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The primary focus of this research is to evaluate the influence of Good Corporate Governance (GCG), profitability levels, and entity scale on the market value of coal mining companies listed on the Indonesia Stock Exchange (IDX) between 2021 and 2023. This study adopts a quantitative design by utilizing secondary data from the official IDX website, where 8 companies were selected as samples from a total population of 34 coal sub-sector companies through purposive sampling techniques. Data processing was carried out through panel data regression analysis using Eviews 12 software. The research data indicates that, independently, the implementation of good corporate governance and the level of profit acquisition do not contribute significantly to determining the value of the entity. Conversely, company size is proven to have a significant negative impact. Simultaneous testing confirms that these three independent variables collectively have a significant effect on company value. These findings indicate the need for strategies that consider factors beyond good corporate governance and profitability in efforts to increase company value, such as operational efficiency and proper asset management.

Asset management and equipment maintenance are crucial aspects in supporting smooth business operations, particularly in the copper crafts industry. Merapi Karya Cipta, located in Dusun III, Tumang, Cepogo District, Boyolali Regency, owns various production equipment assets that play a direct role in the work process, yet their management remains rudimentary and unplanned. This community service activity aims to increase copper craftsmen's understanding and awareness of the importance of asset management and equipment maintenance to improve operational efficiency. Qualitative methods were used through observation, interviews, and direct outreach to the craftsmen. The results of the activity demonstrated increased knowledge and a shift in participants' perspectives on business management, particularly regarding equipment maintenance and division of labor. The craftsmen began to understand that routine maintenance can be performed simply and does not always require significant costs. Therefore, this activity is expected to help maintain the continuity of the production process, reduce the risk of equipment damage, and support increased productivity and the well-being of the local community.

The increasing adoption of collaborative robots in modern manufacturing environments requires reliable perception systems that can ensure both safety and operational efficiency during human–robot collaboration. This study proposes a CNN-based real-time computer vision system for object and human detection in shared robotic workspaces. The research focuses on developing and evaluating a single-stage deep learning detection model optimized for real-time performance while maintaining high detection accuracy. The proposed methodology includes dataset preparation, model training using transfer learning, real-time system implementation, and comprehensive performance evaluation. Experimental results demonstrate that the developed system achieves high detection accuracy, as reflected by strong precision, recall, and mean Average Precision (mAP) values, while maintaining low inference latency suitable for real-time operation. The system consistently operates above real-time frame-rate thresholds, ensuring timely perception updates required for safety-related decision-making in collaborative robotic environments. Graphical and quantitative analyses further confirm the stability of inference performance under dynamic interaction scenarios involving human movement and multiple objects. Compared with existing approaches, the proposed system provides a balanced trade-off between accuracy and computational efficiency, making it practical for deployment in safety-aware human–robot collaboration scenarios. Overall, the findings indicate that CNN-based real-time object detection systems can effectively support perception and situational awareness in collaborative robotics, contributing to safer and more efficient industrial automation.

Recent advancements in environmental monitoring and robotic control demand systems that are capable of real-time responsiveness, energy efficiency, and reliable operation in dynamic and resource-constrained environments. Conventional cloud-centric cyber-physical system (CPS) architectures often suffer from high latency, continuous connectivity dependency, and increased energy consumption, limiting their suitability for time-critical monitoring and adaptive control applications. To address these challenges, this study proposes an intelligent embedded cyber-physical system integrating Edge AI, low-power sensor networks, and adaptive robotic control for environmental monitoring. The proposed architecture relocates data processing and decision-making closer to the data source, enabling real-time inference, reduced communication overhead, and enhanced system autonomy. The research adopts a design-oriented experimental methodology involving system architecture design, lightweight Edge AI model development, prototype implementation, and performance evaluation under realistic operating conditions. Experimental results demonstrate that the proposed edge-based CPS significantly reduces end-to-end latency and energy consumption while maintaining acceptable inference accuracy compared to cloud-based processing. Furthermore, the system achieves improved communication efficiency and higher operational reliability, particularly under intermittent network connectivity. The findings highlight that embedding intelligence at the edge enables closed-loop sensing, decision-making, and actuation, which is essential for adaptive robotic control in environmental monitoring scenarios. This study contributes a system-level perspective on Edge AI–enabled CPS design and provides empirical evidence supporting the transition from cloud-centric architectures toward distributed, energy-aware, and resilient cyber-physical systems for real-time monitoring and control applications.

