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Digital technology advancements have greatly changed how small businesses manage their finances. This change is not only about recording transactions, but it also affects financial control, report preparation, and business decision making. Accounting Information System (SIA) came about as a solution to help small and medium businesses easily, organize, and accurately record their finances, as well as provide reliable financial information. This study aims to explain the role of the Accounting Information System in making it easier to manage the finances of small and medium businesses in the digital age, the benefits gained from using it, and the challenges faced during its implementation. The method used in this research is a literature review, which involves examining books, journals, and other related scientific publications, followed by analysis using a descriptive qualitative approach. Research findings show that using a digital-based Accounting Information System can improve business efficiency, speed up financial reporting, increase transparency, and make it easier for small and medium-sized businesses to get funding access. However, the implementation of the Accounting Information System still faces challenges such as a lack of technological understanding, limited infrastructure, and high implementation costs. Therefore, collaboration and support from various parties are needed to ensure the accounting information system is implemented effectively and sustainably in small and medium businesses.

This community-based project aimed to analyze the cash management system of the micro, small, and medium enterprise (MSME) Bakpia Juwara Satoe and develop recommendations to improve the company's financial performance. Cash management is a crucial but often overlooked aspect of MSME financial management, which can lead to cash flow problems, inaccurate record keeping, and poor management decisions. The methodology used included qualitative data collection through direct observation, in-depth interviews, and financial statement analysis. The project findings revealed that Bakpia Juwara Satoe lacked a functioning cash management system. There was no separation between cash receipts and disbursements, no standardized system for handling cash, and transaction recording remained manual and inconsistent. As part of the project, standard operating procedures (SOP) for cash management were developed, financial accounting training was conducted, and support was provided in creating simple cash flow statements. Following the implementation of these measures, record accuracy increased by 78%, and cash losses were reduced. It was determined that the implementation of efficient cash management contributed significantly to the improvement of Bakpia Juwara Satoe's financial performance.

This study investigates the integration of digital twin technology and machine learning for predictive analysis in smart mechanical systems. The research emphasizes the role of intelligent computational frameworks in improving industrial monitoring, predictive maintenance, and operational efficiency within Industry 4.0 environments. A qualitative content analysis approach was employed by reviewing scientific literature, industrial reports, and previous studies related to digital twins, artificial intelligence, and predictive analytics. The findings indicate that digital twin architectures supported by machine learning algorithms can significantly enhance real-time monitoring, fault prediction accuracy, and maintenance optimization. The integration of IoT devices, cloud computing, and intelligent analytics also improves industrial sustainability, reduces operational downtime, and supports data-driven decision-making processes. Furthermore, the study identifies several technological challenges, including cybersecurity risks, data integration complexity, and computational limitations. Overall, the proposed intelligent digital twin framework provides a promising approach for future industrial innovation and sustainable smart mechanical system management

The Indonesian Archipelagic Sea Lane II (ALKI II) constitutes a strategic route stretching from the Sulawesi Sea to the Indian Ocean with trade values reaching USD 1.5 million daily and traversed by more than 36,773 vessels annually. The complexity of maritime security threats in this region has increasingly intensified following the relocation of the capital city to East Kalimantan, thereby demanding an effective decision support system to assist Indonesian Warship Commanders in making operational decisions that are rapid, accurate, and in accordance with applicable legal provisions. This research employs a qualitative approach through in-depth interviews with four maritime expert sources, with data analysis using NVivo 12 software. Analysis results identified maritime operational complexity and the urgent need for a comprehensive decision support system. These findings subsequently served as guidance in designing a Decision Support System (DSS) with a tab-based interface that integrates international legal frameworks such as UNCLOS 1982, Law No. 3/2025 on TNI, and related national regulations to generate structured action recommendations along with their legal foundations. Research findings demonstrate that the developed DSS successfully integrates operational, legal, and situational aspects to support decision-making that is rapid, accurate, and legally compliant. This system has proven to enhance the effectiveness of Indonesian Warship Commanders in addressing the complexity of maritime security (KAMLA) challenges in ALKI II through the provision of legally-based action recommendations from national and international frameworks accessible in realtime during operational situations.  

