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This study aims to analyze the regulation and implementation of the authority to test laws and regulations (judicial review) in the Indonesian state system based on the 1945 Constitution of the Republic of Indonesia. This study applies a normative juridical method using three main approaches, namely the statute approach, the conceptual approach, and the historical approach. The legal data collected includes primary, secondary, and tertiary legal materials, which are then reviewed through qualitative analysis. The results of the study show that normatively the division of judicial review authority between the Supreme Court and the Constitutional Court has been expressly regulated in Article 24A paragraph (1) and Article 24C paragraph (1) of the 1945 Constitution of the Republic of Indonesia. The Supreme Court is given the authority to test regulations under the law against the law, and the Constitutional Court is given the authority to test laws against the 1945 Constitution. This division of authority is a manifestation of the principle of separation of powers and the mechanism of checks and balances after the third amendment to the 1945 Constitution. However, in practice, this two-roof judicial review system tends to give rise to conceptual and practical problems, such as overlapping authority and differences in decisions between the Supreme Court and the Constitutional Court which have the potential to create legal uncertainty and reduce public trust in the judicial institution. Therefore, it is necessary to reorganize the authority of judicial review by strengthening coordination between institutions or unifying the authority of judicial review which is centered on one institution only in order to guarantee legal certainty, harmonization of norms, and supremacy of the constitution in the Indonesian state system.  

This paper attempts to explore the theological meaning of the Book of Job, particularly in the context of Job's suffering and God's justice. The author focuses this writing on understanding faith in suffering, with the aim of providing a deep interpretation of faith in suffering. The Book of Job is part of the Wisdom Books group consisting of 42 chapters, which discuss the suffering experienced by Job himself, and how he responded to the trials given to him by Satan with God's permission. This writing uses qualitative methods and a library research approach. This paper explains that the Book of Job provides a complex picture of the relationship between human suffering and God's justice. The main finding in this writing is highlighting the urgency of deep reflection on trust, tests of faith, and the meaning of life, leading to the conclusion that suffering is interpreted as an instrument of refining faith in God, then guiding believers towards His will and providence. Therefore, the conclusion of this paper is that suffering is interpreted as an instrument of priesthood of God, which then guides humans who believe in God's will and providence.

Business activities are essential for helping the economy of society function properly. When starting a business, people usually want to make money, but they are also supposed to follow good values, like being honest in their dealings. In real life, some businesses still do unfair things, like giving false information about products, changing prices unfairly, lowering the quality of goods, and using incorrect measurements when selling items. This research focuses on explaining what honesty means and how it should be used in business according to the principles of Islamic economics. The study uses a qualitative method called literature review, which involves looking at books, journal articles, and other sources that talk about Islamic business ethics. The results show that honesty is a key value in Islamic business because it helps build trust with customers, ensures fair deals, and creates positive relationships between sellers and buyers. The value of honesty in the business world can be demonstrated through transparancy of information about products, honesty in pricing, accuracy in measurement, and not hiding defects in the goods being sold. From an Islamic economics perpective, business activities should not only focus on material income, but also on the value of blessings, ethical responsibility, and mutual prosperity. Thus, the application of honesty in an important foundation for building fair, transparent bisuness practices that are in line with Islamic economic prinsiples.

This study aims to explore employees’ work experiences related to work-life balance and compensation in shaping employee performance at CV. Sepanjang Masa (Masa Kreatif), a social media agency located in Makassar. A qualitative approach with a descriptive-analytical field design was employed. Data were collected through in-depth interviews, passive participant observation, and documentation involving 11 informants from both management and creative teams. Data analysis followed processes of data reduction, data display, and conclusion drawing, with trustworthiness ensured through triangulation techniques. The findings reveal that employees’ work-life balance experiences are dynamic and heterogeneous. Work flexibility provides opportunities for personal time management; however, rapid response demands and intensive content production blur the boundaries between work and personal life. A supportive, communicative, and collaborative work environment acts as a protective factor that mitigates work pressure and fosters creativity. Compensation is perceived not only as financial remuneration but also as a symbol of recognition, professional development opportunities, and organizational appreciation, although gaps remain between employee expectations and organizational capacity. Integratively, work-life balance, work environment, and compensation constitute interconnected work experiences influencing employee engagement and performance within the digital creative industry.

