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The Hamlet Head Election is an important part of the practice of village democracy that demands transparent, accountable, and participatory implementation. However, in practice, various obstacles are still encountered, such as limited understanding of regulations by the committee, low democratic literacy of the community, and potential conflicts due to lack of information disclosure. This community service activity aims to accompany the implementation of the Hamlet Head Election in Wonokerto Village so that it runs transparently and accountably. The service methods used include socialization of hamlet head election regulations, technical assistance to the election committee, education to the community regarding the rights and obligations of voters, and monitoring and evaluation of the election implementation. The results of the activity show an increase in the committee's understanding of election procedures in accordance with the principles of village governance, increased community participation, and the implementation of more open and accountable election.Thus, this community service activity can have a positive impact on the implementation of more open and accountable elections, as well as creating a healthy and sustainable democratic climate at the village level.

The background of this research is based on the enormous potential of zakat, infaq, shadaqah, and waqf (ZISWAF) as Islamic social finance instruments which, if managed optimally and sustainably, can play a significant role in reducing poverty and promoting comprehensive economic independence among communities amid the ongoing challenges of social inequality. The purpose of this study is to explain the strategic function of ZISWAF in strengthening the community’s economy while emphasizing the urgency of professional, transparent, and targeted management for the improvement of public welfare at large. The research method used was library research, evaluating various literature sources such as books, scientific journals, and relevant previous research reports. The collected data was then analyzed using a qualitative descriptive approach to provide an in-depth understanding of the mechanism of economic empowerment through ZISWAF. Research findings show that ZISWAF plays a crucial role in improving economic welfare through a paradigm shift from consumptive assistance to productive assistance programs. Management oriented towards sustainability and transparency has proven effective in promoting economic ind ependence among low-income communities and significantly reducing poverty rates. The implication of this study confirm that strengthening regulations, digitizing management, and improving public literacy regarding ZISWAF are essential. Management institutions must continue to improve their accountability in order to increase public trust, so that ZISWAF can become a key development in the future.

This article examines the role of context and underlying assumptions in the formulation of econometric models for economic policy analysis. While econometric models are widely employed to support policy decisions, their construction is often treated as a purely technical process, overlooking the contextual factors that shape variable selection, model specification, and interpretation of results. This study explores how institutional settings, policy objectives, and behavioral considerations influence the assumptions embedded in econometric modeling. By drawing on policy documents, academic literature, and illustrative cases from applied economic research, the article highlights how implicit assumptions may affect the validity and relevance of econometric outcomes. The analysis emphasizes that econometric models are not value-neutral tools but are shaped by theoretical choices and contextual judgments made during their formulation. Understanding these dimensions is crucial to avoid misinterpretation of empirical findings and to enhance the usefulness of econometric analysis in policymaking. The study contributes to the methodological discussion in applied econometrics by encouraging greater transparency and reflexivity in model construction, particularly in the context of economic policy evaluation.      

Network service disruptions are critical issues that can negatively affect public trust and corporate reputation in the telecommunications industry. As one of the largest telecommunication providers in Indonesia, PT Telkomsel faces significant challenges in managing public issues related to network disturbances. This study aims to analyze how the Public Relations division of PT Telkomsel manages issues in handling network service disruptions in Indonesia.This research employs a qualitative descriptive approach by analyzing secondary data, including literature studies, official corporate communications, and media coverage related to network service disruptions. The findings indicate that PT Telkomsel’s Public Relations implements issue management through several systematic stages, namely issue identification, issue analysis, communication strategy formulation, message dissemination, and evaluation. The communication strategy emphasizes transparency, rapid response, and the use of digital media as the main channel to communicate with the public.Effective issue management enables the company to reduce negative public perceptions and maintain customer trust. This study confirms that strategic and proactive public relations communication plays an important role in managing network service disruption issues and protecting corporate reputation.

