State University of Jakarta

Women's political visibility does not by itself explain how women are represented as credible political authorities or which gendered expectations accompany that representation. This study examines affirmative discourse of Sherly Tjoanda in two Indonesian-language texts: a Fimela.com inspirational feature published on 16 April 2026 and an institutional-government article published by the Government of North Maluku Province on 9 June 2026. Feminist linguistics provides the primary linguistic orientation, Feminist Critical Discourse Analysis (FCDA) the critical framework, and selected Systemic Functional Linguistics (SFL) concepts the analytical toolkit. Fairclough's account of discourse as social practice guides contextual interpretation; van Dijk is used more narrowly to consider ideological social representations where the textual evidence warrants it. Close analysis of nomination, predication, agency, evaluation, role association, intertextuality, nominalization, and institutional self-presentation identifies four patterns: empowered womanhood through agency and self-development; competence represented through personal achievement and institutional action; the negotiated compatibility of motherhood, relationality, and leadership; and empowerment articulated through skills, employability, integrity, and public responsibility. The Fimela article also lists government programmes and service achievements, which are analyzed as source-reported claims rather than independently verified outcomes. The comparison suggests that positive representation can make female authority intelligible within a text while attaching it to cultural, moral, economic, and institutional expectations. Two texts cannot establish a stable public discourse, audience reception, policy effectiveness, or achieved political legitimacy. The proposed Feminist Linguistic Legitimation Model (FLLM) is therefore a preliminary analytical heuristic, not a causal or generalizable model.

The transition from linear production systems to a circular economy requires a systemic understanding of the drivers that enable sustainable resource management and closed-loop production. However, existing studies often examine these drivers individually, providing limited insight into their structural relationships within complex socio-economic systems. This study aims to identify and analyze the hierarchical relationships among key drivers of circular economy implementation using a Fuzzy Interpretive Structural Modeling (Fuzzy-ISM) approach integrated with MICMAC analysis. Data were collected through a Delphi process involving ten experts in sustainability, circular economy, and environmental management. The analysis identified ten critical drivers, including government regulation, financial incentives, technological innovation, recycling infrastructure, circular business models, stakeholder collaboration, environmental awareness, supply chain integration, institutional support, and digital technology adoption. The results reveal that financial incentives, supply chain integration, and digital technology adoption function as foundational drivers with high driving power and relatively low dependence, indicating their role as key enablers of circular economy transformation. Meanwhile, variables such as government regulation, technological innovation, recycling infrastructure, circular business models, stakeholder collaboration, environmental awareness, and institutional support exhibit high levels of interdependence, forming a network of linkage variables that shape the operational dynamics of circular systems. These findings highlight that circular economy transitions are driven by interconnected institutional, technological, economic, and social factors rather than by isolated policy or technological interventions. The study contributes to sustainability research by providing a systemic framework for understanding circular economy drivers and offers strategic insights for policymakers and industry practitioners seeking to accelerate circular economy adoption.

This study investigates the effects of Circular Economy-Based Eco-Tourism (CEBE) and Environmental Literacy on marine conservation and marine ecosystem resilience, mediated by Plastic Pollution Reduction (PPR) and Ecosystem Restoration (ER, in coastal communities of Banten, Indonesia. The study is motivated by the persistent gap between eco-tourism initiatives and measurable ecological outcomes, particularly the limited integration of circular economy practices and environmental literacy in addressing plastic pollution and ecosystem restoration simultaneously. Using survey data from 341 respondents and Partial Least Squares Structural Equation Modeling (PLS-SEM), the results indicate that both CEBE and EL positively influence PPR and ER, which in turn contribute to marine conservation. Marine conservation is strongly associated with enhanced marine ecosystem resilience, highlighting the interconnectedness of ecological, social, and economic dimensions. Mediation analysis revealed that some indirect pathways were not significant: PPR did not mediate the effects of CEBE or EL on marine conservation, and ER did not mediate the effect of EL. These findings suggest that individual behaviors alone may not guarantee ecosystem-level improvements without supportive policies, sustained community engagement, and institutional mechanisms. Effect sizes show that EL has a large influence on PPR, while CEBE and ER exhibit moderate effects. High R² values indicate substantial explanatory power but may reflect limitations inherent in self-reported, cross-sectional data. This study offers three main contributions: (1) a theoretical contribution by integrating CEBE with environmental literacy within a socio-ecological resilience framework; (2) a methodological contribution by modeling plastic pollution reduction and ecosystem restoration as parallel mediators using PLS-SEM; and (3) a practical contribution by identifying multi-level interventions linking community behavior, conservation practices, and ecosystem resilience. Limitations include potential self-report bias, context specificity, and cross-sectional design, which constrain causal interpretation. Future studies employing longitudinal or experimental designs are recommended to validate and extend these findings.

This study aims to explore the impact of Problem-Based Learning (PBL) on critical thinking skills, student engagement, and educational sustainability, with a particular focus on the role of technological innovations in Indonesian education. The research utilizes a quantitative approach, with data collected through a survey distributed to 500 students in DKI Jakarta and Banten Province. A total of 403 complete questionnaires were used for analysis. The study employed quantitative approach to analyze the relationships between latent variables using Structural Equation Modeling (SEM). Key findings indicate that PBL positively influences student engagement, critical thinking, and educational sustainability. Furthermore, technological innovations were found to significantly enhance critical thinking and support educational sustainability. However, the mediating role of student engagement in the relationship between PBL and critical thinking was also confirmed, while no significant moderating effects of technological innovations on educational outcomes were found. This research contributes to the understanding of how PBL and technology integration can foster critical thinking and sustainability in education, particularly in the context of Indonesia. The findings have implications for educational policymakers and practitioners seeking to implement more effective teaching strategies to improve student outcomes and educational quality.

In resource-efficient near-term quantum computers, development on the variational quantum eigensolver (VQE) algorithm that improves the accuracy of electronic structure calculations while maintaining lowrequirement quantum gate counts is indispensable. We integrate Slater-type orbitals within the VQE framework, where the ground-state energy minimization with respect to the Slater exponents is shown as a second-order dependence on these parameters, enhancing accuracy compared with the standard methods while maintaining the same number of qubits. Using the full configuration interaction energy as the cost function, optimized parameters for first- and second-row elements are reported and related to the shielding constant, indicating a need to revise the previously established Slater rules. The active space is improved by substantially contracting the orbital exponents of extended basis sets relative to minimal ones, hence capturing additional electron-correlation effects. By considering the geometric structure of the parameter space, quantum Slater-exponent optimization (Q-SEO) demonstrates accelerated convergence to the target ground state, characterized by distinct parameter trajectories. The integration of a decision tree with Q-SEO effectively mitigates error in noisy environments.