This study aims to analyze the implementation of Islamic marketing and digital-based Corporate Social Responsibility (CSR) at Pegadaian Syariah Surabaya from the perspective of maqashid sharia and assess how the integration of the two supports the sustainability of the institution and public trust. The background of the study departs from the development of digital technology that requires Islamic financial institutions to maintain transparency, fairness, data security, and sharia compliance in all marketing activities and social programs. The research method uses a descriptive qualitative approach through in-depth interviews, participatory observation, and documentation analysis on digital services and CSR activities of Pegadaian Syariah. The results show that digital Islamic marketing not only functions as a promotional tool, but also as a sharia education medium that upholds the values ​​of shidq, amanah, and maslahah, thereby supporting hifz al-din, hifz al-mal, and hifz al-‘aql. Meanwhile, the implementation of CSR covers the fields of religion, health, education, and empowerment of MSMEs that are in line with the five dimensions of maqashid sharia. The integration of Islamic marketing and CSR creates a strategic synergy that increases public trust, strengthens the institution's legitimacy, and ensures the sustainability of Pegadaian Syariah in the digital era. This research provides theoretical contributions regarding maqasid-based marketing and CSR strategies, as well as practical recommendations for strengthening sharia governance and digital education programs.

Child grooming is a form of non-physical sexual abuse that involves gradual emotional manipulation, often making it difficult to detect. It typically begins with the abuser gaining the child’s trust and gradually introducing inappropriate behavior, with the goal of sexual exploitation. This study aims to explore the phenomenon of child grooming and the crucial role of guidance and counseling in preventing and managing such cases. The method employed is a literature review, analyzing various relevant scientific articles and research studies. The findings indicate that child grooming is influenced by several factors, including individual traits, family dynamics, and the use of digital media, which has become an increasingly prevalent platform for such abuse. Victims of grooming often experience significant psychological and social consequences, including trauma, emotional distress, and difficulty in forming healthy relationships. Guidance and counseling services are essential in the prevention, early detection, and intervention in grooming cases. These services provide support for both potential victims and their families, helping them understand and recognize the signs of grooming. Additionally, counseling plays a key role in victim recovery, offering psychological support to overcome the lasting impacts of abuse. This research underscores the need for proactive measures and comprehensive guidance and counseling strategies to address child grooming effectively.

Explainable artificial intelligence (XAI) has become a critical requirement in cybersecurity due to the high-stakes nature of security decision-making and the limitations of black-box learning models. This study investigates the construction of an explainable cybersecurity knowledge representation by leveraging standardized terminology from the NIST cybersecurity glossary. The primary problem addressed is the lack of transparent and semantically grounded reasoning mechanisms in existing AI-driven cybersecurity systems, which limits trust, accountability, and analyst adoption. To address this challenge, we propose a NIST-based semantic knowledge graph that embeds explainability directly into its ontology structure and reasoning process. The proposed framework systematically extracts definitional entities and relations from NIST glossary entries to construct a domain ontology and a multi-relational knowledge graph. A rule-based semantic relation extraction method is employed to ensure faithful, interpretable, and reproducible reasoning paths. The resulting knowledge graph contains over 3,000 cybersecurity concepts and approximately 27,000 semantic relations, covering hierarchical, associative, dependency, and mitigation semantics. Experimental evaluation demonstrates that the proposed approach achieves a high level of explainability, with 92.4% of reasoning outcomes being fully traceable and only 1.4% classified as non-traceable. Most explainable reasoning paths are limited to two or three hops, indicating an effective balance between inferential depth and human interpretability. Structural analysis further confirms the presence of meaningful hub concepts that support multi-hop semantic inference. These results confirm that ontology-driven, standard-based knowledge graphs provide a robust foundation for explainable cybersecurity intelligence. The study concludes that explainability-by-design, grounded in authoritative standards, offers a viable and trustworthy alternative to opaque AI models for cybersecurity applications.

This study examines the application of Transparent Artificial Intelligence (AI) for fraud detection in public welfare programs using publicly available administrative data. Persistent challenges in welfare governance such as misallocation, fraud, and data inaccuracy necessitate analytical frameworks that are both effective and explainable. The research aims to design and evaluate an interpretable anomaly detection system capable of identifying irregularities in welfare distribution while maintaining transparency and accountability. Methodologically, the study employs two unsupervised models Isolation Forest and Local Outlier Factor (LOF) to detect anomalies in sub-district-level welfare data, incorporating features such as population size, number of beneficiaries, and coverage ratio. An Explainable AI (XAI) framework integrating surrogate Random Forests, Permutation Feature Importance (PFI), and local linear surrogates (LIME-like) is applied to ensure interpretability of both global and local model behaviors. Findings reveal that receivers per 1000 population and percentage coverage are dominant determinants of anomaly scores. Fifteen administrative units were flagged for potential inconsistencies suggesting over- or under-reporting of beneficiaries. Cross-validation between IF and LOF models confirmed consistency in identifying anomalous regions. The integrated XAI explanations enhance transparency, enabling policymakers and auditors to trace the rationale behind detected anomalies. In conclusion, the proposed Transparent AI framework demonstrates that combining anomaly detection with interpretability tools can strengthen accountability and fairness in welfare administration. It offers a reproducible, ethical, and data-driven approach to social program monitoring, reinforcing public trust and supporting responsible AI governance.