This study examines Terra Drone Indonesia's implementation of management dialogue in addressing crisis communication following a fire at the company's office building. The incident sparked a wave of negative sentiment on Instagram, marked by increased public comments assessing occupational safety, data security, and the company's transparency in conveying information related to the legal process. The study used a qualitative approach with a case study method to understand how the company developed a crisis communication strategy through official statements published on social media. Data were analyzed based on dialogic elements of communication, particularly empathy for victims, humanitarian commitment, and the company's position and normative and defensive stance in affirming legal handling and compliance measures. The results show that the company attempted to balance an empathetic narrative to mitigate public pressure with a defensive strategy to maintain institutional legitimacy. However, the dynamics of public opinion on Instagram indicate that the company's response has not fully met the expectations of two-way communication. This is evident in the dominance of one-way communication patterns and the lack of technical clarifications needed by the public, thus creating a productive economic outlook. Overall, dialogic management has been implemented responsively, but has not been optimal in building a space for dialogue and public trust as a whole.

Local government budget management is a crucial element in regional governance, as it directly impacts accountability, transparency, and efficiency in public service delivery. To support effective regional financial management, the Indonesian Government has established the Government Internal Control System (SPIP), as stipulated in Government Regulation Number 60 of 2008. This study aims to examine the role and practical implementation of SPIP in regional budget management through a case study of the Regional Financial and Asset Management Agency (BPKAD) of Dumai City. Using a qualitative case study approach, this study analyzes regional financial documents, audit reports from the Regional Audit Agency (BPKAD), as well as laws and regulations and internal policies governing SPIP implementation. The results indicate that SPIP has been implemented in BPKAD Dumai City throughout the budget management cycle, from planning and implementation to reporting and accountability. However, its implementation has not reached an optimal level due to constraints such as limited leadership commitment, inadequate human resource capacity, and suboptimal internal oversight mechanisms. Therefore, improving SPIP implementation is a strategic step to realize accountable, transparent, and performance-oriented regional financial governance.

The village is the lowest level of government that directly interacts with the community in providing and delivering public services. This requires the support of competent village officials, who are able to provide transparent and accountable services. Orderly and professional village administration is a crucial foundation for achieving good village governance. However, village administration issues remain a significant challenge that requires serious attention. This Community Service activity aims to improve the capacity of village officials in public service through administrative training in Rinbesihat Village, West Tasifeto District, Belu Regency. This community service activity involved university students and was implemented in several stages: initial coordination with the sub-district and village governments, problem mapping, activity implementation, and evaluation. The results of this community service activity were increased knowledge, which in turn improved the quality of village officials in village administration. With this training, it is hoped that village administration management can become more orderly, effective, and support the achievement of good and accountable village governance.

Public relations management is a strategic approach employed by the Ministry of Tourism and Creative Economy (Kemenparekraf) in providing public information related to tourism. This study aims to analyze the public relations management process of Kemenparekraf in disseminating tourism-related public information by using a descriptive qualitative approach and the public relations management theory proposed by Cutlip, Center, and Broom. Research data were obtained through in-depth interviews, literature review, and observation. The results indicate that Kemenparekraf implements the four stages of public relations management comprehensively: defining public relations problems, planning and programming, taking action and communicating, and evaluating the program. Kemenparekraf utilizes various digital and conventional platforms to disseminate tourism information, with an emphasis on transparency, accuracy, and information accessibility. The implementation of the Public Information Disclosure Act is also a major focus, including the provision of information that must be periodically disclosed, immediately announced, and available at all times. Effective public relations management enables Kemenparekraf to address challenges in the dissemination of complex and dynamic tourism information and to ensure equitable access to tourism information for various stakeholders, thereby supporting sustainable tourism development in Indonesia.