The use of Information Systems and Information Technology (IS/IT) is a crucial factor in improving the efficiency and accuracy of retail sector operations. PT XYZ, a retail-level staple goods provider, has implemented IS/IT to support sales recording, inventory management, security, and operational reporting. This study aims to assess the effectiveness, efficiency, security, and compliance of the information system used. The audit was conducted through observation, interviews, document review, and system testing, referring to the COBIT framework and the ISO/IEC 27001 standard. The audit results indicated that the system supported core operational functions, but weaknesses remained, including insufficient system documentation, limited access controls, and suboptimal data security and backup mechanisms. Furthermore, reliance on manual procedures has the potential to lead to errors and slow down service delivery. Therefore, system improvements, strengthening security controls, developing standard operating procedures, and enhancing the competency of human resources and IT infrastructure are needed. This audit is expected to support improved service quality and secure, effective, and sustainable IT governance at PT XYZ.

This study explores the transformative role of big data-driven Decision Support Systems (DSS) in global digital enterprises, particularly focusing on their impact on operational efficiency and corporate governance. By leveraging big data analytics, DSS offer organizations the tools to process vast amounts of real-time data, enabling executives to make more informed decisions that optimize resources, improve productivity, and reduce operational costs. The research highlights the integration of predictive analytics, machine learning, and real-time data processing within DSS, which allows businesses to gain strategic insights and anticipate market trends. Furthermore, the study emphasizes the significant role of DSS in enhancing corporate governance, improving transparency, accountability, and compliance with regulations. These systems foster better decision-making processes, which contribute to building trust among stakeholders and ensuring long-term organizational success. However, the study also identifies several challenges in implementing big data-driven DSS, including data management complexities, technological integration difficulties, and the need for skilled personnel. Despite these challenges, the findings demonstrate that big data-driven DSS are pivotal in driving competitive advantage, operational optimization, and governance improvements. The research concludes with actionable recommendations for executives to adopt and implement big data-driven DSS, emphasizing the importance of continuous support, training, and system integration. The study also suggests future research directions, including exploring the integration of emerging technologies like AI and IoT into DSS and assessing their long-term impact on sustainability and corporate governance.

The increasing integration of Cyber physical Systems (CPS) into industrial environments has highlighted the need for secure, scalable, and efficient cryptographic key management systems. Traditional centralized key management protocols are often limited by vulnerabilities such as single points of failure, scalability issues, and significant overhead. Blockchain technology presents a promising solution to these challenges by leveraging decentralization, immutability, and transparency to enhance security and efficiency in CPS. This study investigates the use of blockchain based cryptographic key management systems, focusing on smart contracts for automated key distribution and rotation. Experimental results demonstrate that blockchain based systems significantly improve system integrity, auditability, and resilience, offering enhanced protection against cyber-attacks and reducing the risks associated with centralized systems. Blockchain’s decentralized architecture eliminates the need for a central authority, making it more resistant to tampering and operational failures. Additionally, smart contracts automate the key management process, improving efficiency while maintaining a high level of security. The study also evaluates the impact of blockchain on communication performance, finding that it reduces latency and overhead by automating processes and eliminating the need for centralized control. Despite these advantages, challenges such as scalability, latency, and integration with legacy systems remain. The study concludes by suggesting future research directions, including the development of lightweight blockchain protocols tailored for industrial applications and the integration of blockchain with emerging technologies like Artificial Intelligence (AI) to further enhance key management in CPS. Blockchain based solutions have the potential to transform the security landscape of industrial environments, offering greater robustness, reliability, and trust.

This study aimed to analyse the mineral water inventory management practices and improve production cost efficiency at PT. Pintar Sumber Mineral. The research utilized a quantitative descriptive method, with data collected through interviews, documentation reviews, and literature studies. The findings demonstrated that the company had successfully and effectively implemented the Economic Order Quantity (EOQ) model. This effective implementation was evidenced by: The increase in the EOQ value corresponding with the growth in annual demand. The implementation of specific inventory management strategies that supported cost efficiency. While significant demand growth led to an increase in ordering and holding costs, the strategy of adjusting the EOQ model was able to optimally mitigate the impact of these rising costs. This study concluded that the application of the EOQ model had made a positive contribution to the company's operational efficiency.