High-dimensional clinical data exhibit complex and non-linear relationships among patient attributes, where outcomes are often influenced by feature interactions rather than isolated variables. However, many existing machine learning models prioritize predictive performance while providing limited interpretability and insufficient insight into interaction structures. This study aims to address this limitation by developing an interpretable and robust framework for feature interaction mining in clinical data. We propose a hybrid tree–neural modeling framework that explicitly captures and ranks feature interactions while maintaining stable predictive performance. Tree-based ensemble models are employed to identify non-linear interaction patterns, while neural representations enhance learning flexibility and generalization. The framework integrates interaction importance analysis, cross-validation–based stability assessment, and evaluation across multiple data splits to ensure robustness and interpretability. Experiments conducted on a real-world high-dimensional clinical dataset demonstrate that the proposed approach achieves consistent predictive performance, with AUC values ranging from 0.628 to 0.641 across five cross-validation folds (mean AUC ≈ 0.633). Performance remains stable under varying train–test splits, indicating strong generalizability. Interaction analysis reveals that a small number of dominant feature interactions—such as age combined with length of hospital stay and medication count combined with diagnostic information—consistently contribute to model predictions, appearing in over 80% of validation folds. Ablation studies further confirm that removing interaction-aware components leads to noticeable performance degradation, highlighting their importance.  In conclusion, this study demonstrates that explicit feature interaction modeling enhances interpretability, stability, and generalization in clinical prediction tasks. The proposed hybrid framework provides a reliable foundation for developing trustworthy and transparent clinical decision-support systems

This study aims to analyze the effectiveness of public service policy implementation at the Regional Technical Implementation Unit of the Freshwater Fish Cultivation Center (UPTD BBIAT) in Pekalongan Regency, focusing on the influence of service quality on fish farmers' satisfaction mediated by trust. The research employs a mixed-methods approach with a concurrent embedded design, combining a survey of 40 fish farmers and in-depth interviews with 5 key informants from the UPTD and Agency levels, along with observation and document analysis. The theoretical framework is built on New Public Service Theory, Policy Implementation Theory, and the SERVQUAL, trust, and public satisfaction concepts. The research findings indicate that all three variables are in the high category with robust and significant positive correlations: service quality with trust, service quality with satisfaction, and trust with satisfaction. Trust has been shown to play a strong mediating role in the relationship between service quality and fish farmers' satisfaction. The assurance and empathy dimensions are the strengths of UPTD BBIAT, while tangibles and reliability require improvement through infrastructure modernization and enhanced consistency in seed availability. Theoretically, this research confirms the applicability of the SERVQUAL model and trust theory in the context of public services in the fisheries sector. In practice, it provides strategic recommendations to improve policy implementation effectiveness through infrastructure strengthening, human resource development, service digitalization, and enhanced institutional coordination.

This study investigates the evolutionary and research trends on social capital and economic resilience within the small and medium enterprises sector through bibliometric analysis. Data were obtained from the google scholar through Publish or Perish software, covering the period from 2020 to 2025, then organized using Mendeley and analyzed through VOSviewer. The results indicate that topic of social capital is a central link between trust, innovation, and business sustainability. Research trends have shifted from theoretical approaches to practical applications, particularly during times of crisis or challenges. Overall, social capital is proven to be instrumental in strengthening the resilience and sustainability of SMEs, while also serving as the foundation for developing sustainable economic policies based on social capital.

Service quality is a critical issue faced by service providers, as it plays a significant role in shaping customer satisfaction and maintaining customer trust for future services. A decline in service quality over time may negatively affect customers’ perceptions and loyalty. Therefore, this study aims to examine the effect of service quality dimensions on customer satisfaction. This research employed a quantitative approach using primary data collected through a survey method. The sampling technique used was probability sampling with a random sampling method, involving 98 customers as research respondents. Data were analyzed using SPSS version 24. The service quality dimensions analyzed in this study were Tangible, Reliability, Responsiveness, Assurance, and Empathy. The results of the analysis revealed that Tangible and Responsiveness did not have a significant effect on customer satisfaction. In contrast, Reliability, Assurance, and Empathy were found to have a significant positive influence on customer satisfaction. These findings indicate that customers place greater importance on service accuracy, employee competence, trustworthiness, and personal attention. Therefore, service providers are encouraged to prioritize improvements in Reliability, Assurance, and Empathy to enhance customer satisfaction and sustain long-term customer relationships.

