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Manual server administration introduces operational inefficiencies and elevated risks of human error. This study evaluated the effectiveness of server administration automation utilizing Shell scripting and Cron Job scheduling within a virtualized Linux Debian 12 environment. An experimental method compared manual execution against automated procesases based on execution duration, resource consumption, and error reduction. The findings indicated that the automated system executed backup routines within 0.043 seconds, demonstrating a 95.16% time efficiency increase compared to the manual baseline of 0.89 seconds. Automated monitoring maintained a stable resource allocation, utilizing 275 megabytes of memory and low central processing unit usage between 0.0% and 1.3%. Furthermore, automation reduced operational failures to 0%. In conclusion, this integration significantly optimizes server reliability.

The emergence of Internet of Things (IoT) technology has opened up considerable possibilities for automation systems aimed at enhancing energy efficiency in both home and office settings. This study focuses on the creation and deployment of an IoT-driven Smart Home system utilizing ESP32 for the automatic and manual supervision and regulation of electrical appliances within the Employee Dormitory of the Institute for Lecturer Performance Development (LPKD). The established system employs a Passive Infrared (PIR) sensor for detecting human presence and a Light Dependent Resistor (LDR) sensor to assess the intensity of light in the room. The data from these sensors is analyzed by the ESP32 microcontroller, which controls lights and fans automatically through relay modules based on the surrounding conditions. Furthermore, the system is linked to the Blynk application and the Telegram Bot API to enable remote operation and immediate notifications. The methodological approach taken in this research is Research and Development (R&D) employing a prototyping method. The assessment outcomes show that the system functions reliably, with success rates for sensor detection and appliance management exceeding 95%. The introduction of this system aims to boost electrical energy efficiency, improve user experience, and facilitate the adoption of IoT-centered smart facility management within the LPKD framework.

The rapid advancement of Internet of Things (IoT) technologies has transformed conventional residential environments into intelligent smart housing systems capable of enhancing energy efficiency, security, comfort, healthcare services, and environmental sustainability. However, existing studies remain fragmented, focusing on specific technologies or applications rather than providing a comprehensive understanding of the smart housing ecosystem. Therefore, this study aims to systematically review the major technologies employed in IoT-based smart housing systems, examine their contributions to residential benefits, and identify the challenges and future opportunities associated with their implementation. This research adopted a Systematic Literature Review (SLR) approach using the Scopus database as the primary source of literature. The review process followed a structured screening and selection procedure, resulting in the inclusion of 26 studies that met the predefined eligibility criteria. The findings indicate that Artificial Intelligence, Blockchain, Edge Computing, Fog Computing, Cloud Computing, Digital Twin, Smart Grid technologies, renewable energy systems, and advanced sensor infrastructures constitute the primary technological foundations of modern smart housing systems. The reviewed studies indicate that these technologies contribute to energy optimization, cybersecurity enhancement, intelligent automation, healthcare monitoring, safety improvement, and sustainable resource management. However, challenges related to security, privacy, interoperability, scalability, computational complexity, and implementation costs remain important barriers to widespread adoption. In conclusion, IoT-based smart housing systems have evolved into integrated and intelligent residential ecosystems, and future development is expected to be driven by the convergence of Artificial Intelligence, distributed computing, Digital Twin technologies, and sustainable smart infrastructure solutions.  

Hot material dumping in the chemical industry is an important process stage that affects occupational safety, process stability, and product quality reliability. In manual processes, dumping activities may cause variation because they are influenced by operator condition, pouring angle, work speed, and exposure to hot materials. This study aims to analyze the consistency of the hot material dumping process and formulate a B2B strategy based on process reliability. The research method uses a descriptive-quantitative case study approach with data from 20 batches, analyzed through three indicators: dumping time, pouring flow stability, and material temperature change or ΔT. The data were primary data obtained directly through field observation, production-process documentation, and recording of process parameters; journal literature was used only as the theoretical and interpretive basis. The results show that the automated process provides more consistent performance than the manual process. The average dumping time decreased from 49.14 seconds to 30.18 seconds, the coefficient of variation for dumping time decreased from 12.44% to 1.36%, the pouring flow stability score increased from 2.55 to 4.70, and the average material ΔT decreased from 15.26°C to 8.16°C. These findings indicate that automation can improve process regularity, reduce variation between batches, and maintain material conditions in a more controlled manner. This process consistency can serve as the basis for a B2B strategy based on process reliability, emphasizing process reliability, production safety, quality consistency, and data-based evidence as key values in building industrial customer trust.