Agentic artificial intelligence (AI) systems capable of autonomous goal-directed behavior, multi-step planning, tool use, multi-agent coordination, and iterative self-correction represent a transition from passive clinical AI tools toward systems that can participate in complex healthcare workflows. However, empirical evidence remains fragmented across clinical decision support, patient monitoring, and administrative applications, and no systematic synthesis has evaluated which agentic principles have been technically demonstrated and which have accumulated sufficient evidence to support responsible clinical deployment. We conducted a PRISMA-informed systematic review of peer-reviewed empirical studies published between January 2025 and April 2026. Searches across five bibliographic databases and Google Scholar, supplemented by citation tracking, identified 443 unique records for screening, of which 25 met the predefined PICOS and quality appraisal criteria. Evidence was synthesized using an evidence-informed seven-principle framework derived from the integration of agentic AI, clinical AI, and healthcare governance literature. This framework provides a structured lens for examining how agentic principles are evaluated individually and in combination, enabling a deployment-readiness perspective that extends beyond capability-focused assessments alone. The evidence base was concentrated on technical capability principles, whereas human oversight, safety, compliance, and equity-related evaluation received comparatively limited attention. Most studies remained at the laboratory, benchmark, or proof-of-concept stage, and none reported demographic-stratified performance outcomes. Overall, the findings suggest a structural asymmetry in agentic healthcare AI: empirical research is advancing agentic capabilities more rapidly than it is generating evidence for the oversight, safety, equity, and governance mechanisms required for responsible clinical translation.

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.

The enactment of Law Number 1 of 2023 concerning the Criminal Code (KUHP) has brought a fundamental paradigm reconstruction to the Indonesian criminal justice system through the explicit recognition of the "living law" (hukum yang hidup di masyarakat). This study aims to analyze the legal standing of living law within the Indonesian legal system and examine the juridical and sociological implications of integrating these unwritten norms from the perspective of Article 2 of Law Number 1 of 2023. The research method employed is normative legal research with a statutory approach. The results indicate that the positioning of living law holds a strategic standing rooted in Article 18B paragraph (2) of the 1945 Constitution of the Republic of Indonesia and is further reinforced by the Constitutional Court Decision Number 35/PUU-X/2012. Following the promulgation of Law Number 1 of 2023, Article 2 paragraph (1) formally deconstructs the rigidity of the colonial-inherited formal legality principle (Wetboek van Strafrecht) and transforms it toward a material legality principle. Consequently, living law is now recognized as a valid basis for criminal liability and acts as a complement to national law, manifested through additional criminal penalties in the form of fulfilling local customary obligations to support restorative justice. Nonetheless, the state imposes limitations through a codification mechanism into Regional Regulations guided by Government Regulations, which must be aligned with Pancasila, the 1945 Constitution, Human Rights, and general principles of law recognized by civilized nations to prevent legal uncertainty and subjective interpretations of the law.

SR12 Herbal Cosmetics is a company engaged in the field of herbal and skin care. Founded in 2015 byToni Firmansyah, S. Farm., Apt. and Asrianty Salam, Farm. This company has a vision to provide benefits to many people through the herbal and skin care products they produce. SR12 Herbal Cosmetics products are formulated based on research from certified scientists, and have been tested at the Sucofindo Laboratory, are free of mercury and hydroquinone, and have been registered with the Indonesian Food and Drug Supervisory Agency (BPOM RI). SR12 Herbal Cosmetics has several factories in West Java Province and has an extensive distribution network with hundreds of distributors and tens of thousands of partners throughout Indonesia. The goal to be achieved is to produce a management information system model including a management information system for PT SR12 Herbal Cosmetics. The research object chosen is a company in the field of cosmetics and skin care which has its head office in Gunung Sindur, West Java. This selection aims to form a management information system design model that is able to produce relevant and timely information for planning, controlling, decision making and evaluating the performance of activities. For the Web-Based Instagram Content Management Information System Design project to Support SR12 Herbal Cosmetics' Brand Awareness, I used Agile (Scrum) due to the dynamic nature of digital marketing and potential changes to the Instagram API or business needs. This allowed SR12 to get core functionality faster and provide iterative feedback, ensuring the system built was truly relevant to their brand awareness needs.