This study investigates the role of Artificial Intelligence (AI) tools, specifically ChatGPT and Jenni AI, in supporting academic integrity through accurate citation generation. Employing a descriptive qualitative method, the research involved 30 undergraduate students who evaluated AI-generated citations using Fishman’s (2014) Academic Integrity Theory and Smith’s (2020) Citation Accuracy Framework. Data were collected through questionnaires assessing students’ perceptions of reliability, ethical responsibility, and accuracy in AI-assisted citation practices. Quantitative analysis revealed that Honesty and Accountability were the most dominant values (22.58% each), followed by Fairness and Respect (19.35% each), Trust (12.90%), and Courage (3.23%). Qualitative findings showed that students recognized AI’s potential to enhance writing efficiency but emphasized the need for human verification to ensure factual correctness and ethical compliance. Comparatively, Jenni AI demonstrated greater consistency and citation verification than ChatGPT, which exhibited more frequent fabrication and inaccuracy. The study concludes that while AI tools can enhance academic productivity, maintaining academic integrity still requires critical human oversight, ethical awareness, and adherence to scholarly honesty and accountability.

This study aims to improve digital money literacy among the community of Kineppen Village, Munte District, Karo Regency, through education and the implementation of the QRIS (Quick Response Code Indonesian Standard) payment system. The research utilized a descriptive qualitative approach, incorporating field observations, interviews, and direct mentoring with four local businesses: Ayam Penyet Pak Lek, Warkop Aim Tigander, Oke Laundry Kineppen, and Pangkas Singarimbun. The findings show that two businesses, Ayam Penyet Pak Lek and Pangkas Singarimbun, successfully adopted QRIS, leading to smoother transactions and increased customer trust. However, the other two businesses, Warkop Aim Tigander and Oke Laundry Kineppen, still face challenges in adopting the system due to limited internet access and deep-rooted traditional cash payment habits. Despite these barriers, the program significantly enhanced the digital literacy of local entrepreneurs, raising their awareness and readiness to participate in the village’s digital economy. This study emphasizes the importance of continuous support and access to technology in fostering the broader adoption of digital payment systems, particularly in rural areas where technological access may still be limited

This study examines how Perplexity AI is integrated into academic research, particularly its role in research gap analysis and proposal development among university students. Using a qualitative descriptive method and questionnaire data from 32 participants, the research explores students’ perceptions, benefits, and ethical considerations regarding AI- assisted research. The findings reveal that Perplexity AI improves efficiency in literature review and research gap identification, with 75% of students using it to explore research topics and 65.6% acknowledging its usefulness in recognizing trends and gaps. However, concerns remain about accuracy and source reliability, as only 56.3% fully trust AI-generated results, and many still verify information manually. The study concludes that effective use of Perplexity AI requires strong AI literacy that includes critical thinking, verification skills, and ethical awareness. These insights contribute to a broader understanding of human–AI collaboration in academic settings and highlight the need for responsible, well-guided integration of AI tools in research education.

Economic empowerment of rural communities through the strengthening of Micro, Small, and Medium Enterprises (MSMEs) is a crucial pillar in achieving national economic independence. One of the fundamental obstacles faced by MSMEs in rural areas is financial exclusion due to low digital literacy and dependence on conventional cash transaction systems. The Community Service Program (KKN) of students from the State Islamic University of North Sumatra (UIN SU) in Pematang Tengah Village was designed to bridge this gap by optimizing the Indonesian Standard Quick Response Code (QRIS). Through an intensive participatory mentoring approach, students acted as agents of digital transformation who educated, trained, and facilitated 10 local MSME actors in adopting non-cash payment technology. The results of the program show a significant shift from digital skepticism to digital trust. The implementation of QRIS has been proven to increase operational efficiency, financial management accuracy, and strengthen the image of business modernity in the eyes of consumers. This article emphasizes that the role of students is not merely as information deliverers, but as catalysts of social capital that is crucial for the sustainability of digitalization at the village level.

