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Employee performance is a strategic factor in the success of regional banking organizations that are oriented towards service and achieving business targets. However, empirical evidence at PT Bank Sumut Kantor Cabang Koordinator Medan, indicates that employee performance tends to stagnate in the "Good" category during the 2021–2024 period. This condition is thought to be related to career development that is not yet optimally structured, organizational commitment that has not been fully actualized in work behavior, and inadequate extrinsic motivation. This study aims to analyze the effect of career development and organizational commitment on employee performance through extrinsic motivation as a mediating variable. The study used a quantitative approach with a survey method of employees at PT Bank Sumut Kantor Cabang Koordinator Medan. Data were analyzed using Structural Equation Modeling. The results show that career development and organizational commitment influence extrinsic motivation, and extrinsic motivation plays a role in improving employee performance and mediating the relationship between variables. These findings strengthen the role of extrinsic motivation as an important mechanism in bridging human resource policies and employee performance in regional banking.

The Presbyterian-Synodal system of church government is based on the ideal theological foundation of Christocracy, the confession that Christ is the sole Head of the Church who rules directly through His Word and Spirit. Theoretically, this model rejects hierarchy, affirms the parity of all ecclesiastical officers (ministers, elders, deacons) as servants, and views the local church council as a complete church (ecclesia completa). However, in historical and contemporary practice, a fundamental tension exists whereby this system consistently deviates into hierarchical and clerical practices. This deviation manifests as a hierarchy of office (clericalism) and a hierarchy of assemblies (Synod-centrism), where authority shifts from Christ to official figures and Synodal structures that are viewed as the "highest court." This article aims to analyze the fundamental causes of this authority shift. Using a qualitative library research method, the author conducts a systematic-theological, historical-critical, and comparative analysis of the works of Reformers (especially Calvin), historical church order documents, and contemporary case studies (such as in Malawi and GMIM). This study concludes that this authority shift stems from two primary factors: First, a "theological deficiency" in many church order documents, which fail to affirm Christ's rule "through His Word and Spirit," stating instead only His rule "through the ministry of officials," thus effectively equating official authority with Christ's authority. Second, the historical legacy of Scottish "national covenant" ecclesiology, which was historically intentionally designed with a centralized authority structure for "godly officials" to "rule over" a mixed populace. The author recommends that churches in this tradition revise their church orders to explicitly re-assert the supremacy of Christ's rule through His Word and Spirit over any human official or synodical authority.

This research explores the development of a participatory governance model for community based waste management systems, aiming to enhance both legal compliance and public social welfare outcomes. Community based waste management (CBWM) plays a critical role in addressing environmental and health challenges, yet its success is often hindered by weak governance structures, limited community involvement, and insufficient regulatory frameworks. The study introduces a governance model that integrates local community participation into decision making processes, encouraging ownership and responsibility among residents. The primary goal is to improve compliance with environmental regulations while promoting social welfare by fostering better public health and community cohesion. A review of literature highlights key theories of participatory governance, focusing on its ability to enhance legal adherence and increase social equity. Previous studies on CBWM demonstrate the potential of community involvement in overcoming barriers to legal compliance, such as weak enforcement and fragmented governance. However, challenges like inadequate infrastructure, socio economic factors, and cultural habits still impede full participation and compliance. The study utilizes a mixed methods approach, including stakeholder analysis, participatory workshops, and regulatory compliance assessments, to evaluate the effectiveness of the model. The results show that communities involved in participatory governance exhibit higher compliance with waste management laws, improved sanitation, and healthier living conditions. Furthermore, the model fosters social capital and community empowerment, contributing to long term sustainability. In comparison to centralized waste management systems, the participatory approach is found to be more adaptable, accountable, and socially accepted. While the model presents several benefits, challenges such as infrastructure limitations and cultural barriers remain. Future research should further investigate how to address these challenges, particularly through technological integration and cross sector collaborations, to ensure the scalability and sustainability of the participatory governance model.

This study explores the integration of customary law and government regulations in environmental protection, emphasizing the role of community perceptions in shaping effective legal frameworks. Marginal ecosystems, such as coastal areas, urban fringes, and sacred natural sites, often face vulnerability due to fragmented governance systems that fail to coordinate customary practices with formal legal structures. The research investigates how integrating local traditions and state regulations can enhance biodiversity conservation, improve community engagement, and ensure the long term sustainability of environmental management efforts. Findings reveal that when customary laws are formally recognized and incorporated into state regulations, they significantly enhance the legitimacy and effectiveness of conservation policies. Communities in regions like Bali, Indonesia, and Pacific Islands have shown that hybrid legal approaches, which respect traditional ecological knowledge, result in greater participation and trust in conservation activities. However, challenges such as administrative complexity, lack of standardized guidelines, and the need for adequate funding and support for community based governance hinder the full potential of this integration. The study highlights the importance of simplifying legal processes and fostering mutual understanding between customary practices and formal regulations to achieve successful ecosystem protection. This research emphasizes the need for policy reforms that ensure the inclusion of customary law in environmental governance frameworks, ultimately promoting a more inclusive, adaptive, and sustainable approach to managing marginal ecosystems.