This research explores the role of human algorithm interaction mechanisms in enhancing trust, reliability, and user confidence in Decision Support Systems (DSS). Traditional DSS models often focus solely on algorithmic accuracy and performance, neglecting crucial factors such as transparency and user engagement, which are essential for building trust. By incorporating explainable AI (XAI) techniques like SHAP and LIME, real-time feedback mechanisms, and user-friendly interfaces, the study develops structured interaction models that improve the interpretability of AI-driven decisions. The results show that transparent decision-making processes and interactive features significantly enhance user trust, making DSS more reliable and easier to adopt. Users interacting with systems that provide clear, understandable explanations of decisions, along with real-time updates on the system’s confidence, reported higher levels of decision-making confidence, especially in high-stakes scenarios. These improvements lead to greater user engagement and adoption of the system in various domains, including healthcare and finance. The study also highlights the importance of balancing interpretability with efficiency in user interface design to ensure both trust and usability. The findings contribute to the design of more user-centric DSS that prioritize trust, interpretability, and cognitive factors, providing a framework for the successful integration of intelligent decision support systems in complex decision-making environments. Future research should focus on refining interaction models and exploring the broader applicability of these systems in different sectors.

Human–Robot Interaction (HRI) systems increasingly rely on data-driven approaches to interpret multimodal sensory inputs and support natural interaction. However, purely neural-based HRI models often suffer from limited interpretability and insufficient context-aware decision-making, which can reduce user trust and adaptability in dynamic interaction scenarios. To address these limitations, this study proposes a hybrid neural–symbolic HRI framework that integrates multimodal neural perception with explicit symbolic reasoning for adaptive and interpretable robot behavior. The proposed system combines deep neural networks for processing visual, speech, and gesture inputs with a rule-based symbolic reasoning layer that models interaction context, user states, and behavioral constraints. A loosely coupled integration strategy enables neural outputs to be transformed into symbolic representations, allowing logical inference to guide action selection while preserving perceptual accuracy. The framework was evaluated through controlled HRI experiments comparing a neural-only baseline with the proposed hybrid configuration across multiple interaction scenarios. Experimental results demonstrate that the hybrid neural–symbolic system significantly improves interaction accuracy, contextual responsiveness, and user satisfaction, while achieving substantial gains in interpretability. These findings indicate that symbolic reasoning effectively complements neural perception by enhancing transparency and context-aware adaptation without compromising performance. The study concludes that hybrid neural–symbolic architectures provide a promising foundation for developing trustworthy, adaptive, and human-centered HRI systems.

Honesty (ṣidq) is a fundamental moral value in Islam that serves as the foundation for personal integrity and social ethics. In the current era of globalization and growing materialistic culture, this value faces serious challenges as societal orientation shifts from moral virtue to economic achievement and social image. This study employs a narrative review method, analyzing recent literature on moral education, Islamic ethics, and contemporary social dynamics. The findings reveal that honesty functions not only as a personal virtue but also as a social force that strengthens public trust and national stability. However, the global wave of materialism has weakened the internalization of ṣidq, especially among younger generations. Restoring honesty as the moral identity of the nation requires synergy among character-based education, spiritual reinforcement, and public policies that promote transparency and integrity. The recontextualization of honesty through Islamic spiritual principles and Rokeach’s value theory offers a path toward moral recovery for Indonesian society amid the global challenges of the 21st century.

Autonomous decision-making systems increasingly rely on complex artificial intelligence models to operate in dynamic and safety-critical environments. While these models provide strong predictive capabilities, their black-box nature limits transparency, trust, and accountability. This study proposes a structured research methodology for integrating Explainable Artificial Intelligence (XAI) into autonomous decision-making systems. The research adopts a conceptual–analytical approach to develop an explainability-oriented framework that embeds transparency across perception, decision-making, and action execution stages. The methodology includes literature-driven problem identification, conceptual framework construction, classification and mapping of XAI methods, and formulation of explainability evaluation criteria. The results demonstrate that effective explainability in autonomous systems requires a hybrid integration strategy, combining in-model transparency with post-hoc explanation mechanisms. A structured mapping of XAI techniques to autonomous system components and a conceptual decision-flow diagram are presented to illustrate explainability integration. The findings highlight that layered and context-aware explainability enhances system interpretability, supports human oversight, and improves safety relevance without compromising autonomous operation. This study contributes a reusable methodological foundation for the design and evaluation of explainable autonomous systems, offering practical guidance for future empirical validation and real-world deployment in safety-critical applications.