Micro, Small, and Medium Enterprises (MSMEs) are a fundamental pillar of the Indonesian economy, but their potential is often hampered by the digital divide, especially in rural areas. The Quick Response Code Indonesian Standard (QRIS) initiative is a way for the government to encourage digital transformation and make payments more accessible to everyone. This article aims to document and analyse the process and impact of a community service programme that facilitated the adoption of QRIS among 10 MSMEs in Pematang Tengah Village, Tanjung Pura Sub-district. This activity used the Community-Based Participatory Action Research (CBPAR) method, which emphasises active collaboration between the service team and MSME partners. The process included participatory planning, collaborative action in the form of intensive training and mentoring, and joint evaluation. The results showed that all 10 MSME partners successfully adopted and used QRIS for daily transactions. The significant benefits included increased transaction efficiency, improved financial record-keeping, and a more modern business image. The main challenges identified were initial doubts about the technology and unstable internet connectivity, which were successfully mitigated through personalised mentoring based on trust. It was concluded that the CBPAR (Community-Based Participatory Action Research) method is a highly effective framework for implementing technological innovation in rural MSME communities because it not only addresses technical skill gaps but also builds crucial social capital such as trust and digital confidence.

The healthcare sector is increasingly confronted with a VUCA environment (Volatility, Uncertainty, Complexity, and Ambiguity), requiring hospitals to adopt adaptive, resilient, and innovative strategies. This study aims to systematically review the evidence on smart hospital strategies in responding to uncertainty, particularly in improving service quality, operational efficiency, and patient satisfaction. A systematic literature review was conducted using major academic databases, including Scopus-indexed sources, Google Scholar, and Semantic Scholar, covering publications from 2020 to 2026. Articles were selected based on predefined inclusion criteria focusing on hospital management strategies in dynamic and uncertain environments. A total of 10–15 relevant studies were included and analyzed using thematic synthesis. The findings indicate that key strategies in addressing VUCA challenges include digital transformation (e.g., electronic medical records and telemedicine), adaptive and transformational leadership, agile management approaches, and patient-centered care. Digital technologies significantly improve efficiency and decision-making processes, while agile and adaptive leadership enhances organizational responsiveness and resilience. However, several studies highlight that technological advancement alone is insufficient without integrating humanistic values such as empathy, communication, and trust. In conclusion, the most effective hospital strategies in a VUCA world are those that integrate technological innovation with human-centered care. Hospitals must develop flexible, data-driven, and patient-oriented systems to ensure sustainability and competitiveness in uncertain environments. Future research should focus on longitudinal and experimental designs to strengthen causal evidence and explore the integration of digital systems with humanistic healthcare values.

Healthcare organizations are increasingly required to preserve the sustainability of their institutional values by ensuring high-quality services, operational efficiency, and rigorous adherence to risk governance frameworks. RSUD dr. Chasbullah Abdulmadjid Bekasi City continues to face considerable challenges in this regard, particularly due to the limited internalization of core organizational values, disparities in the cultivation of an adaptive culture, and inconsistent employee compliance with established risk management procedures. These issues highlight the necessity for a leadership paradigm grounded in service, empathy, and empowerment.This study investigates the extent to which servant leadership influences the creation and protection of corporate values, while examining the mediating roles of strong adaptive culture and employee compliance doing the implementation of risk management. Employing a quantitative explanatory survey design, the research collected responses from 153 hospital employees, and data were analyzed through Structural Equation Modeling (SEM) to evaluate both direct and mediated causal pathways among variables.The findings reveal that servant leadership significantly strengthens creation and protection of corporate values, not only through direct influence but also by enhancing cultural adaptability and reinforcing compliant behavior in risk-related practices. Leaders who embody service-oriented principles are shown to cultivate work environments that foster mutual trust, organizational learning, and value-based decision-making.This study contributes meaningful empirical evidence to the discourse on leadership, organizational culture, and compliance within public hospital settings. Institutional strategies should prioritize continuous leadership development and comprehensive risk governance training to secure long-term performance excellence and reputational resilience.

Significant changes have occurred in the land administration sector with the introduction of digital land certificates as part of an ongoing digital transformation in public services. However, public understanding of the concept, procedures, and benefits of digital certificates is still relatively limited, leading to uncertainty and hesitation in their adoption. This community service program aims to increase public awareness and knowledge about digital land certificates through interactive education and structured socialization activities. The program includes seminars, guided discussions, and question-and-answer sessions designed to provide clear and practical explanations about how digital certificates function within the land registration system. As a result of these activities, community members become more informed about the advantages of digital certificates, such as greater efficiency, enhanced data security, improved transparency, and reduced risks of document damage or loss. This educational initiative is expected to strengthen public trust, encourage active participation, and support the more effective and sustainable implementation of digital land certificate services in the future.