This study examines the impact of IT-driven innovation management on IT service effectiveness and competitive value creation within smart organizations. As digital transformation accelerates across industries, organizations are increasingly leveraging advanced IT solutions to enhance service delivery, responsiveness, and customer satisfaction. While traditional IT service management (ITSM) models focus on efficiency and structured processes, the integration of innovation management introduces new opportunities to improve service quality and operational agility. Through a quantitative research design, this study employs regression modeling to assess the relationship between IT-driven innovation management and two key outcomes: IT service effectiveness and competitive value creation. Data were collected from 100 technology-intensive organizations that actively integrate innovation into their IT service management processes. The results demonstrate that IT-driven innovation significantly enhances service quality, customer satisfaction, and organizational competitiveness. Furthermore, a curvilinear relationship was identified, indicating that while moderate innovation leads to improved outcomes, excessive innovation may have diminishing returns. These findings highlight the importance of balancing innovation efforts with business goals to achieve optimal performance. The study also compares innovation-driven IT service management with traditional models, illustrating how innovation fosters agility, responsiveness, and long-term value creation. The implications for smart organizations are clear: integrating innovation into IT service management is essential for maintaining a competitive edge in the rapidly evolving digital landscape. Future research should explore the long-term impact of innovation management on organizational sustainability and growth, considering external factors such as market volatility and technological disruptions.

This study investigates the role of Enterprise Information Systems (EIS) in driving innovation within organizations. The research employs a mixed-method approach, combining survey-based structural analysis and in-depth organizational case studies to explore how different EIS capabilities influence organizational innovation. The study focuses on four key EIS capabilities: functional capabilities such as workforce management and customer value creation; technological capabilities including ERP systems and real-time analytics; dynamic capabilities, especially organizational learning; and collaborative innovation through external partnerships. The survey results reveal that EIS capabilities, particularly data analytics and integration, significantly enhance organizational agility, decision-making, and innovation outcomes. In-depth case studies provide detailed insights into how these capabilities are applied in real-world organizational settings, illustrating their impact on process and service innovation. The findings indicate that the effective integration of EIS across organizational functions, along with improved access to data, contributes to operational efficiency and innovation success. However, challenges such as integration issues, resistance to change, and lack of skilled personnel were also identified as barriers to successful EIS adoption. The study contributes to the literature by offering a comprehensive understanding of how EIS capabilities drive innovation and highlighting the importance of organizational culture and leadership in the adoption process. The research provides practical recommendations for organizations to leverage EIS for fostering innovation, such as focusing on EIS integration, overcoming organizational barriers, and ensuring leadership engagement. Finally, the study suggests future research directions, including the refinement of multi-method approaches and the need for longitudinal studies to better understand the long-term impact of EIS on innovation outcomes.

This research explores the integration of Enterprise Architecture (EA) and Artificial Intelligence (AI) to optimize strategic decision-making in digital service-oriented organizations. These organizations often face challenges such as fragmented decision-making due to disconnected IT systems and limited data-driven insights. The objective of the study is to develop an integrated framework that combines EA and AI to enhance decision-making accuracy, operational efficiency, and strategic alignment. The study employs design science research methodology, involving the development of the framework, expert validation, and testing in simulated organizational scenarios. The findings reveal that the integrated framework improves decision-making by providing real-time, data-driven insights, predictive analytics, and better alignment with organizational goals. AI's role in analyzing large datasets and generating actionable insights allows decision-makers to anticipate future trends and make more informed decisions. The framework significantly outperforms traditional EA approaches, particularly in terms of predictive decision support and adaptive intelligence. The study concludes that the integration of EA and AI provides a robust solution for organizations looking to improve strategic decision-making, enhance operational efficiency, and stay competitive in dynamic business environments.

The integration of Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) systems has emerged as a critical strategy for modern digital enterprises aiming to enhance customer experience and operational efficiency. This study examines the impact of CRM-ERP integration on customer satisfaction, personalized service, and organizational responsiveness. By adopting a mixed-methods approach, this research combines quantitative customer data analysis and qualitative managerial interviews to assess the benefits and challenges of CRM-ERP integration. Key findings highlight significant improvements in customer experience, with increased satisfaction and personalized interactions facilitated by a unified view of customer data. Operational efficiencies were also realized through streamlined processes, better alignment of departments, and enhanced decision-making based on real-time, data-driven insights. Despite these positive outcomes, challenges such as system integration complexities, data fragmentation, and resistance to change were identified, which hindered the speed of integration and full utilization of the systems. This study demonstrates that CRM-ERP integration provides a competitive advantage by improving both customer service and business agility, particularly in industries undergoing digital transformation. For digital enterprises, integrating these systems is crucial for maintaining a seamless customer experience across various touchpoints and achieving greater operational effectiveness. The paper concludes by suggesting future research on the long-term impact of CRM-ERP integration on customer loyalty, business growth, and the potential role of emerging technologies like AI and blockchain in further enhancing these systems.