Digital democracy and e-governance have emerged as transformative instruments for promoting transparency, accountability, and efficient public administration in India. This study examines the role of digital governance initiatives in strengthening democratic participation and reducing corruption through technology-driven governance mechanisms. Using a qualitative and doctrinal research methodology based on secondary sources, the study analyses major initiatives such as Digital India, Aadhaar, DigiLocker, BharatNet, BHIM-UPI, and MyGov. The findings demonstrate that digital governance has improved accessibility to public services, enhanced administrative efficiency, and minimized bureaucratic corruption through automation and electronic monitoring systems. Furthermore, digital platforms have expanded citizen participation in democratic processes by facilitating communication between governmental institutions and the public. However, challenges such as digital inequality, cyber-security risks, infrastructural limitations, and privacy concerns continue to affect the effectiveness of digital democracy in India

This study examines the transformation of financial management through the implementation of digital accounting in PPOB (Payment Point Online Bank) businesses, which still face manual recording problems such as input errors, delayed reconciliations, and data discrepancies. The research used a descriptive qualitative method with a case study approach involving PPOB agents in Sidoarjo. Data were collected through observation, interviews, and documentation. The findings show that digital accounting significantly improves operational efficiency through automated transaction recording, real-time data integration, and faster as well as more accurate reconciliation processes. In addition, features such as automatic validation, API integration, and audit trails help minimize recording errors and maintain data consistency. The implementation of digital accounting also supports transparency and improves the quality of financial information used in decision-making. Although challenges remain regarding agents’ technological understanding and infrastructure readiness, overall implementation has provided positive impacts on financial management effectiveness and business operations in PPOB services, making processes more efficient, accurate, and reliable.

Computers in one of the network companies at PT. Estrada uses the Fortinet operating system. The final result expected through this implementation is to comprehensively see the capabilities of the firewall on Fortinet in overcoming the problem of blocking social media applications and streaming platforms during working hours. Blocking the application in question is the ability to filter web processes such as Facebook, Instagram, YouTube, etc. In the tests carried out, web filtering was able to block applications on social media and streaming platforms, which proves that the performance of web filtering is quite good. In analyzing web filtering performance, use the office hour rule tool by carrying out the rule schedule in the Fortinet network and displaying all the information in detail. The final result obtained in the network application filtering simulation process using Fortinet is that every network sent cannot be entered (blocked) on both social media applications and streaming platforms.

Feasibility evaluation is a crucial step in port development as it ensures that the project to be implemented provides optimal technical, economic, social, and environmental benefits. This study aims to provide a comprehensive overview of global research trends related to port feasibility evaluation, approaches applied in previous studies, and risks that arise when feasibility aspects are neglected in port development. Using a systematic literature review (SLR) approach, the study analyzes articles published between 2020 and 2025 indexed in Scopus. The results show that there has been increasing global attention to the importance of sustainable ports focused on green technologies and terminal automation. However, many studies still overlook social and environmental risks in feasibility evaluations. The study also found that neglecting feasibility aspects can lead to economic losses, environmental damage, and social dissatisfaction, resulting in project failure. Therefore, this research emphasizes the need for a more integrated feasibility evaluation that includes all technical, economic, social, and environmental dimensions. This study is expected to contribute to the development of a more holistic feasibility evaluation model, especially for developing countries like Indonesia, which still face significant challenges in port modernization and the adoption of green technologies.

