Microplastics (MPs) are an emerging pollutant in agricultural irrigation systems, particularly in densely populated regions with intensive land use. This study investigated the distribution, characteristics, and ecological risks of MPs across seven sampling sites within a rural irrigation network. MPs concentrations ranged from 3.1 to 64.3 particles/L, with the highest levels observed at sites receiving domestic runoff and urban channel inputs. Fibers (44
Purpose This study examines how generative artificial intelligence functions as a governance stressor within higher education institutions and investigates how ethical boundary ambiguity, perceived academic risk and institutional policy clarity shape support for governance reform. Design/methodology/approach A mixed methods design was employed. The quantitative phase involved 228 participants comprising 142 undergraduate students and 86 lecturers. A structured survey measured perceptions across four governance related domains. Multiple regression analysis identified predictors of reform support. The qualitative phase included semi structured interviews to explore implementation level tensions and policy interpretation dynamics. Findings Ethical boundary ambiguity and perceived academic risk significantly predicted support for governance reform. Institutional policy clarity was negatively associated with reform demand, indicating a stabilising effect. Qualitative findings revealed that inconsistent assessment expectations and uneven policy communication translated abstract governance into everyday uncertainty. Results suggest that reform pressure emerges from misalignment between policy articulation and pedagogical practice rather than from misconduct alone. Originality/value The study proposes a governance alignment model that reframes academic integrity governance as a problem of communicative coherence linking policy clarity, ethical boundary definition and perceived academic risk. The findings contribute empirical evidence to institutional level debates on sustainable AI integration in higher education.
IntroductionCoconut agroindustry supports rural livelihoods and economic resilience in Indonesia, yet many producers remain dependent on inefficient marketing systems characterized by intermediary dominance, weak bargaining power, and limited value-added diversification. This study examines how behavioral decision-making influences marketing institution preferences and strategic agroindustry development in Buton Regency, Indonesia.MethodsA field-based mixed-method study involved 489 copra processors, 182 coconut shell charcoal processors, marketing actors, and 10 institutional experts. Economic performance was evaluated through Hayami value-added analysis, farmer’s share, marketing margins, and a price-spread efficiency index. The archived expert-consensus ordering of five marketing-institution criteria was converted into normalized rank-order centroid weights. The retained four-group priority vector was analyzed through a transparent group-level SWOT-AHP synthesis and one-at-a-time sensitivity analysis.ResultsCoconut shell charcoal processing generated an average value added of IDR 1,002.52/kg and a value-added ratio of 54.87%. The shorter marketing channel increased farmer's share from 75.00% to 85.71% and reduced the price-spread index from 25.00% to 14.29%. Selling price (0.4567), demand stability (0.2567), and accessibility (0.1567) were the leading preference criteria. SWOT weights were 0.4658 for strengths, 0.2771 for opportunities, 0.1611 for weaknesses, and 0.0960 for threats. The normalized strategy scores ranked SO first (0.3715), followed by ST (0.2809), WO (0.2191), and WT (0.1286); no rank reversals occurred under ±10% and ±20% weight perturbations.DiscussionCoconut-agroindustry decisions reflect both economic incentives and institutional constraints. Higher-value processing and shorter marketing channels improve economic outcomes, but liquidity certainty, transaction security, accessibility, and institutional familiarity continue to shape producer preferences. The behavioral interpretation is therefore preference-based and conceptual rather than a psychometric validation of bounded rationality or institutional trust.
This study aims to examine the Islamic educational perspective on the Sara Pataanguna philosophy of the Buton community. The discussion focuses on three aspects: the philosophical foundations of Sara Pataanguna, the concepts of Islamic education reflected in its values, and the relevance of Islamic educational concepts to the philosophy. This research employs a library research method through the examination of books, scholarly journals, and other scientific works relevant to the topic. Data were collected from various academic sources and analyzed using philological, theoretical, philosophical, and anthropological approaches. The findings reveal that Sara Pataanguna contains Islamic educational values that correspond to the fundamental dimensions of Islamic education, namely aqidah (faith), ibadah (worship), and akhlaq (morality). The philosophy emphasizes the development of human character through the cultivation of akhlaq al-karimah (noble character), reflecting educational efforts that are consistent with the objectives of Islamic moral education. Furthermore, the humanitarian values embedded in Sara Pataanguna are highly relevant to the goals of Islamic education, as they encourage self-awareness, social responsibility, mutual respect, compassion, and obedience to Allah as the foundation of harmonious human relationships.
This study examines netizen opinion on corruption-related news in Indonesian social media, focusing on how sentiment, issue framing, and engagement patterns shape digital public discourse. The research aims to analyze how users respond to corruption narratives and to identify dominant patterns of opinion expression in online environments. Using a quantitative content analysis approach combined with computational sentiment analysis, the study analyzes 149 social media mentions collected through an automated analytics platform. The methodology integrates sentiment classification, keyword mapping, and engagement metrics to provide a comprehensive understanding of discourse dynamics. The results indicate that negative sentiment dominates the discourse, accounting for more than half of the total mentions, followed by neutral and positive sentiments. Keyword analysis reveals that discussions are primarily framed around legal and economic issues, including prosecution processes, state financial losses, and institutional accountability. Engagement patterns show that emotionally charged content, particularly negative narratives, tends to generate higher levels of interaction across platforms such as Instagram and TikTok. These findings suggest that social media functions as a hybrid public sphere where informational and affective elements interact to shape public opinion. The study highlights the importance of digital platforms in influencing public perceptions of corruption and institutional trust. By combining computational analysis with theoretical insights, this research contributes to a deeper understanding of digital public opinion formation and offers implications for media, policymakers, and scholars interested in corruption communication.