This article examines various guidance and counseling (BK) management models relevant to the context of modern education in Indonesia. The models discussed include POAC (Planning, Organizing, Actuating, Controlling) management, comprehensive BK services, school-based BK management, specialized service management, and the use of digitalization in BK services. This review was compiled using a literature review method, drawing on various credible national sources, such as scientific journals, reference books, and education policy documents. The purpose of this research is to provide an in-depth understanding of the characteristics, principles, and implementation of each BK management model in educational practice. The results indicate that each model has its own advantages and limitations, both in terms of service planning, resource management, and the effectiveness of service delivery to students. Therefore, the selection and implementation of a BK management model must be tailored to the needs of the school, the availability of professional staff, infrastructure, and student characteristics. The integration of a systematic, data-driven, and adaptive management approach to developments in information technology is a key factor in improving the quality and effectiveness of BK services. This article is expected to provide theoretical and practical contributions to school counselors, educators, and education policymakers.  

Generation Z, growing up in the digital era, faces various challenges in social, emotional, and academic adjustment in the school environment. This study aims to determine the effectiveness of individual planning services in improving the adjustment abilities of Generation Z students. A qualitative approach was used with a literature review from the past five years. The results of the study indicate that the use of digital technology to support students' personal development can help them better understand themselves, set goals, and plan adaptive steps. This service also plays a role in providing support and early intervention, which helps counselors shift from a reactive approach to a more proactive one. The findings of this study underscore the importance of changing the role of counselors, from being responsive to being more proactive and preventative, by integrating personal and technological approaches in the mentoring process. Therefore, guidance and counseling teachers are advised to design services that are more structured, participatory, and relevant to the unique characteristics of Generation Z. This will ensure that the services provided are more effective in helping students adjust to the school environment.

This study aims to analyze the application of the franchising system on business performance in the beverage franchise business through a case study of Mitra Minuman Siap Saji. The approach used is qualitative with a case study design, with data collection techniques in the form of in-depth interviews, operational observations, and supporting documentation. The results show that the implementation of standardized Standard Operating Procedures (SOPs), franchisor support in the form of training, raw material supplies, and periodic monitoring contribute significantly to improving business stability, product quality consistency, and customer satisfaction. However, there are limitations in flexibility and several communication obstacles that have the potential to affect the effectiveness of the partnership. The relatively strict contract structure also impacts partners' perceptions of local innovation space, although it is generally still viewed as providing business security and business model clarity. These findings emphasize that a balance between franchisor control and partner autonomy, accompanied by open communication and fair contract design, is a key factor in creating sustainable business performance in a franchising system.

This study aims to map the intellectual structure and research trends in entrepreneurial innovation using bibliometric analysis based on Scopus data. A total of 891 documents published between 1972-2025 were analyzed through Bibliometrix and Biblioshiny, employing techniques such as bibliographic coupling, co-authorship, and thematic mapping. The results reveal four major clusters: (1) innovation theory and entrepreneurial development, (2) business model innovation and digital transformation, (3) regional innovation systems and policy frameworks, and (4) sustainability and green entrepreneurship. Emerging themes include artificial intelligence (AI), generative AI applications, and digital entrepreneurship education, indicating a shift toward multi-level and interdisciplinary integration. Influential documents and authors were identified, highlighting their role in shaping the knowledge base. The findings suggest that entrepreneurial innovation research is evolving toward digitalization, sustainability, and policy-driven ecosystems, offering opportunities for longitudinal and mixed-method studies. This study contributes by providing a comprehensive overview of the field, identifying gaps, and proposing future research directions to strengthen theoretical and practical advancements.

