can weaken national sovereignty. This study aims to analyze the implications of global digital economy fragmentation on Indonesia's national sovereignty, evaluate the role of generative AI in supporting or weakening this sovereignty, and formulate policy strategies that can strengthen Indonesia's position in international digital economy governance. The research uses a descriptive qualitative approach with normative-empirical analysis. Data was obtained through literature studies, analysis of policy documents, and in-depth interviews with regulators, industry players, and academics. The data analysis technique was carried out by thematic analysis and content analysis of international documents and national regulations related to AI. The results of the study show that global digital fragmentation puts Indonesia in a vulnerable position as a technology adopter, with the risk of dependence on foreign platforms. This dependence has an impact on weakening data sovereignty, reduced regulatory independence, and increasing national security vulnerabilities. However, there are opportunities through three main strategies: strengthening national regulations, developing local innovations based on Indonesian data, and digital diplomacy in international forums.

As video games continue to evolve, understanding what drives player enjoyment remains a key challenge. Player reviews provide valuable insights, but their unstructured nature makes large-scale analysis difficult. This study applies generative AI and machine learning, leveraging Microsoft Phi-4 small language model (SLM) and Google Cloud, to quantify and analyze game reviews from Steam and Meta Quest stores. The approach converts qualitative feedback into structured data, enabling comprehensive evaluation of key game design elements, monetization models, and platform-specific trends. The findings reveal distinct patterns in player preferences across PC and VR games, highlighting factors that contribute to higher player enjoyment. By using Google Cloud for large-scale data storage and processing, this study establishes a scalable framework for game review analysis. The study’s insights offer actionable guidance for game developers, helping optimize game mechanics, pricing strategies, and player engagement.

This fast development of cloud-native computing and Generative Artificial Intelligence (GenAI) has facilitated the creation of scalable and intelligent applications in various fields. But current literature and practice are full of individual studies on cloud-native machine learning pipelines and Generative AI systems, creating a fragmented architecture, haphazard governance, and more complicated operation in enterprise. Specifically, no combined architectural advice exists that combines principles of cloud-native computing with foundation model-driven GenAI processes into an integrated and consistent framework. The given paper provides a systematic literature review of cloud-native AI architectures, Generative AI models, and AWS-managed AI services to reveal major patterns of design, challenges, and gaps of the current practices. It was on this basis that we have developed a consistent cloud-native reference architecture to deploy and operate Generative AI workloads on Amazon Web Services (AWS). This work has the contribution of introducing a design-oriented AWSspecific reference architecture that applies standard cloud-native principles to unify traditional machine learning pipelines and Generative AI systems. Instead of concentrating on empirical performance measurement, the study suggests architectural guidance and practical design advice that are supposed to guide the organization in designing scalable, secure, and governance-conscious GenAI deployments on AWS. Future research will involve implementation-level verification and empirical evaluation of the proposed architecture in the real-life application contexts.

The integration of consumer behavior models into bank-owned e-commerce strategies has emerged as a critical focal point for enhancing customer engagement, improving transaction volumes, and fostering competitive advantage in the digital economy. This technical review examines the theoretical foundations and practical applications of key consumer behavior models such as the Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT) within the context of bank-operated e-commerce ecosystems. Banks are increasingly leveraging e-commerce platforms not only as transactional interfaces but also as value-driven ecosystems aimed at providing personalized financial and non-financial services. However, the adoption and sustained usage of these platforms hinge significantly on understanding consumer motivation, perceived value, trust, convenience, and digital literacy. The review explores how predictive behavioral models inform digital platform design, influence user interface optimization, guide recommendation engines, and support omnichannel banking strategies. By mapping consumer psychological and sociocultural factors to technological engagement metrics, banks can better tailor user experiences, segment markets, and optimize conversion pathways. Furthermore, the paper evaluates the integration of machine learning and data analytics in modeling dynamic consumer behaviors and preferences across different demographic and regional segments. Challenges such as data privacy concerns, algorithmic bias, and the digital divide are also addressed, with proposed solutions focusing on ethical AI, inclusive design, and adaptive learning systems. Case studies from leading African and global banks illustrate diverse implementation pathways and outcomes. This review concludes that a data-informed understanding of consumer behavior, when aligned with agile technology architectures, can significantly enhance the effectiveness of bank-owned e-commerce strategies. Future research directions include the co-evolution of behavioral models with emerging technologies like blockchain, embedded finance, and generative AI.

Impedance mismatch of data flow is the major problem in the relational database when one is using the web based application development on the computer system. It effects the development of scalable and reusable web application. Due to this, the research cost of development and maintenance increases. Therefore the present work is an attempt towards an object-oriented database system by using Db4o to overcome the impedance mismatch problem. In the current work, the development of web application for Indian Postal Services by using Db4o is demonstrated on dot NET platform. Before developing the application, the authors used a Unified Modeling Language (UML) model in the form of UML class, sequence and use-case diagrams. The Db4o is used to store the object-oriented database and the performance of Db4o is observed through several object-oriented queries and corresponding results are demonstrated.