Digital transformation (DT) has become a critical component for organizations aiming to enhance their operational efficiency, innovation, and competitiveness. However, many organizations struggle to achieve successful digital transformation due to the misalignment between their Enterprise Information Systems (EIS) and organizational strategic goals. This research seeks to design and validate a model for aligning EIS with digital transformation strategies to improve organizational effectiveness. By adopting the Design Science Research (DSR) approach, this study develops a practical model that integrates strategic planning, process management methodologies, and emerging technologies to facilitate alignment between IT and business strategies. The research includes key steps such as requirement analysis, artifact design, expert validation, and case study evaluation to ensure the model's robustness and applicability across different organizational contexts. Findings indicate that the proposed model significantly improves strategic-system alignment, enhances decision-making consistency, and facilitates better integration between business and IT units. The model also addresses common challenges such as resistance to change, skill gaps, and misalignment, fostering a supportive culture for digital transformation. In comparison to existing descriptive frameworks, the proposed model is more structured, adaptable, and actionable, providing organizations with a clear framework to guide their digital transformation efforts. This research contributes to the growing body of knowledge on EIS alignment and offers practical insights for organizations seeking to achieve successful digital transformation. Future research could explore the model's application in various organizational settings and examine its impact on long-term organizational growth and innovation.

In the context of both public organizations and Small and Medium Enterprises (SMEs), inefficient business processes remain a significant challenge. Fragmented information systems often hinder the optimization of these processes, leading to slower decision-making, redundant efforts, and increased operational costs. This study aims to analyze and optimize business processes by utilizing integrated information systems (IIS), providing a comparative analysis between the two sectors. The theoretical framework explores key theories such as Business Process Management (BPM) and the integration of information systems for process optimization. Previous studies highlight the differences in how IIS implementation impacts the public and SME sectors, noting challenges such as data silos, legacy systems, and resistance to change. A case study analysis methodology was employed to assess the effectiveness of IIS across both sectors. Business Process Modeling (BPMN) was used to visualize business processes before and after optimization, and process performance was measured through key metrics such as time reduction, error rates, and cost efficiency. The results show that IIS integration improved business process efficiency by an average of 28%, with reductions in redundancy and faster decision cycles observed in both sectors. Public organizations benefited from enhanced service delivery and better resource management, while SMEs gained competitive advantages through streamlined operations and increased responsiveness to market demands. The comparison reveals that integrated systems had a greater operational impact than traditional isolated process reengineering methods. Public organizations faced more regulatory and governance challenges, while SMEs leveraged their flexibility for faster integration. Recommendations for both sectors include focusing on overcoming barriers such as resistance to change and investing in system modernization. Future research should explore the long-term effects of IIS integration and further sector-specific comparisons.

The selection of this research topic is based on the important role of packing machines in the noodle production process. As consumer demand continues to increase and industrial competition becomes more intense, optimizing production efficiency is a critical requirement for manufacturing companies. This study focuses on the Tokiwa W500 Packing Machine used at PT. Indofood CBP Sukses Makmur, Noodle Division, Semarang. The research method involves a comprehensive review of the machine control system to evaluate its operational performance. Data collection was conducted through direct observation, structured interviews with machine operators, and relevant literature review. The review emphasizes system performance, operational efficiency, and the level of automation, while identifying potential areas for improvement. The results indicate that the Tokiwa W500 Packing Machine operates in a stable and consistent manner during the noodle packaging process. However, opportunities were identified to enhance the automation system in order to improve production efficiency and reduce the risk of human error. This study is expected to contribute to the development of more effective and optimized control systems for industrial packing machines.

The rapid growth of information technology has encouraged small and medium-sized food businesses to adopt digital systems in order to improve service quality and operational efficiency. Ayam Goreng Pakdhe, a local culinary business, still relies on manual ordering processes that often lead to order inaccuracies, slow service, and limited access to sales data. This study aims to design and develop a web-based ordering system for Ayam Goreng Pakdhe using the Spiral software development method, which emphasizes iterative development, risk analysis, and continuous user feedback. The research method consists of requirement analysis, system design, implementation, and evaluation carried out in repeated cycles according to the Spiral model. Data were collected through observation, interviews with business owners and employees, and analysis of existing business processes. The results show that the proposed web-based system is able to streamline the ordering process, reduce human errors, and provide real-time information on orders and sales reports. Furthermore, the iterative nature of the Spiral method allows the system to be adjusted according to user needs and potential risks identified during development. The implementation of this system is expected to enhance operational efficiency, support better decision-making, and increase customer satisfaction, thereby contributing to the digital transformation of small-scale culinary enterprises.