This study analyzes the juridical implications of delegated authority in the context of business license signing by heads of regional offices acting on behalf of regents. Using a qualitative approach with library research, the paper explores the legal foundation, validity, and administrative consequences of delegation within local governance. The findings indicate that delegation of authority is a legitimate administrative mechanism recognized under Indonesian law, particularly within Law No. 23 of 2014 concerning Regional Government. However, its implementation frequently lacks procedural clarity, leading to potential legal defects (ultra vires) in administrative decisions. The study emphasizes that the validity of business permits depends on both formal and substantive fulfillment of delegation requirements through explicit legal instruments such as regional head decrees. Improper delegation not only invalidates administrative acts but also undermines legal certainty and public trust in local governance. Theoretically, this research contributes to strengthening the doctrine of state administrative legality, while practically, it provides recommendations for standardizing delegation mechanisms to enhance transparency, accountability, and legal compliance in regional public service delivery.

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 aims to analyze the implementation of Good Corporate Governance (GCG) principles at PT Bank Mandiri (Persero) Tbk as one of the state-owned banks that plays a strategic role in the Indonesian banking system. The implementation of GCG is crucial in maintaining public trust, improving performance, and ensuring business sustainability in the banking sector. This research employs a qualitative method with a descriptive approach, focusing on secondary data analysis obtained from annual reports, corporate governance reports, sustainability reports, and official information published on the website of PT Bank Mandiri (Persero) Tbk. The results indicate that Bank Mandiri has consistently implemented the principles of transparency, accountability, responsibility, independency, and fairness in its corporate governance system. These principles are reflected in information disclosure practices, clear organizational structures, regulatory compliance, independent decision-making processes, and fair treatment of all stakeholders. Overall, the implementation of GCG at PT Bank Mandiri (Persero) Tbk contributes positively to strengthening internal control systems, enhancing public trust, and supporting the stability and sustainability of banking operations.

Explainable Artificial Intelligence (XAI) has become a critical area of research within artificial intelligence, focusing on improving the transparency and interpretability of machine learning (ML) models, often referred to as "black-box" models. The need for XAI techniques arises from the inherent complexity of ML models, which can make their decision-making processes difficult for users to understand. This study investigates various XAI techniques, including LIME (Local Interpretable Model-agnostic Explanations) and SHAP (SHapley Additive exPlanations), to assess their impact on model interpretability without significantly compromising predictive performance. A comparative experimental design was used, applying these XAI methods to different ML models, including deep neural networks and ensemble methods, within large-scale enterprise data analytics systems. The results indicate that XAI methods significantly enhance model transparency and decision traceability, allowing users to understand the influence of individual features on predictions. While a slight reduction in predictive accuracy was observed, especially with simpler models, the trade-off between interpretability and performance was deemed acceptable, particularly in fields requiring transparency, such as healthcare, finance, and autonomous systems. The use of XAI in enterprise data systems has practical implications for fostering trust and enabling informed decision-making among stakeholders. Furthermore, the study discusses the challenges and limitations of applying XAI techniques, such as complexity, scalability, and model-specific limitations. Future research is suggested to focus on developing more scalable and efficient XAI methods, enhancing their applicability across various model types, and addressing the challenges of real-time applications. This will be crucial in ensuring the widespread adoption of XAI in critical domains, promoting the ethical use of AI while maintaining predictive accuracy.