This article analyzes the recurring flash floods in North Konawe Regency which occurred in 2000, 2013, 2016, 2018, 2019, 2020, and 2021 as ecological disasters causally linked to three decades of natural resource exploitation through logging, oil palm plantations, and open-pit nickel mining. Using the dual framework of political ecology and environmental justice, this article argues that these disasters are not neutral natural events, but rather the product of a structured system of injustice: the indigenous Culambacu People and Tolaki People communities who were excluded from decision-making processes regarding extractive permits have borne the greatest burden of the destructive impacts of such exploitation. The most dramatic event was the 2019 flood that devastated Tapuwatu Village, causing losses amounting to Rp 674.8 billion and displacing 9,908 people. The findings demonstrate that the dominant government narrative framing the floods as “natural disasters caused by high rainfall” constitutes a strategic denial that obscures structural responsibility. Empirical data including rates of deforestation, exceeded river carrying capacity, and the chronology of concession expansion correlated with disaster escalation support the ecological disaster thesis. Persistent poverty amid abundant natural resource wealth confirms the condition of a “sacrifice zone,” characterized simultaneously by distributive, recognitional, and procedural injustices.

The availability of a reliable backup power source is essential for supporting the operational continuity of the Indonesian National Army Fuel Filling Station (SPBT) at the Naval Academy (AAL). Interruptions in the main electrical supply can disrupt fuel distribution activities and reduce operational readiness. This study aims to determine the most appropriate emergency generator as a backup power source for SPBT AAL using the Analytical Hierarchy Process (AHP) method. Data were collected through observations, interviews, documentation, and questionnaires administered to experts with competencies in electrical systems and operational management. The evaluation was based on three criteria: purchase cost, spare parts availability, and ease of maintenance. Five generator alternatives were assessed, namely Cummins C10D6, Yanmar YTG10S, Traknus PL15P-SS, Honda EM10000, and Yamaha EF12000E. The results indicate that ease of maintenance is the most influential criterion with a priority weight of 0.627, followed by spare parts availability at 0.280 and purchase cost at 0.094. The global priority ranking shows that Yanmar YTG10S achieved the highest score of 0.438, making it the most suitable emergency generator for SPBT AAL. Furthermore, the consistency ratio (CR) values were below 0.10, indicating that the respondents’ judgments were consistent and that the results are valid for decision-making purposes.

This study aims to evaluate how petty cash management practices contribute to improving operational efficiency at PT Anugerah Langgeng Berkat Abadi. This research focuses on examining the implementation of the petty cash management system, applied procedures, and its impact on the smooth execution of daily operational activities. The study employs a descriptive qualitative approach, with data collected through interviews, direct observation, and documentation during the internship period. The collected data were analyzed systematically to describe the actual condition of petty cash management within the company. The results indicate that PT Anugerah Langgeng Berkat Abadi implements a fluctuating fund system in managing petty cash. Expenditures are initially recorded manually and then re-entered into the company’s internal digital system to maintain control and accountability. Petty cash is used to finance routine and urgent operational needs, such as office stationery, transportation costs, and other short-term expenditures. The company has established standard operating procedures governing the use, recording, and accountability of petty cash. Several challenges were identified, including delays in the disbursement and reimbursement process, which may affect time efficiency. However, overall, the petty cash management system is considered effective in supporting short-term operational needs without disrupting the stability of the company’s main cash. This study concludes that systematic and well-controlled petty cash management plays an important role in the company’s cost efficiency strategy and supports daily operational activities. These findings align with strategic management principles, where appropriate financial decision-making contributes to the achievement of long-term organizational objectives.