The management of material and labor costs at Gregors Barbershop is still manual and not formally structured, resulting in wastage of consumable materials, suboptimal labor utilization, and difficulties in determining service prices that align with the expected profit margins. Material costs, such as hair gel, tissues, disposable razors, and alcohol/disinfectants, are not recorded systematically, leading to frequent mismatches between stock and actual needs, while labor costs are calculated improvisationally without considering productivity and service targets. This activity aims to improve the ability of owners and employees to plan, control, and evaluate operational costs systematically, ensuring efficiency, resource optimization, and business profitability. The method uses an applied, hands-on approach, including the identification of partner needs, preparation of relevant training modules, direct operational mentoring, and evaluation with follow-up. The object of the activity is Gregors Barbershop in Batu Aji District, Batam City, which offers services such as modern men’s haircuts, classic shaves, shaving, hair treatments, and the sale of grooming products like pomade and hair oil. The results show increased efficiency in the use of consumable materials, more productive labor management, more systematic cost planning, and the ability to set service prices in line with costs and profit margins. It is recommended to implement a digital recording system and productivity-based incentives to ensure more accurate cost control, more efficient operations, and sustainable business profitability.

This study aims to analyze the implementation of business networks in improving operational efficiency in small and medium-sized enterprises (SMEs) operating in the outdoor equipment sector. Increasing public interest in outdoor activities has intensified competition among SMEs, requiring them to develop effective collaboration strategies to maintain operational sustainability. This research employs a qualitative descriptive approach with a single case study design conducted at Misala Gear Outdoor, an SME engaged in outdoor equipment rental and sales in Ciwidey, Bandung Regency. Data were collected through in-depth interviews, direct observation, and documentation, and analyzed using descriptive qualitative techniques. The results indicate that the implementation of business networks involving supplier partnerships, outdoor communities, tourism agents, and digital platforms contributes significantly to improving operational efficiency, particularly in inventory management, service delivery, and market reach. Moreover, business networks enable cost control, resource optimization, and service differentiation, which strengthen the enterprise’s competitive position. This study highlights the strategic role of business networks as an operational efficiency driver for SMEs in the outdoor industry and provides practical implications for SME managers in developing collaborative business strategies.

The development of information technology requires service companies to improve the effectiveness and quality of their services, including in the field of electrical installation services. CV Givas Jaya Sentosa still faces problems in managing orders, customer data, and technician scheduling, which are done manually, resulting in inefficiency. This study aims to design and build a web-based electrical installation service provider information system using the Object Oriented Analysis and Design (OOAD) method. The research method used is qualitative with a research and development (R&D) approach, through data collection techniques such as observation, interviews, and documentation. The system is designed using Unified Modeling Language (UML) modeling and implemented as a web application. The results of the study show that the system is able to simplify the service ordering process, improve service and technician data management, and help monitor work status in an integrated and real-time manner. Thus, this information system can improve operational efficiency and service quality at CV Givas Jaya Sentosa.

The digital era presents challenges as well as opportunities for business actors, especially Micro, Small, and Medium Enterprises (MSMEs). Accelerating the adoption of digital technology-based payment systems is an urgent need so that MSMEs are able to compete and improve transaction efficiency. This Community Service (PKM) activity was carried out in Cendoro Village, Tuban Regency, with the aim of providing assistance to MSME actors through the implementation of a QRIS-based digital payment system. The method of implementing PKM consists of three stages, namely preparation, implementation, and evaluation. In the preparation stage, needs are identified and socialization of QRIS benefits are carried out. The implementation stage includes technical training on the use of QRIS as well as direct assistance in the implementation of non-cash transactions. The evaluation stage was carried out to measure the level of understanding and application of QRIS by participants. The results of the activity showed that participants understood the concept of digital payment and were able to apply QRIS in daily transactions. In addition, this activity encourages an increase in the adoption of QRIS which has an impact on efficiency, transaction security, expansion of market access, and local economic growth. The main obstacles faced include limited technological knowledge, uneven internet access, and operational costs. Thus, this PKM contributes to strengthening digital literacy and supporting technology-based economic transformation in Cendoro Village, Tuban Regency.