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Advancements in information technology encourage MSMEs to utilize information systems to enhance the effectiveness of their business management. Es Teh Arjuna, an MSME in Tegal City, faces challenges in monitoring partner sales and managing revenue because transactions are recorded manually using disparate methods; this results in slow data recapitulation, a risk of recording errors, and difficulty for the business owner in quickly accessing sales information. This study aims to analyze requirements, design, develop, and test a web-based information system for partner sales and revenue that provides information in  real-time. The Waterfall model was used for system development, while data collection involved observation, interviews, and a literature review. The system was developed using PHP and MySQL and tested via Black Box Testing. The results demonstrate that the system successfully integrates sales data from all outlets into a centralized database, streamlining the management of products, outlets, employees, cashiers, and sales transactions, as well as facilitating the generation of revenue reports for specific periods. Furthermore, the system enables the business owner to monitor sales performance more quickly, accurately, and systematically, thereby supporting decision-making and improving the operational efficiency of Es Teh Arjuna.

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.  

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.

Indonesia’s Free Nutritious Meal Program (MBG) requires an efficient and adaptive supply chain system to ensure timely distribution, cost efficiency, and adequate nutritional delivery for a large number of beneficiaries. However, conventional supply chain approaches are generally static and unable to respond effectively to dynamic demand, supply uncertainty, and logistical constraints. This study proposes a Multi-Objective Reinforcement Learning (MORL) model to optimize the MBG supply chain by simultaneously considering distribution cost, delivery timeliness, service level, nutritional adequacy, and food waste reduction. The model is developed using a simulation-based environment representing real-world supply chain conditions, including demand variability, transportation limitations, and kitchen capacity constraints. The results show that the proposed approach achieves cost reductions of 15–22%, improves delivery timeliness by 18–25%, maintains a service level above 90%, increases nutritional fulfillment by 12–18%, and reduces food waste by 10–15% compared to baseline methods. Sensitivity analysis further demonstrates the robustness of the model, with minimal performance degradation under disruption scenarios. These findings indicate that Reinforcement Learning provides a scalable and adaptive solution for optimizing large-scale public food distribution systems. The proposed model contributes both theoretically by integrating multi-objective optimization within an RL framework and practically by supporting data-driven decision-making for improving the effectiveness of the MBG program in Indonesia.

Educational planning management is an essential process in managing educational institutions to achieve educational goals effectively and efficiently. One form of implementing educational planning management is through the preparation of the Madrasah Work Plan (RKM) and School Work Plan (RKS). This article aims to describe the concept of educational planning management through the preparation of RKM/RKS, their objectives, preparation processes, and implementation in schools and madrasahs. The research method used is library research with a qualitative descriptive approach by collecting data from books, scientific journals, government regulations, and other supporting documents. The results of the study indicate that RKM/RKS has a strategic role as a guideline for implementing educational programs, a basis for decision-making, an evaluation tool, and an instrument for improving the quality of education. The preparation of RKM/RKS is carried out systematically through team formation, school/madrasah self-evaluation, formulation of priority programs, preparation of medium-term and annual work plans, and budgeting plans. Proper implementation of RKM/RKS can improve the effectiveness of educational management, accountability, transparency, and the quality of educational services in schools and madrasahs.

The rapid growth of digital technology and social media has reshaped communication practices, consumer behavior, and marketing approaches, particularly among Generation Z, who are widely recognized as digital natives. For this generation, social media serves as a major channel for obtaining information and exploring product references before making purchase decisions. In this environment, influencer marketing has emerged as a prominent promotional approach because it can foster audience interaction, emotional connection, and trust more effectively than conventional advertising. This study examines the role of influencer marketing in shaping the digital behavior of Generation Z in Indonesia. A qualitative literature review method was employed by analyzing secondary sources drawn from academic journals, books, and related publications. The findings indicate that influencer marketing has a meaningful influence on information-seeking behavior, decision-making processes, and the level of digital engagement among Generation Z. Influencers are commonly viewed as more credible, relatable, and authentic sources of information. Furthermore, the effectiveness of influencer marketing is determined more by credibility, authenticity, and the quality of interaction than by follower count alone. These findings suggest that companies should adopt digital marketing strategies that are more interactive, personalized, and relationship-oriented in order to engage Generation Z more effectively.

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.