Purpose Research on digitalization in Human Resource Management (HRM) has grown significantly alongside rapid digital transformation and organizational change. However, studies integrating systematic literature review and bibliometric analysis remain limited. This study aims to examine research trends and thematic developments related to digitalization in HRM through a hybrid systematic literature review and bibliometric analysis approach. Method This study employed a Systematic Literature Review based on PRISMA 2020 guidelines using data from the Scopus database with keywords related to digitalization and Human Resource Management. The initial search identified 2,497 documents, and after the screening process, 108 relevant articles were selected. Data were analyzed using VOSviewer to identify publication trends, keyword relationships, collaboration networks, and thematic clusters. Findings The findings indicate that research on digitalization in HRM increased significantly during 2018–2026. Dominant themes include digital transformation, artificial intelligence, e-HRM, innovation, Industry 4.0, sustainability, and organizational performance. Digitalization in HRM has evolved from administrative automation toward strategic organizational transformation supported by technology and data-driven decision making. Originality/value This study integrates systematic literature review and bibliometric analysis to provide a comprehensive understanding of digitalization in HRM.  

Digital transformation has positioned artificial intelligence (AI) as a major driver of organizational change and innovation. This study aims to analyze the influence of AI implementation on transformational leadership dynamics and the shifting role of leaders in managing human resources through a Systematic Literature Review of reputable studies published within the last five years. The findings indicate that AI acts as a catalyst in strengthening the dimensions of intellectual stimulation and individualized consideration through predictive analytics and talent personalization. The automation of administrative and repetitive tasks enables leaders to focus more on strategic vision, organizational innovation, decision-making, and emotional engagement with employees. However, the effectiveness of AI implementation is highly dependent on leaders’ digital literacy, adaptive capabilities, and readiness to integrate technology into organizational processes. This study contributes by proposing a hybrid leadership framework that combines artificial intelligence with human emotional intelligence to support more effective leadership practices. The practical implications emphasize the importance of leadership development that prioritizes empathy, ethical awareness, and algorithmic transparency in order to maintain trust, encourage sustainable innovation, and strengthen organizational resilience in increasingly dynamic and volatile environments.

In Indonesia, interest in becoming a public accountant is very low. Several factors prevent accounting graduates from choosing public accounting as their career choice. This phenomenon is the reason for this study. This study aims to reconstruct the understanding of career interest as a public accountant, by considering the integrative influence of AI, workplace well-being, and labor market considerations. A quantitative approach was used by distributing questionnaires to accounting students at various universities in Yogyakarta as a representation of the future generation of prospective public accountants. Data analysis was conducted using IBM SPSS Statistics 26. The results show that artificial intelligence, workplace well-being, and labor market considerations have a positive and significant influence on career interest as a public accountant. The addition of the artificial intelligence variable is the main difference between this study and previous studies. This research provides a theoretical contribution through the integration of technological, psychological, and economic dimensions in the analysis of public accountant career behavior. Practically, the results of this study provide strategic recommendations for Public Accounting Firms and educational institutions to design work environments and curricula that are responsive to the values of the digital generation, particularly in preparing adaptive accounting talent in the era of automation.

This study presents a systematic qualitative literature review examining regulatory, ethical, and organizational challenges in the adoption of artificial intelligence (AI) for letter of credit (LC) automation in trade finance. Synthesizing prior interdisciplinary research, the review finds that AI technologies—such as machine learning and natural language processing—offer substantial efficiency, accuracy, and transparency gains in documentary credit examination. However, these benefits are constrained by regulatory uncertainty stemming from legacy legal frameworks, ethical concerns related to algorithmic opacity, bias, and accountability, and organizational challenges involving trust, governance, and workforce readiness. The findings highlight that AI-driven LC automation constitutes a socio-technical transformation rather than a purely technological upgrade, requiring alignment between evolving regulation, responsible AI governance, and organizational change management. This study contributes to the trade finance and digital transformation literature by providing an integrated perspective on how transparency can be institutionalized without undermining trust in automated financial decision-making