Primary Healthcare Facilities (Fasilitas Kesehatan Tingkat Pertama, FKTP) represent the first level of contact in the healthcare system and play a central role in infection prevention and control. Despite mandatory Infection Prevention and Control (IPC) training in Indonesia, evidence regarding its effectiveness in improving cognitive abilities among primary healthcare workers remains limited. This study aimed to evaluate the effectiveness of IPC training in enhancing the cognitive abilities of healthcare workers in FKTP. A quasi-experimental study with a one-group pretest–posttest design was conducted involving 91 healthcare workers who participated in IPC training across three cohorts in 2024. The training was delivered online through a Learning Management System and consisted of structured learning modules accompanied by a pre-test and a final quiz. Cognitive improvement was assessed using paired samples t-tests, while the magnitude of training impact was evaluated using Cohen’s dz effect size. The results showed statistically significant improvements in cognitive scores across all cohorts (p < 0.001), with mean score increases ranging from 16.10 to 23.35 points. Effect size analysis revealed large to very large effects, with an overall Cohen’s dz of 1.19, indicating substantial and practically meaningful cognitive gains. In conclusion, IPC training was effective in improving cognitive competence among FKTP healthcare workers. These results reinforce the value of well-structured training programs as an essential component of efforts to strengthen infection prevention capacity in primary healthcare settings.

End-to-end autonomous driving has emerged as a promising paradigm in which deep neural networks directly map raw visual inputs to continuous control actions. Despite its effectiveness, this approach suffers from limited transparency, posing significant challenges for deployment in safety-critical driving scenarios. This study addresses the lack of interpretability in vision-based end-to-end autonomous driving systems and aims to analyze model decision-making behavior under critical conditions such as sharp steering maneuvers and abrupt control transitions. To this end, an explainable end-to-end autonomous driving framework is proposed, combining a convolutional neural network trained via imitation learning with gradient-based visual attribution techniques, including Grad-CAM. The model predicts continuous steering, throttle, and braking commands directly from front-facing camera images, while explainability mechanisms are applied to reveal input regions influencing each control decision. Model performance is evaluated using both prediction accuracy and safety-oriented behavioral metrics. Experimental results show that the proposed explainable model achieves lower control prediction errors compared to a baseline end-to-end CNN, reducing steering mean squared error from 0.034 to 0.031, throttle error from 0.021 to 0.019, and brake error from 0.018 to 0.016. Moreover, safety-oriented analysis indicates improved driving stability, with steering variance reduced from 0.087 to 0.072 and abrupt control changes decreased from 14.6 to 10.3 events. Visual explanations consistently highlight road surfaces and lane-related structures during complex maneuvers, indicating reliance on semantically meaningful cues. In conclusion, the results demonstrate that integrating explainability into end-to-end autonomous driving not only preserves predictive performance but also correlates with smoother and more stable driving behavior. This framework contributes to the development of transparent and trustworthy autonomous driving systems suitable for safety-critical applications

Abstract: The rapid diffusion of Generative Artificial Intelligence (AI) has intensified public debate regarding its benefits, risks, and societal implications. This study investigates public sentiment and thematic structures surrounding Generative AI by analyzing Twitter discourse as a representation of large-scale, real-time public perception. The research addresses two main problems: how public sentiment toward Generative AI is distributed and what dominant themes shape this perception. Accordingly, the objective is to map both emotional polarity and thematic narratives embedded in social media conversations. A computational mixed-methods approach was employed using a dataset of 12,470 tweets collected on 17 December 2024. Sentiment classification was conducted using a transformer-based DistilBERT model, while semantic representations were generated with Sentence-BERT. Topic modeling was performed using BERTopic, integrating HDBSCAN clustering and class-based TF-IDF to extract coherent and interpretable topics. Human-in-the-loop validation supported the interpretive robustness of topic labeling. The findings reveal that public sentiment toward Generative AI is predominantly positive (41.8%), particularly in relation to productivity enhancement, education, and creative applications. Neutral sentiment (31.4%) reflects informational discourse, while negative sentiment (26.8%) centers on ethical concerns, privacy risks, misinformation, and AI hallucinations. Seven dominant topics were identified, with clear topic–sentiment alignment showing optimism in utility-driven themes and skepticism in ethics- and risk-related discussions. In conclusion, public perception of Generative AI is dualistic—characterized by strong enthusiasm alongside persistent caution. These results provide empirical insights for AI governance, responsible innovation, and future research on socio-technical impacts of Generative AI. *    