Dijkstra's algorithm is one of the algorithms in graph theory that is used to solve the problem of the shortest path of a graph at each vertex that has a non-negative value. This algorithm was discovered by Edsger Wybe Dijkstra, a scientist from the Netherlands. The search for the shortest route for product delivery can be calculated through the application of the Dijkstra algorithm in the problem being faced. The problem of decision making for selecting the shortest route is still manual, so it experiences several obstacles, including the absence of a systematic and computerized system to assist the decision-making process in determining the route for shipping goods, the determination of shipping routes still depends on manual estimates so that the time taken between deliveries becomes inconsistent, the operational costs of shipping are relatively high because there is no optimal route determination system. Facing these problems, a system is needed that can minimize delays and increase effectiveness in shipping goods, namely determining the shortest route using the Dijkstra algorithm. This system works by finding various alternative routes for shipping goods at PT AMSA to address various structured and unstructured problems using data and models. To process this data and models, a method called the Dijkstra algorithm is required. Based on the description above, researchers will create a method for determining the shortest route for shipping goods at PT AMSA using the Dijkstra algorithm to facilitate the company's process of determining the shortest route.

Digital transformation in Human Resource Management (HRM) has shifted the organizational paradigm from an administrative function to a strategic function focused on adaptive and sustainable human resource development. This study aims to systematically review the integration of digital technology in HRM practices with particular emphasis on inclusivity and organizational sustainability. The method employed is a literature review analyzing various studies related to the implementation of Artificial Intelligence (AI), big data analytics, and digital systems in recruitment, competency development, and employee performance evaluation. The findings indicate that digital transformation enhances operational efficiency, decision-making quality, and workplace flexibility. However, the adoption of digital technology also creates ethical challenges, including algorithmic bias, unequal access to technology, and concerns regarding employee data privacy. Therefore, the implementation of Equity, Diversity, and Inclusion (EDI) principles is essential in developing fair and inclusive HRM systems. Furthermore, continuous learning cultures and flexible work models have proven effective in supporting employee well-being while strengthening organizational resilience in facing global changes. This study emphasizes the importance of synergy between technological innovation, ethical leadership, and sustainability in building HRM systems that are responsive to the future of work.

This study aims to evaluate the effectiveness of the e-monev application at the Jambi Province Public Works and Public Housing Agency (PUPR) and to identify the constraints encountered in its management. The research used a qualitative descriptive method with data collection through in-depth interviews, observation, and documentation involving seven informants directly engaged in the application's management and operation. The analysis framework adopts the e-government success element theory by Indrajit (2002), comprising three dimensions: Support, Capacity, and Value. The findings reveal that the Support dimension is already strong, marked by leadership commitment, annual socialization and training, clear policy directives, and effective inter-unit coordination. In the Capacity dimension, human resource competence is generally adequate; however, technical constraints such as network instability, system slowdowns during concurrent access, and dependency on external programmers remain significant challenges. The Value dimension confirms that the e-monev application provides positive contributions to reporting efficiency, real-time monitoring, and data-based decision-making. Nevertheless, the overall effectiveness has not yet reached the optimal level due to persistent technical and infrastructure constraints. This study is expected to serve as an empirical basis for improving the quality of digital monitoring and evaluation systems in regional government agencies.

This study examines the implementation of Islamic business ethics in e-commerce transactions, with a specific focus on the Shopee platform. The research is motivated by the increasing growth of digital commerce accompanied by various ethical issues such as product misrepresentation, lack of transparency, and weak accountability of sellers. The objective of this study is to analyze how ethical principles, including honesty, fairness, and responsibility, are applied in online transactions. This research employs a qualitative approach using a systematic literature review method by analyzing 20 relevant scholarly articles published between 2020 and 2026. The findings reveal that although the platform provides adequate transactional systems, ethical violations are still prevalent, primarily due to information asymmetry between sellers and consumers. Trust emerges as the most influential factor in purchasing decisions, while perceived risk and security play supporting roles in shaping consumer behavior. Additionally, economic incentives such as promotions often override ethical considerations in influencing consumer decisions. The study implies that strengthening ethical enforcement, enhancing platform supervision, and improving consumer digital literacy are essential to ensure a sustainable and trustworthy e-commerce ecosystem.