The rapid evolution of digital technologies has fundamentally reshaped tax administration systems, particularly for Micro, Small, and Medium Enterprises (MSMEs), which constitute a critical driver of economic development yet continue to demonstrate suboptimal levels of tax compliance. This study aims to critically examine the role of Application Programming Interface (API)-based tax automation in enhancing MSME tax compliance through a systematic narrative literature review approach. Employing a qualitative design, this study synthesizes recent scholarly works published within the last five years to identify patterns, relationships, and emerging trends in digital taxation practices. The findings indicate that API-based automation significantly improves administrative efficiency, minimizes human error, and facilitates real-time data integration between taxpayer systems and tax authorities. Moreover, such integration enhances transparency and reduces compliance costs, thereby fostering voluntary compliance behavior among MSMEs. Nevertheless, the effectiveness of this technological intervention is contingent upon several structural and behavioral factors, including digital literacy, technological readiness, and the availability of reliable digital infrastructure. Persistent disparities in these areas may constrain the scalability and inclusiveness of API implementation. This study underscores that API-based tax automation represents a transformative policy instrument in modernizing tax administration systems, provided it is supported by coherent regulatory frameworks, capacity-building initiatives, and equitable infrastructure development. The findings contribute to the broader discourse on digital taxation by offering a conceptual foundation for developing adaptive and sustainable compliance strategies in the era of economic digitalization

Marriage confirmation services are often hampered by manual procedures, leading to delays and administrative errors. This study aims to design and implement a web-based Marriage Confirmation Information System to facilitate registration, document uploads, and online monitoring of verification status and court schedules. The system was developed using the PHP programming language and MySQL database using the Waterfall method, encompassing analysis, design, implementation, and testing. The results show that the system is capable of optimally performing all managerial functions, from document validation to report automation. Black Box testing confirmed that all features functioned as expected and were easy to use. In addition to improving bureaucratic efficiency, the system ensures data security through login encryption and provides transparency through real-time status tracking. The presence of this platform significantly saves time and transportation costs for the public, as bureaucratic processes can be monitored from anywhere. In conclusion, this system successfully supports the digitalization of public services and improves the quality of administration within the Office of Religious Affairs (KUA) and Religious Courts, thereby realizing more effective, efficient, accountable, and modern governance for all levels of society

This systematic literature study conducts a comparative analysis of Reliability-Centered Maintenance (RCM) and Total Productive Maintenance (TPM) in manufacturing, and proposes an integrated hybrid model. The research concludes that RCM and TPM are fundamentally distinct methodologies: RCM excels in risk-based, analytical management of complex, high-criticality assets, while TPM is superior for achieving broad-based productivity gains and cultural empowerment through total employee involvement. The effectiveness of each approach is contingent upon factors such as asset characteristics, organizational culture, data availability, and level of automation. To leverage their complementary strengths, the study proposes the Synergistic RCM-TPM Hybrid Model (SRTHM). This framework advocates for a sequential implementation where TPM establishes the foundational operational stability, discipline, and data culture, upon which selective RCM analysis is applied to critical assets for precision risk management. The model incorporates explicit feedback mechanisms to create a continuous organizational learning cycle. The study provides a contingency framework for methodology selection and a practical roadmap for integration, offering theoretical and practical guidance for building more resilient and context-appropriate maintenance systems in modern manufacturing.

Waste management remains a critical environmental issue due to the lack of public awareness in separating organic and inorganic waste, resulting in accumulation and environmental pollution This study aims to analyze and evaluate the development of automatic waste sorting systems based on proximity sensors with full-capacity notification using a Systematic Literature Review (SLR) approach.. The proposed system utilizes a combination of sensors, including proximity sensors for material identification and ultrasonic sensors for detecting object presence and bin capacity, integrated with a microcontroller for real-time processing. Additionally, the system is equipped with IoT-based monitoring that allows users to receive notifications when the waste bin reaches its capacity. The research method involves system design, hardware and software integration, and functional testing to evaluate system performance. The results indicate that the system is capable of sorting waste automatically with a high level of accuracy and responsiveness, while also providing real-time monitoring to support waste management operations. The implementation of this system can reduce manual intervention, increase operational efficiency, and promote better waste segregation practices. Furthermore, this study highlights the potential of integrating smart technology into environmental management systems, contributing both theoretically and practically to the development of sustainable waste management solutions.