Decentralisation and democracy are two interrelated concepts in governance reform, particularly in improving the effectiveness of regional development. Decentralisation is often seen as an instrument to strengthen democracy by bringing the decision-making process closer to the people. This study aims to analyse the trend of research publications on decentralisation in Indonesia using a bibliometric analysis approach. The articles used in this study were obtained from Scopus data. From 472 articles found in the scopus database between 1999 and 2025. The selected articles were then managed using biblioshiny and Vosviewer software. The results show that publications related to decentralisation have fluctuated over the last 27 years. The article with the most citations entitled Decentralisation and Democracy in Indonesia: A Critique of Neo-Institutionalist Perspectives has 213 citations. Meanwhile, the highest affiliation shows that the University of Indonesia is the institution with a total of 25 publications. The mapping of articles based on the relationship between keywords (co-occurance) is formed into 8 clusters, each cluster describes topics that are often discussed in decentralisation-related literature such as Indonesia, decentralization, democracy, local government, governance approach, election, Asia and southeast Asia.

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 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.

The digital transformation driven by the acceleration of Artificial Intelligence (AI) has fundamentally transformed leadership paradigms and the structure of the modern workplace. This study aims to provide an in-depth analysis of the various strategic opportunities and systemic risks arising from the integration of AI into contemporary organizational leadership practices, where technology is no longer merely a tool but a collaborative partner in managerial processes. Using a Systematic Literature Review (SLR) method on 30 reputable scientific journals with publications spanning up to 2026, this article analyzes the transition of the leader’s role from a conventional hierarchical model toward the concept of Augmented Leadership. Data analysis results indicate that AI implementation offers significant opportunities through data-driven decision-making systems with high precision, intelligent resource allocation optimization, and enhanced leadership intervention effectiveness, which has been documented to reach up to 35%. However, this transformation also brings a series of complex multidimensional risks, including algorithmic biases that could trigger inequality cascades, ethical dilemmas related to operational transparency (black box), and the potential erosion of the meaning of work for employees. The discussion in this article emphasizes that the success of this transformation depends not only on technical expertise, but also on redefining leadership competencies to prioritize emotional intelligence and ethical governance frameworks such as the CARE Framework (Control, Awareness, Responsibility, and Evaluation).

The advancement of digital technology has significantly transformed organizational decision-making, particularly in modern leadership contexts that demand rapid and data-driven responses. Artificial Intelligence(AI) has emerged as a strategic technology capable of enhancing accuracy, speed, and effectiveness in decision-making through comprehensive data analysis. This study aims to analyze the role of AI in supporting leadership decision-making and its implications for organizational effectiveness using a narrative literature review approach. Secondary data comprising peer-reviewed national and international journal articles were analyzed to identify patterns, themes, and interactions between AI, leadership, and decision-making processes. The findings indicate that AI functions not only as a data analysis tool but also as a strategic element that strengthens leaders’ capabilities in evidence-based decision-making, improves team coordination, and optimizes organizational processes. Thematic synthesis identified three main domains analytics and predictive capabilities, leadership strategies, and implementation challenges that form the basis for integrating AI into managerial practice. This study contributes theoretically by expanding the digital leadership and technology-based decision-making framework and practically by providing guidance for organizations to optimize AI utilization to enhance decision quality and efficiency. The research also offers directions for future empirical studies to explore AI-leadership interactions across various organizational sectors, supporting more adaptive, effective, and data-driven decision-making in the digital era.

. A website is a crucial digital promotion medium for companies to convey information and attract potential customers. However, many websites experience low user interaction despite having high visitor traffic. This study aims to analyze the effectiveness of A/B Testing implementation in improving the performance of the PT Pamor Putra Mandiri website. A quantitative experimental approach was used, applying A/B Testing to two page variations: Variation 1 (Rafting & Outdoor Activity theme) and Variation 2 (Camping & Accommodation theme). The evaluation focused on three main performance metrics: Click, Page Visit, and Engagement. The results show that Variation 1 consistently outperformed Variation 2 across all metrics. Statistical testing using a two-proportion z-test confirmed that these differences were statistically significant (p-value < 0.05). Therefore, A/B Testing proves to be an effective method in identifying superior content strategies and page structures, as well as a relevant tool for data-driven decision-making in corporate website development.

Leadership in educational management has a strategic role in determining the success of educational implementation. This study aims to examine the integrative paradigm between psychology and leadership in educational management, focusing on the psychological dimensions of educational leadership. This research employs a qualitative approach using a systematic literature review method. Data were collected from scientific articles published between 2020 and 2026 through Google Scholar using Publish or Perish. The findings indicate that the integration of psychological perspectives into leadership significantly enhances organizational effectiveness, particularly in fostering work motivation, strengthening interpersonal communication, and improving adaptive decision-making. Furthermore, psychological approaches contribute to conflict management and the development of a positive organizational climate. The study also highlights that leadership effectiveness is strongly influenced by psychological characteristics such as personality, emotional intelligence, and empathy. Therefore, integrating psychology into leadership serves as a strategic foundation for advancing educational management and improving human resource performance sustainably.