The selection process for accepting new employees is one of the important stages in a company to ensure that the candidates accepted have qualifications that suit the company's needs. At WINMART, the selection process is still carried out manually, so it is less efficient and prone to errors. Therefore, a system is needed that can assist in more objective and efficient decision making. This Decision Support System (DSS) is designed to assist the selection process for recruiting new employees using the Simple Additive Weighting (SAW) method, which can assess several relevant criteria, such as work experience, education, skills and competency tests. This system was built on a web basis, so it can be easily accessed by parties involved in the selection process, such as HRD and managers. The SAW method was chosen because of its ability to convert various subjective criteria into more objective numerical scores, so that selection results can be more transparent and accountable. By using this system, it is hoped that it can increase efficiency, accuracy and transparency in the new employee selection process at WINMART, as well as facilitate decision making in selecting candidates who best suit the desired criteria.

.This study aims to analyse the role of Financial Information Systems (FIS) in supporting risk management, decision-making, and organisational performance in the digital transformation era. This study employs the Systematic Literature Review (SLR) method to examine articles indexed in Scopus from 2016 to 2026. The PRISMA framework is used to ensure a systematic, transparent article selection process, resulting in the selection of 37 relevant articles for further analysis. The results of the study show that Financial Information Systems make a major contribution to improving financial transparency, operational efficiency, the quality of strategic decision-making, and organisational risk mitigation. In addition, the integration of emerging technologies such as Artificial Intelligence (AI), FinTech, big data analytics, and cloud computing further strengthens the effectiveness of financial information systems in modern organisations. This study contributes theoretically by mapping research trends and identifying research gaps, while providing practical benefits for organisations seeking to increase competitiveness through digital financial systems. For future research, it is recommended to develop a more predictive and intelligent Financial Information Systems model to address future business dynamics.

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.

The development of artificial intelligence (AI) has driven fundamental changes in the way organizations manage work processes, make decisions, and coordinate teams in digital environments. However, an integrated understanding of how AI-based leadership affects digital team performance, particularly through the roles of transformational leadership and digital literacy, remains limited and dispersed across different streams of literature. This study aims to analyze the role of AI in supporting digital leadership, identify its influence on decision-making effectiveness and team performance, and examine the challenges and ethical implications of its implementation in organizations. The study employs a Systematic Literature Review (SLR) approach by reviewing relevant scholarly literature on AI, leadership, digital literacy, human–AI collaboration, and digital team performance. The findings indicate that AI-based leadership can enhance team management effectiveness when implemented through transformational leadership practices that foster vision, change readiness, learning, and team coordination, and when supported by adequate digital literacy. Conversely, barriers such as low trust in AI, digital competency gaps, resistance to change, and ethical issues remain major challenges. This study contributes by offering a conceptual synthesis that positions AI-based leadership, transformational leadership, and digital literacy within a single framework to explain the optimization of digital team performance in modern work environments.

This research is motivated by the increasing role of Artificial Intelligence (AI) in organizational transformation and the crucial function of leadership in ensuring its successful implementation. The primary objective of this study is to analyze the relationship between leadership, AI integration, and organizational performance, as well as to identify various challenges and supporting factors in the process. This study employs a systematic literature review (SLR) method by examining 30 relevant, reputable scientific articles from the Scopus and Google Scholar databases within the 2020–2026 timeframe through selection, evaluation, and thematic synthesis processes. The results indicate that AI integration significantly contributes to improving operational efficiency, data-driven decision-making quality, and organizational innovation. However, this success heavily depends on the role of adaptive, transformational, and digitally-oriented leadership capable of steering the technological vision. Conversely, major challenges were identified, such as employee resistance, limited digital competencies, and ethical issues surrounding data privacy. This study contributes to strengthening the conceptual understanding of leadership's role as a bridge between technology and organizational performance, while offering practical implications for management in designing effective, inclusive, and sustainable digital transformation strategies.