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Optimizing human resource (HR) performance through a business process reengineering (BPR) approach is a crucial strategy in a competitive and dynamic industrial environment. This study qualitatively examines through a literature review how BPRs radically redesign business processes to improve productivity, quality, time efficiency, and reduce operational costs, with a focus on HR aspects such as recruitment, training, performance appraisal, and career development. The BPR theory by Michael Hammer and James Champy emphasizes the principles of results-based workflow reorganization, the integration of information technology such as ERP and AI, and the empowerment of HR to eliminate task redundancy. In the Indonesian industrial context, the integration of BPR with digital transformation supports Industry 4.0, where HR acts as a catalyst for innovation through adaptive skills and cross-functional collaboration. The study results show that BPR implementation strategies including as-is process analysis, to-be design, change management, and continuous evaluation increase employee motivation, retention, and sustainable competitive advantage. Case studies such as PT Telkom Indonesia and PT Cahaya Mega Group demonstrate efficiency increases of up to 100%. This approach not only streamlines operations but also builds an organization resilient to market and technological disruption.

This study aims to analyze the efforts made by the Sukabumi City Civil Service Police Unit (Satpol PP) in enforcing Mayor Regulation Number 05 of 2014 concerning restrictions on the operating hours of night entertainment venues. The regulation was implemented to maintain public order, reduce social disturbances, and ensure community comfort, particularly during nighttime hours in urban environments. Using a sociological legal approach with qualitative methods, data were collected through interviews with relevant stakeholders, field observations, and literature reviews. The findings reveal that Satpol PP has undertaken various enforcement efforts, including routine patrols to monitor venue compliance, educational outreach to business owners regarding regulations, and administrative sanctions such as written warnings and temporary closures for violators. Despite these initiatives, several challenges hinder the optimal enforcement of the regulation. These include limited human resources and operational infrastructure within Satpol PP, inconsistent public awareness of the regulation, and resistance from certain business actors who view the regulation as a barrier to economic activity and local tourism development. Moreover, coordination between relevant agencies, such as tourism and licensing departments, remains suboptimal. This study emphasizes the need for stronger inter-agency synergy, increased budget allocation, and ongoing public education to foster better compliance. It also suggests capacity-building programs for enforcement officers and the implementation of community-based monitoring systems to enhance transparency and support. In conclusion, although Satpol PP has shown commitment to implementing the regulation, the effectiveness of enforcement can be significantly improved through strategic resource optimization, cross-sector collaboration, and a participatory approach involving both authorities and the community.

Enterprise Resource Planning (ERP) systems have become the operational backbone of many modern companies, not only as a data integration tool but also as a crucial pillar in management control systems (MCS). This study aims to comprehensively analyze the impact of ERP implementation on operational efficiency and corporate accountability. Using a qualitative approach through literature study and case review, this study explores how ERP facilitates real-time and integrated information flow, which in turn improves managerial decision-making capabilities, resource optimization, and increased transparency and accountability at various levels of the organization. The results show that ERP contributes significantly to increased efficiency through process standardization and reduced redundancy, and strengthens accountability by providing clear audit trails and reliable data. However, the success of the implementation is highly dependent on factors such as top management support, adequate employee training, and alignment with business strategy.  

This paper explores the application of quantum-inspired optimization algorithms in the training of large-scale Graph Neural Networks (GNNs) within distributed cloud-edge environments. GNNs have gained significant attention due to their ability to model complex relationships in graph-structured data, yet their training presents challenges such as high computational demand, inefficient resource allocation, and slow convergence, especially for large datasets. Traditional meta-heuristic algorithms, while useful, often face scalability and performance issues when applied to such large-scale tasks. To address these challenges, we propose a quantum-inspired meta-heuristic algorithm that leverages quantum principles, such as superposition and entanglement, to enhance optimization processes. The algorithm was integrated into a hybrid cloud-edge system, where computational tasks are dynamically distributed between edge nodes and the cloud, optimizing resource utilization and reducing latency. Our experimental results demonstrate significant improvements in training speed, resource efficiency, and convergence rate when compared to traditional optimization methods such as Genetic Algorithms and Simulated Annealing. The quantum-inspired algorithm not only accelerates the training process but also reduces memory usage, making it well-suited for large-scale GNN applications. Furthermore, the system's scalability was enhanced by the hybrid cloud-edge architecture, which balances computational load and enables real-time data processing. The findings suggest that quantum-inspired optimization algorithms can significantly improve the training of GNNs in distributed systems, opening new avenues for real-time applications in areas such as social network analysis, anomaly detection, and recommendation systems. Future work will focus on refining these algorithms to handle even larger datasets and more complex GNN architectures, with potential integration into edge devices for enhanced real-time decision-making.