Global environmental challenges require active engagement from all sectors, including education. For Muslim youth, awareness of environmental sustainability aligns with Islamic ethical principles such as stewardship (khalifah), justice (ʿadl), and social welfare (maslahah). This study examines the influence of green economy education within Islamic higher education on students’ eco-literacy, ethical awareness, and sustainable economic behavior. A quantitative approach was employed using a structured questionnaire distributed to students from both Islamic economics and non-economics programs. Data were analyzed with descriptive statistics, independent t-tests, and one-way ANOVA to identify differences in environmental knowledge, attitudes, and behavior. Findings show that students with an Islamic economics background consistently achieve higher scores in knowledge, attitudes, and behavioral engagement related to sustainability compared to non-Islamic economics students. Integrating Islamic ethical values into the curriculum provides a holistic framework for internalizing sustainability principles, encouraging students to translate ethical knowledge into practical action. Pedagogical strategies such as project-based learning, reflective exercises, and experiential programs further enhance engagement and eco-conscious behavior. The study highlights the critical role of Islamic education in fostering a generation of ethically aware and environmentally responsible students. By embedding moral and ecological principles in academic programs, educational institutions can strengthen students’ capacity for sustainable decision-making and support broader goals of responsible economic and environmental stewardship.

The integration of cloud computing and data security systems is vital for the operational success and competitiveness of fintech startups. Cloud computing enables these startups to scale quickly, manage resources efficiently, and reduce infrastructure costs, making it an indispensable tool for businesses in the rapidly evolving fintech sector. However, with the benefits come significant challenges, particularly in data protection and cybersecurity. As fintech services handle sensitive financial data, ensuring robust security measures such as encryption, access controls, and continuous monitoring is crucial to maintaining user trust. Furthermore, regulatory compliance, both local and global, adds complexity to the data protection strategies of fintech companies. This research explores the key factors that drive cloud adoption in fintech, the security challenges associated with cloud environments, and the strategies implemented by startups to address these challenges. Interviews with IT managers from Indonesian fintech startups reveal that while cloud computing offers scalability and cost-effectiveness, issues like compliance with local regulations and the protection of sensitive data remain major concerns. The research suggests that fintech startups should invest in both cloud infrastructure and advanced cybersecurity measures to protect their operations and customer data. Additionally, creating a comprehensive roadmap for regulatory compliance and fostering partnerships with cybersecurity firms will help mitigate risks and ensure long-term success. The findings highlight the importance of integrating cloud computing with effective security strategies to navigate the complex regulatory and security landscape of the fintech industry.

This study aims to conduct a systematic literature review and bibliometric analysis on Transformational Leadership (TL), based on empirical research. Despite extensive studies on TL in recent decades, comprehensive research remains limited. The methodology used is a Systematic Literature Review (SLR) of articles containing “Transformational Leadership” in the title, abstract, or keywords, sourced from the Scopus database, which yielded 1,297 publications from 1977 to 2025. The data were analyzed using VOSviewer software. The findings suggest that TL is an innovative model in vocational education, bridging industrial systems with academic environments for authentic, practice-based learning. However, challenges include limited resources, insufficient instructor training, and inadequate institutional support. Recent innovations, such as advanced ICT, holographic technology for real-time interaction, and digital twins for process optimization, have enhanced the model's effectiveness. The study also discusses the conceptual framework of TL. This research uses the Scopus database, and future studies could broaden its scope by incorporating other databases like Web of Science. Practically, the study’s findings suggest integrating modern pedagogical strategies, including gamification, simulation, and project-based learning, to enhance student engagement and understanding of manufacturing processes. Socially, it encourages educational institutions to invest in infrastructure, strengthen industry partnerships, and provide continuous instructor training. This study highlights the growing global research on TL and calls for deeper exploration of the topic in existing literature.

The purpose of this scientific paper is to design and implement a knowledge-based expert system to assist students in determining their major specializations at Vocational High Schools (SMK) more objectively and accurately. A major problem frequently faced by SMK students is the mismatch in department selection caused by a lack of understanding regarding their own potential and the specific criteria of each competency. To address this issue, the system was developed using the Forward Chaining method as the inference engine. This method operates in a data-driven manner, beginning with the collection of facts such as interests, academic abilities, and psychological aspects, which are then matched against a Knowledge Base consisting of IF-THEN logical rules. Based on system testing results, the inference engine is capable of processing the list of facts to generate a specialization diagnosis for SMK students and provide the most relevant departmental recommendations, such as Computer and Network Engineering (TKJ), Accounting, Office Automation and Governance (OTKP), or Marketing. The research results indicate that the implementation of the Forward Chaining method is effective in accelerating the decision-making process and minimizing placement errors. This expert system is expected to serve as a tool for Guidance and Counseling (BK) teachers in providing appropriate career direction for students based on structured empirical data.