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 rapid growth of digital marketplaces has fundamentally transformed consumer decision-making processes by intensifying price transparency, product comparability, and information exposure. In highly competitive marketplace environments, consumers are frequently confronted with numerous product alternatives and dynamic pricing structures, which shape how they evaluate options and ultimately decide to purchase. This study examines the effects of product variety and price perception on consumers’ purchase decisions in the context of ROSCA tumbler products sold on the Shopee marketplace. Using a quantitative explanatory approach, this research employs a survey-based design to analyze the relationships among variables and to estimate their relative effects through multiple linear regression analysis. Data were collected from 100 respondents who had previously purchased ROSCA tumblers on Shopee, selected using purposive sampling based on predefined criteria. The research instrument consisted of 15 Likert-scale items measuring product variety, price perception, and purchase decision. Data analysis included descriptive statistics, instrument validity and reliability testing, regression assumption diagnostics, and hypothesis testing using both partial (t-test) and simultaneous (F-test) procedures. The findings reveal that product variety has a positive and significant effect on purchase decisions, indicating that consumers are more likely to finalize purchases when they perceive product options as sufficiently diverse, relevant, and comparable. Price perception also exerts a positive and significant influence and demonstrates a stronger relative effect compared to product variety. This result underscores the central role of perceived price fairness, competitiveness, and value-for-money in shaping purchase decisions within transparent and highly competitive marketplace settings. Simultaneously, product variety and price perception explain a substantial proportion of variance in purchase decisions, highlighting their combined importance as key marketing stimuli. These findings contribute to the literature on digital consumer behavior by providing empirical evidence from a specific marketplace–product context and offer practical implications for sellers and brand managers in optimizing assortment design and pricing strategies to enhance conversion rates in online marketplaces

This study explores strategies for mobilizing financial resources and multi-stakeholder participation in Islamic education financing to achieve institutional financial independence. The research was conducted at SMA Muhammadiyah 5 Yogyakarta, a private Islamic secondary school implementing a financing model based on Sharia values and Total Quality Management (TQM) principles. A qualitative case study approach was employed, utilizing primary data from in-depth interviews with school administrators and observations of financial management practices, as well as secondary data from budget plans, government funding reports, and cooperation documents with philanthropic institutions. Data were analyzed using an interactive model involving data reduction, data presentation, and inductive conclusion drawing. The findings reveal that financial independence is strengthened through diversified funding sources, including government support, parental contributions, Islamic philanthropy, and school-based business units. Transparency and accountability are maintained through open financial reporting and stakeholder involvement. The study highlights that integrated Islamic education financing aligned with Sharia values and TQM enhances institutional sustainability, educational quality, and organizational competitiveness.

Digital transformation initiatives have become essential for organizations seeking to remain competitive in today’s rapidly evolving technological landscape. However, many organizations face challenges due to ineffective Information Systems (IS) governance, which hampers strategic decision-making and the successful execution of these initiatives. This study aims to develop an IS governance framework that enhances decision-making quality by aligning IT decisions with organizational goals during digital transformation efforts. The proposed framework addresses existing gaps in current IS governance models, offering a solution to common challenges such as inadequate governance structures, resource constraints, and misalignment between IT and business strategies. The framework was developed through a mixed-method approach, including conceptual framework development, expert consensus via the Delphi method, and organizational validation studies. Key findings reveal that the framework improves transparency in decision-making, enhances accountability for IT decisions, and ensures better alignment between IT strategies and organizational objectives. By embedding agile leadership and data-driven decision-making principles, the framework enables organizations to respond effectively to the fast-changing dynamics of digital transformation. This study also compares the proposed framework to existing models such as COBIT and ITIL, highlighting its unique features, including its adaptability to the fluid nature of digital transformation. The framework's strengths include its comprehensiveness and flexibility, though its application may face challenges in organizations with limited digital maturity or rigid governance structures. Future research directions include exploring the integration of emerging technologies into the framework and its applicability across different organizational contexts.