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This paper discusses in depth the role of accounting in business decision-making in the digital era, as well as the challenges and opportunities faced by the accounting profession in the context of rapid and complex technological developments. In the modern business world, accounting information plays a crucial role, not only as a financial reporting tool but also as a foundation for strategic analysis that can influence the direction and policies of an organization. The issues raised pertain to the importance of timely and accurate accounting information in supporting managerial decision-making, as well as how this information can be used to enhance the performance and competitiveness of companies. The main objective of this research is to explore how digitalization and technological innovations, such as artificial intelligence (AI), big data analytics, and cloud-based information systems, affect accounting practices and their impact on business decision-making. This research also aims to identify the challenges arising from technological changes, including data security issues, the necessary technological skills, and regulatory changes that accountants must face. The methodology employed in this research is a normative approach with descriptive analysis, which includes literature studies and analysis of various relevant secondary data sources. Additionally, this research presents several case studies to demonstrate the application of theory in real practice and its impact on decision-making. The findings indicate that although digitalization brings many benefits in terms of efficiency and accuracy, there are serious challenges to be faced, such as the increased risk of data breaches and the need for higher technological skills among accounting professionals. The conclusion drawn from this research is that to optimally leverage the potential of accounting in supporting business decision-making, companies must invest in training and skill development for their accountants. Furthermore, the importance of implementing sustainable accounting practices is increasingly gaining attention, especially in the context of social and environmental responsibility. Thus, accounting not only functions as a supporting tool but also as a strategic element that adds value to companies in facing the complexities and uncertainties of the future.

Big Data Analytics has gained significant popularity in recent years, with many companies integrating it into their information technology roadmaps to enhance business performance. However, surveys indicate that Big Data Analytics demands substantial resources, including technology, costs, and talent, which often leads to failures in the initial stages of implementation. This study proposes a VGG6 architecture approach, intended to provide a framework for the initial implementation of Big Data Analytics. The study's outcomes include the implementation of the VGG6 architecture for processing images of aromatic plants using Python. Furthermore, this approach enabled the development of a Minimum Viable Product (MVP) solution that adheres to general Big Data principles, such as the 3Vs (Volume, Velocity, and Variety), and encompasses key technological components: 1) Data Storage and Analysis, 2) Knowledge Discovery and Computational Complexity, 3) Scalability and Data Visualization, and 4) Information Security.

Bridging the gap between theoretical knowledge and practical application remains challenging in big data education. Our paper proposes a platform where students actively participate in a role-based learning (RBL) exercise designed to simulate real-world big data projects. This RBL exercise assigns each student participant to a business analyst role tasked with eliciting requirements or a customer role that provides those big data requirements. We conducted RBL sessions for postgraduate and undergraduate students learning big data analytics/data warehousing. Through role-playing in a collaborative environment, students face challenges such as unclear objectives, data privacy concerns, and evolving requirements. We evaluated the effectiveness of RBL simulations through brainstorming sessions, which verified that the students achieved the learning outcomes through RBL exercises. We also collected students’ feedback through a survey and found the RBL experience helped us understand the big data requirement elicitation skills, highlighting the significance of communication and collaboration skills. Further, we have evaluated students through a final exam question, and identified that students who participated in the RBL exercise outperformed in the big data requirement elicitation question. In summary, our research demonstrates that this RBL approach offers a valuable learning experience by enabling students to directly experience the complexities of big data requirement elicitation and identify the future requirements or challenges that encourage them to acquire the required skills.

This study analyzes and optimizes production systems in the Industry 4.0 context, examining the fundamental shift from centralized, push-based production models to decentralized, adaptive, pull-based approaches. The research employs a mixed-method approach combining comprehensive literature review and multiple case studies across manufacturing sectors. Findings reveal that integration of Internet of Things (IoT), cyber-physical systems, artificial intelligence, and big data analytics enables real-time communication between production components, product personalization, and faster decision-making. Despite significant benefits in efficiency, flexibility, and competitiveness, implementation challenges persist, including high initial investment, employee resistance, technical expertise limitations, and integration complexity. Optimization approaches such as mixed-integer linear programming, digitally-integrated Lean Six Sigma, and digital twin simulations effectively enhance performance indicators including flexibility, reliability, and energy efficiency. The study concludes that successful production system transformation requires an integrated strategy encompassing process engineering, digital competency development, change management, and continuous evaluation to ensure sustainable optimization in the digital era

The digital transformation within the public sector has shifted from an optional advancement to a primary parameter for local government success in managing dynamic metropolitan areas. This research examines the acceleration of Smart Governance in Surabaya through the implementation of the mandatory non-cash parking policy on public roads. Using a qualitative approach with a descriptive-analytical design, the study explores how this transition redefine the relationship between the government, parking attendants, and citizens. Findings indicate that the policy effectively minimizes budget leakage and enhances fiscal transparency. The integration of digital payment systems has transformed traditional parking management into a data-driven service, fostering public trust through accountable financial tracking. Furthermore, the shift from cash to digital transactions has successfully professionalized the role of parking attendants within the urban ecosystem. However, success relies heavily on consistent infrastructure readiness and public literacy. The study concludes that Surabaya's non-cash parking model serves as a vital instrument for strengthening Regional Original Revenue (PAD) while modernizing urban governance. These implications suggest that digital integration is not merely a technical change but a fundamental shift in bureaucratic culture. This model provides a strategic framework for other Indonesian metropolitan cities aiming to implement similar digital-based public service innovations and sustainable smart city governance.

This article investigates the evolving role of consumer behavior in shaping entrepreneurial marketing strategies in the digital age. The proliferation of social media, online platforms, and big data analytics has transformed how entrepreneurs engage with consumers. The study delves into how entrepreneurs use consumer insights to create personalized marketing strategies, foster customer loyalty, and enhance brand value. A qualitative analysis of case studies from various industries illustrates the impact of digital tools on marketing effectiveness. The paper provides insights on how entrepreneurs can better align their marketing approaches with changing consumer preferences in a rapidly evolving digital landscape.

The high number of fraud cases that occur in Indonesia has caused large amounts of losses to be suffered by the country. Thus, finding effective methods to detect fraud is still the focus of many parties, especially the Government. Therefore this research was carried out. This research aims to analyze the implementation of big data to minimize froud. This research uses the Literature Review method. Contains reviews, summaries and the author's opinion about several sources in the library, the results obtained from this research were collected from previous research, the use of big data