The coffee shop industry in Indonesia is experiencing rapid growth that requires business owners to optimize data-driven strategies. This study aims to analyze customer preferences at Semanis Coffee and Resto using data mining methods  to support more effective business decision-making. The method used is Market Basket Analysis with the FP-Growth algorithm for association rule mining and the K-Means algorithm for customer segmentation. The research data consists of 672 sales transactions during the March-May 2025 period. The results of the association analysis with a minimum support of 0.004 and a minimum confidence of 0.2 resulted in five valid rules with a lift ratio above 1. The strongest rule is the combination of Americano→Milk Choco with a confidence of 42.9% and an elevator ratio of 5.229, indicating a strong linkage between products. The most popular products are Milk Choco (10.8%) and Americano (8.5%). Customer segmentation analysis identified three clusters: Cluster 0 (Loyal Customers) 80% with high frequency but low transaction value; Cluster 1 (Occasional Customers) 10% with low activity; and Cluster 2 (Large Buyers) 10% with high transaction value but low frequency. This study concludes that product bundling strategies, loyalty programs, reactivation campaigns, and premium services can be applied to increase the effectiveness of coffee shop businesses.

This study aims to analyze the role of assessment in decision-making within guidance and counseling services. Assessment plays a crucial role in providing accurate, objective, and comprehensive data regarding students’ characteristics, needs, and problems. This research employs a qualitative approach using a literature review method by analyzing 25 relevant scholarly sources related to assessment, measurement, and counseling services. The findings indicate that measurement serves as the fundamental basis of assessment, which involves systematic processes to obtain quantitative data. The quality of assessment results is highly influenced by the reliability and validity of the instruments used. Reliable instruments ensure consistency, while valid instruments ensure accuracy in measuring intended variables. Furthermore, assessment functions as a basis for diagnosis, planning, implementation, and evaluation of guidance and counseling services. The study also reveals that the application of assessment in schools is not yet optimal due to several factors, including limited counselor competence and lack of effective use of instruments. In addition, the integration of technology and the use of both test and non-test instruments have been shown to improve the accuracy and effectiveness of assessment. In conclusion, systematic and well-implemented assessment significantly enhances the quality of decision-making in guidance and counseling services. Therefore, improving counselors’ competencies and optimizing the use of assessment instruments are essential to support more effective counseling practices

The abuse of authority by public officials within Indonesia’s governmental administration has become an increasingly urgent issue to address. Such misconduct undermines the fundamental principles of good governance  including transparency, accountability, and justice which are essential for ensuring efficient and effective government operations. This study aims to conduct an in-depth analysis of the forms of abuse of authority by public officials, the factors influencing such behavior, and its impact on the effectiveness of governance and public trust. The research employs a normative approach with a prescriptive legal method, analyzing legislation related to the abuse of authority as well as a case-based approach to explore the implementation of authority by public officials in governmental practice.The findings indicate that abuse of authority may occur in various forms, such as exceeding the limits of granted power, conflating different authorities, or acting arbitrarily for personal or group interests  all of which contradict the principle of legality governing governmental actions. Moreover, such practices negatively affect the quality of public services and tarnish the image of governmental institutions. The study also finds that although Law No. 30 of 2014 on Government Administration provides a clear legal framework, its implementation remains hindered by weak internal and external oversight systems. Therefore, this research recommends strengthening more effective supervision mechanisms, enhancing transparency in administrative decision-making processes, and involving the public in monitoring efforts to ensure that public officials exercise their authority in accordance with established objectives in pursuit of a clean and just government.

The development of Artificial Intelligence (AI) integrated with biometric technology has opened new opportunities in leadership development, particularly in enhancing emotional regulation capabilities within high-stakes environments. This study aims to analyze the role of AI-driven biometric feedback in improving self-awareness, emotional regulation, and decision-making quality among leaders. The study employs a systematic literature review approach by examining recent reputable scientific publications related to AI, biometrics, and leadership. The findings indicate that physiological data such as heart rate variability (HRV) and galvanic skin response (GSR), when processed through AI systems, can provide real-time feedback that enhances individuals’ ability to recognize and regulate emotions adaptively. Furthermore, the integration of this technology contributes to improved accuracy and consistency in decision-making under pressure. The results also reveal that the effectiveness of implementation is influenced by both technical and non-technical factors, including data quality, algorithm accuracy, and user acceptance. This study contributes to strengthening the integration of psychological and technological approaches in modern leadership research and offers practical implications for developing data-driven leadership training programs in the digital era.