Node.js is one of the hottest open source web platforms currently available. It's built on Google Chrome's V8 JavaScript runtime engine and it allows you to write all kinds of network applications and servers in just a few lines of code. Node.js uses an asynchronous programming model built on non-blocking I/O and a single-threaded event loop. What this means, basically, is that you don't need to be concerned with awful race conditions or synchronization issues that arise when programming for a concurrent multi-user environment. This workshop is aimed mainly at web development instructors that would like to consider teaching a single programming language, JavaScript, for both client-side and server-side coding. Participants will learn how to employ Node.js on Windows, Mac OS or Linux in order to write scalable web servers and applications. Additionally, the Express web framework will be introduced in order to demonstrate how to quickly program traditional webapps and single-page applications (SPA) with the aid of jQuery, AJAX and RESTful web services. The resulting programs will be usable from any modern web browser, including those found in desktop and laptop computers, and mobile devices such as tablets and smart-phones. Participants should have prior working knowledge of client-side (running on a browser) JavaScript and HTML. More information: http://node.arielortiz.info/ Laptop Required.

As globalization progresses at a rapid pace, the dramatic advancements in AI technology have significantly accelerated its integration into global education systems. This study explores the interplay between AI and international education, analyzes the educational transformations driven by AI adoption. We examine the integration of AI technologies—such as natural language processing (NLP), machine learning, and generative AI—in addressing language barriers, personalizing learning experiences, optimizing teaching management, and fostering global educational collaboration. A systematic technical implementation framework is presented, encompassing local content processing, AI-generated content (AIGC) via cloud computing, and efficient multi-platform distribution. Case studies of leading AI platforms (e.g., ChatGPT, Grok, Qwen) demonstrate their capacity to enhance accessibility and engagement. Critical risks—including privacy vulnerabilities, algorithmic bias, cultural conflicts, and ethical concerns—are rigorously assessed, with mitigation strategies proposed. Our findings reveal that AI-driven international education not only enhances teaching efficiency and cost-effectiveness but also promotes equitable access and cross-cultural awareness. The research provides theoretical guidance for the future development of international education.

systems across diverse industries. Integrating these technologies fundamentally reshapes customer engagement strategies, enabling organizations to achieve unprecedented levels of personalization, automation, and service delivery optimization.

Many are seeking to position current technological developments as promising to “transform” higher education as we know it. Technologies such as empathic and socially intelligent robots, generative AI, and quantum computing are all said to be “game changers” for the work of colleges and universities. Are they? Given the long history of hype and disappointment related to educational technologies (Watters, 2021), this chapter explores this narrative, especially about AI and its promise. It explores the challenges leaders and those in decision roles face, given the speed at which these technologies develop. A particular focus is on the challenge demands for new forms of cognitive development needed to support the development of quantum computing.

Apple production, a cornerstone of global agriculture, faces significant threats from diseases such as apple scab, fire blight, powdery mildew, and cedar apple rust, which reduce yield, quality, and sustainability. Early and accurate disease classification is essential to mitigate economic losses and ensure food security. This paper evaluates traditional and modern approaches to apple plant disease classification, including manual visual diagnosis, image-based techniques, and molecular methods like PCR and ELISA. While traditional methods are accessible but error-prone, advanced technologies such as machine learning, deep learning, and sensor-based systems offer high accuracy and scalability, achieving up to 95% detection rates in controlled settings. Challenges, including limited labeled datasets, high computational costs, and poor model generalization across apple varieties and regions, hinder widespread adoption. Emerging trends, such as generative AI, explainable AI, drone-based monitoring, and edge computing, promise to enhance real-time diagnostics and accessibility. The paper also explores opportunities for integrating these technologies with precision agriculture to optimize orchard management and promote sustainability. By synthesizing current methods, technologies, and research gaps, this paper provides a comprehensive roadmap for researchers, farmers, and policymakers to advance apple disease management, fostering sustainable agricultural practices and global food security.

This paper presents the possibilities of using software based on the model of cloud computing as a scalable web application server. In this paper a performance issue for scalable Cloud Computing based systems was analyzed in the context of load balancing between the different configurations of resources. An application of the EUCALYPTUS system as well as the results of the performance tests, both for the case of the use of virtual machines with different number of resources and the use of Apache mod_proxy_balancer software were presented.

Благодаря быстрому развитию информационных технологий и популяризации Интернета во всем мире сформировалась новая экономическая форма — цифровая экономика. Цифровая экономика основана на цифровых технологиях и охватывает такие области, как электронная коммерция, цифровые платежи, облачные вычисления и анализ больших данных, что оказывает глубокое влияние на экономическое и социальное развитие. В эту цифровую эпоху цифровая экономика играет важную роль в содействии развитию региональной экономики. Однако вопрос о том, как эффективно использовать цифровую экономику для содействия региональному экономическому развитию, остается актуальным. Целью данного исследования является изучение роли цифровой экономики в продвижении региональной экономики и путей ее развития. Анализируя взаимосвязь между цифровой экономикой и региональной экономикой, данная статья раскрывает механизм воздействия цифровой экономики на региональное экономическое развитие и предоставляет эффективные рекомендации и предложения по региональному экономическому развитию. Due to the rapid development of information technology and the popularization of the Internet throughout the world, a new economic form has emerged — the digital economy. The digital economy is based on digital technologies and covers areas such as e-commerce, digital payments, cloud computing and big data analysis, which has a profound impact on economic and social development. In this digital age, the digital economy plays an important role in contributing to the development of the regional economy. However, the question of how to effectively use the digital economy to promote regional economic development remains relevant. The purpose of this study is to study the role of the digital economy in promoting the regional economy and ways to develop it. Analyzing the relationship between the digital economy and the regional economy, this article reveals the mechanism of the digital economy's impact on regional economic development and provides effective recommendations and suggestions for regional economic development.