This study aims to examine the integration of Generative AI in higher education through the perspective of the SAMR framework, which consists of Substitution, Augmentation, Modification, and Redefinition. The study used a narrative literature review method by analyzing 30 relevant academic publications published between 2023 and 2025. The findings reveal that the implementation of GenAI in higher education is still predominantly situated at the substitution and augmentation levels, with primary functions focused on improving efficiency, automation, and academic assistance. In contrast, transformative applications categorized under modification and redefinition remain relatively limited and are still in the early stages of development. This study concludes that although Generative AI possesses substantial potential to transform higher education practices, its current implementation has not yet reached an optimal transformative stage. Therefore, future educational practices should emphasize the development of more transformative implementation strategies that move beyond efficiency-oriented utilization toward fostering pedagogical innovation and meaningful learning transformation.

This research was conducted with the aim of developing an automation system for recording warehouse inventory based on Google Sheets to improve the effectiveness and efficiency of the stocktaking process at the Cresta Management warehouse. This research was based on problems in the semi-manual process that used logbooks and separate files for each group of goods, which caused problems such as data duplication, limited data access, lack of data transparency, and lengthy recapitulation process. This research used the Research and Development method using the ADDIE model (Analyze, Design, Develop, Implement, and Evaluate). Data were collected through observastion, interviews, questionnaires, and documentation. The result of this development is a system consisting of a login page, goods transcation recording, warehouse dashboard, stock reports, stock cards, and PDF report exports. This study also produced evaluation scores regarding the system’s feasibilty: 93,3% from the first media expert, 80% from the second media expert, 73,3% from the material expert, and 91,75% from users through User Acceptance Testing. These evaluation results indicate that the system is feasible for use and implementation in supporting warehouse operations, as it provides real time data updates, improves the efficiency of goods reporting, and enhances warehouse transactions.

This study aims to analyze digital transformation in public administration as a strategy to improve the efficiency and transparency of government services in Poso Regency. The study uses a qualitative approach with library research methods, sourced from various scientific literature, both national and international journals relevant to the research topic. The results show that digital transformation plays a significant role in improving the efficiency of public services through the automation of administrative processes, thereby accelerating service times and reducing the potential for human error. Furthermore, digital transformation also increases transparency and accountability through the openness of public information that is widely accessible to the public. However, the implementation of digital transformation in the regions still faces various challenges, such as limited technological infrastructure, low readiness and competence of human resources, and suboptimal system integration and data security. Therefore, a comprehensive strategy is needed, including strengthening digital infrastructure, increasing the capacity of government officials, and optimizing open data-based policies. This research is expected to contribute to the development of sustainable digital transformation policies at the regional level.

This community service activity aims to improve the effectiveness of clean water distribution management through the implementation of a Water Level Control (WLC) system as an automatic control for water pumps and three-phase motors at a regional drinking water supply company in Lamongan. The methods employed include field observation, problem identification, system design and implementation, as well as periodic evaluation of system performance. The activity focuses on the water treatment unit by conducting control and monitoring of operational parameters such as frequency (Hz), pump pressure, and flow stability to ensure optimal water distribution according to consumer needs. The results indicate that the implementation of the WLC system enhances operational efficiency, minimizes human error, and supports more structured and sustainable equipment maintenance. In addition, this activity contributes to improving the knowledge and technical skills of personnel in operating, monitoring, and maintaining automated control systems. In managing automation-based technology in a professional and independent manner, human resource capacity is strengthened, while the quality of clean water services is also improved through this community service program.