The port is a vital infrastructure in the global logistics chain that connects sea and land transportation. The efficiency of cargo loading and unloading operations at the port is a critical factor influencing the smooth flow of goods and overall logistics costs. In this context, the use of Business Intelligence (BI) as an integrated technological system to support data collection, analysis, and presentation is becoming increasingly important for optimizing data-driven decision-making in port environments. XYZ Port, as one of the strategic ports in Indonesia, faces challenges in managing complex loading and unloading operations with increasing cargo volumes. The implementation of a BI dashboard offers a solution to visualize operational data in real-time, identify bottlenecks, and optimize resource allocation. This study aims to implement a BI dashboard for cargo handling operations at XYZ Port. The specific objectives include identifying information needs in cargo handling operations and developing a BI dashboard that suits the characteristics of port operations. The findings indicate that the dashboard effectively supports real-time decision-making and enhances operational efficiency. The study also highlights the importance of addressing technological infrastructure, human resource readiness, and system integration challenges in BI implementation.

The function of Prosecutorial Intelligence (Intel Kejaksaan) holds a crucial strategic role, not only in supporting prosecution duties but also in crime prevention, safeguarding national development, and recovering state assets. Despite having a strong legal basis and a broad mandate, this function often faces operational challenges, data integration issues, and resource optimization constraints that limit its effectiveness within the dynamic law enforcement ecosystem. This research aims to deeply analyze the role and challenges of Prosecutorial Intelligence and formulate a model for optimizing its function to enhance the effectiveness of law enforcement in Indonesia. The research methodology employed is normative and sociological juridical with a qualitative approach, gathering data through literature review, regulatory study, and in-depth interviews with practitioners and academics. The findings indicate that the optimization of the Prosecutorial Intelligence function requires three main pillars: (1) Enhancing the capacity and professionalism of human resources (HR) through modern intelligence training and digital forensics. (2) Integrating and ensuring interoperability of the intelligence information system with other law enforcement agencies (Police, KPK, PPATK) to build a comprehensive intelligence big data. (3) Expanding the spectrum of intelligence operations, shifting from a traditional focus on corruption crimes to transnational crimes, cybercrime, and securing strategic national investments. This optimization is expected to transform Prosecutorial Intelligence into a proactive, data-oriented strategic early warning system capable of supporting Prosecutors in making evidence-based decisions, thus achieving effective, just, and impactful law enforcement for the community.

The improvement of education quality has become a major challenge in modern education, where elementary schools are required to continuously adapt to the developmental needs of students and societal demands. This study aims to describe and analyze the management strategies for improving education quality at SD Negeri 64 Prabumulih, as well as to identify the supporting factors and obstacles influencing its implementation. The research method used is qualitative with a descriptive approach, employing data collection techniques such as in-depth interviews, observation, and document analysis. The results indicate that the management strategies implemented at SD Negeri 64 Prabumulih include participatory planning, teacher capacity building, resource optimization, and continuous evaluation. The main supporting factors for success are visionary school leadership, teacher commitment, and community support, while the challenges faced include limited infrastructure, a high administrative workload for teachers, and uneven parental involvement. This study provides an important contribution to enriching the understanding of the implementation of quality management in elementary schools with limited resources.

Optimizing human resources (HR) in digital marketing through the synergy between creativity and technology is an important strategy to create effective and innovative marketing campaigns in the digital era. Creativity plays a crucial role in producing engaging and relevant content, which is able to build an emotional connection with consumers as well as strengthen the brand identity. Meanwhile, technology allows for personalization, data-driven analysis, and efficiency in the implementation of marketing strategies. This study examines how the combination of human resource creativity and the use of digital technology can create a competitive advantage for companies. The results of the study show that companies that successfully integrate these two elements can increase consumer engagement, customer loyalty, as well as the effectiveness of marketing campaigns. From a conceptual perspective, this approach is changing the way companies view innovation and cross-functional collaboration within organizations, which in turn improves responsiveness and adaptability to market changes. The practical implications of this research are the importance of investing in the development of creative and skilled human resources in technology, to create a sustainable digital marketing strategy and be able to compete in an increasingly competitive global market.

Digitalization has become a transformative force reshaping how organizations innovate and sustain competitive advantages in an interconnected global economy. This study explores the intricate relationship between business digitalization, innovation capabilities, and sustainability outcomes. Employing a comprehensive literature review, it examines how digital transformation fosters innovative practices and supports sustainable business models. Key findings reveal that integrating digital technologies, such as artificial intelligence, IoT, and blockchain, significantly enhances innovation capacity by accelerating product development cycles, improving decision-making precision, and fostering collaborative innovation ecosystems. Moreover, digitalization optimizes resource utilization, minimizes environmental impact, and strengthens stakeholder engagement, contributing to measurable economic, environmental, and social sustainability outcomes. The synergy between digital transformation and sustainability initiatives provides organizations with strategic advantages, including improved operational efficiency, customer loyalty, and competitive positioning. However, challenges such as implementation barriers, balancing digital-sustainable priorities, and managing unintended environmental impacts persist. Future research should focus on empirical validation, industry-specific applications, and longitudinal studies to further elucidate the pathways through which digitalization supports sustainable innovation and long-term business resilience. This study underscores the imperative for organizations to strategically align digital transformation with sustainability objectives, ensuring their future success in a rapidly evolving business environment.