The Planning, Research, and Development Agency (BAPPELITBANG) has an important role in supporting regional development planning and evaluation. One of the main activities of this agency is the coordination of working visits with external agencies or institutions. The process of managing schedules and work visit reports is currently still carried out manually, causing obstacles such as delays in information, duplicate schedules, and lack of integration of report data. This research aims to design a web-based application that is able to manage work visit schedules in a structured manner and facilitate the creation of visit reports digitally. The method used in this study is the Waterfall system development method which includes needs analysis, system design, implementation, and testing. The results of the study show that the application is able to display the visit schedule in real time, minimize schedule conflicts, and speed up the process of preparing work visit reports. Thus, this application makes a significant contribution in increasing the effectiveness and efficiency of the work visit administration process at BAPPELITBANG.

Toddlers are a vulnerable age group to various types of diseases due to their immune systems that are still developing. Limited utilization of medical record data and the lack of structured information regarding disease patterns in toddlers based on age and causative factors have resulted in suboptimal prevention and treatment efforts. Therefore, an approach is needed to systematically classify toddler disease data. This study aims to apply data mining techniques using the clustering method with the K-Means algorithm to group types of diseases in toddlers based on age and causative factors. The variables used in this study include toddler age, type of disease, and causative factors. The data were obtained from RSUD Dr. R. M. Djoelham Binjai and processed using MATLAB software with three clusters. The results show that the K-Means algorithm successfully groups toddler disease data into three clusters with different characteristics. The first cluster is dominated by toddlers aged 0–11 months with appendicitis caused by genetic factors. The second cluster is dominated by toddlers aged 1–3 years with diarrhea caused by environmental factors and has the largest number of members. Meanwhile, the third cluster is dominated by toddlers aged 0–11 months with sore throat caused by environmental factors. The clustering results indicate a relationship between toddler age, disease type, and causative factors, which can be used as supporting information for decision-making in the prevention and treatment of toddler diseases.

The advancement of digitalization and government programs through the Electronic-Based Government System (SPBE) have impacted digital performance systems at various levels of government. The Puloniti village government is also one of the village governments that needs to transform conventional performance into digital performance in response to global challenges. Through this study, the research team aims to assess the capacity of the Puloniti village government to carry out digital work transformation and identify the main obstacles that hinder it. This research was conducted using a qualitative descriptive approach through observation, interviews, and documentation. This study identified two main obstacles for the Puloniti village government in carrying out digital performance transformation: limited human resource literacy and inadequate software facilities and infrastructure.

This study analyzes the role of the Golkar Party of Serang City in the formulation and oversight of Regional Regulation Number 11 of 2019 on the Implementation of Tourism Business Governance using the Institutional Analysis and Development (IAD) framework. The study aims to examine how political party institutions perform their functions in local legislative processes, particularly in terms of public representation, interest articulation, and policy oversight. A qualitative case study approach was employed, involving in-depth interviews with party actors and members of the Regional House of Representatives (DPRD), as well as document analysis of relevant policy materials. The findings reveal that Golkar’s role in the formulation and supervision of the regulation was predominantly carried out by its legislative faction through informal mechanisms, while the party’s organizational structure played a limited institutional role. The process of absorbing public aspirations was relatively constrained and tended to favor groups with close social and political ties, indicating that the party has not fully exercised its functions of public articulation and accountability. From the perspective of the IAD framework, this condition reflects weaknesses in internal rules, actor capacity, and interaction mechanisms within the party as a political institution in the policy arena. Therefore, strengthening Golkar’s institutional capacity is essential to enable a more substantive, responsive, and inclusive role in local legislative and policy oversight processes

The increasingly massive development of social media has been exploited by terrorist groups as a strategic tool to spread propaganda, violent ideology, and radicalism to the wider community, especially the younger generation. This situation demands an effective counter-radicalization strategy that adapts to the dynamics of the digital space. This study aims to analyze the strengthening of legal instruments and the role and institutional structure of the National Counterterrorism Agency (BNPT) in implementing social media-based counter-radicalization policies. The research method used is a normative juridical approach with a legislative approach and a conceptual approach, through a review of laws and regulations, legal doctrine, and policies related to counter-terrorism in Indonesia. The results show that the normative legal basis for BNPT's authority to carry out counter-radicalization is already available, particularly in the Law on the Eradication of Criminal Acts of Terrorism. However, its implementation still faces various obstacles, including weak derivative regulations specifically governing the supervision and counter-measures of digital radicalism, limited inter-agency coordination, and suboptimal evaluation of data- and technology-based policies. Therefore, this study recommends strengthening derivative regulations, increasing the digital capacity of BNPT, and developing a more integrated coordination and evaluation system.