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This study examines clause structures and syntactic relations in argumentative articles published on the 2025 edition of the Badan Bahasa website. As a communication tool, language plays a crucial role in conveying ideas and shaping logical reasoning, particularly in argumentative texts that require a high degree of cohesion and coherence. The research aims to describe the patterns of clause structure and interclausal syntactic relations used in these articles to understand how linguistic constructions influence argumentative strength. Employing a qualitative descriptive approach with the distributional method, the study relies on internal linguistic elements as analytical instruments. The findings show that the articles generally employ single clauses with S–P–Pelengkap patterns as well as complex clauses expressing causation, alongside syntactic relations that include coordination and subordination, including causal, contrastive, purposive, and additive relations. These patterns indicate consistent application of Indonesian syntactic rules, although some repetitive tendencies appear in the use of active clauses and multi-layered complex sentence structures. The study highlights the importance of mastering clause structure in constructing logical, persuasive argumentative texts, and the findings are expected to serve as a reference for writers and language institutions to improve academic writing quality and enrich linguistic studies in digital contexts.

This study examines the export barriers encountered by emerging small and medium-sized enterprises (SMEs) in Indonesia, with a focus on export documentation challenges, tariff constraints, and the adaptive marketing strategies employed to sustain international market engagement. Employing a qualitative case study approach, this research investigates PT Albarka International Group, a nascent export-import company established in 2021 and headquartered in Malang, East Java, which specializes in the export of natural commodities including Bakhur-related materials (opercula shells, damar resin, agarwood), spices, and other Indonesian products to Middle East markets including Yemen, Saudi Arabia, UAE, Libya, Sudan, and Djibouti. Data were collected through in-depth interviews with key company personnel and supplemented by document analysis. Findings reveal three primary export barriers: (1) high shipping tariffs relative to regional competitors, frequently triggering order cancellations by importers; (2) complex and time-intensive export documentation requirements, particularly for regulated natural resource products subject to CITES compliance, fish quarantine certification (Health Certificate), and customs declaration (PEB); and (3) internal organizational constraints stemming from overlapping job roles. In response, PT Albarka has adopted adaptive strategies including Full Container Load (FCL) consolidation to reduce per-unit shipping costs, advance payment systems (TT in advance) to mitigate importer default risk, and collaborative consultation with customs and quarantine authorities. The study contributes to the SME internationalization literature by demonstrating how resource-constrained emerging exporters navigate institutional and logistical complexities in developing economy contexts, offering practical insights for SME practitioners and export policy stakeholders.

This study investigates the implementation of history learning based on Higher Order Thinking Skills (HOTS) in developing students' analytical history skills. This research is motivated by the dominance of conventional teaching focused on lectures that emphasize memorization of facts rather than critical and analytical thinking. The study aims to describe how HOTS-based strategies are implemented in history classes and to analyze their impact on students' analytical skills. This research uses a qualitative descriptive methodology. Data were collected through classroom observations, interviews, and documentation, then analyzed using data reduction, data display, and conclusion drawing techniques. The findings show that before the implementation of HOTS, students' responses were mostly descriptive and limited to recalling factual information. After the implementation of HOTS-based learning through the use of analytical questions, historical case studies, source analysis, and structured group discussions, students showed significant improvement in explaining cause-and-effect relationships, evaluating historical evidence, and building logical arguments. Students became more active in discussions and demonstrated a deeper conceptual understanding than mere memorization. However, several challenges were identified, including students' limited experience in critical thinking, time constraints, and the need for teachers to be better prepared in designing HOTS-oriented learning instruments. Overall, this study concludes that HOTS-based history learning effectively improves students' analytical history skills and shifts the learning orientation from lower-order thinking to higher cognitive engagement. This approach pedagogically contributes to fostering a critical, reflective, and contextual understanding of history that is relevant to the demands of 21st-century education.

This study investigated the logical function of clause complexes in two selected English nursery tales, Jack the Giant Killer and Jack and the Beanstalk, using Halliday’s Systemic Functional Linguistics (SFL) framework. The research focuses on the realization of clause interpendency through the taxis system (parataxis, hypotaxis, and taxis combination) and logico-semantic relations (elaboration, extension, enhancement, idea and locution). The method employed is qualitative content analysis based on Krippendorf involving processes such as unitizing, sampling, coding, reducing, interpreting, and narrating. From 1,048 clauses analyzed, 341 wereidentified as clause complexes. The findings show that enhancement is the most dominant logico-semantic relation (164 cases), followed by extension (123 cases), elaboration (100 cases), locution (57 cases), andidea (22 cases). The findings show that paratxis is the most dominant taxis in selected English nursery tales. While hypotaxis relations mostly realized in enhancement, while extension appeared dominantly in parataxis. These results reveal that although nursery tales are intended for children, they often employ complex grammatical structure, therefore, balancing narrative engagement and linguistic accessibility is crucial to support children’s language development and reading comprehension.

This research investigates transparency and accountability in the management of state-owned assets (BMN) at the East Java Regional Police's Logistics Bureau as a step toward enhancing effective, adaptive, and integrity-focused governance in police logistics. The research context arises from the growing public call for transparency and accountability in managing state assets, in line with policies for bureaucratic reform and digitalization in the police logistics framework. This study utilized a qualitative descriptive approach involving in-depth interviews, observations in the field, and analysis of documents. The results show that adopting a unified digital system has enhanced the efficiency of asset management, sped up inventory operations, and reduced the risks of asset misuse. Nonetheless, obstacles persist, such as restricted human resource capacity, data alignment problems, and inadequate performance-based assessments. The conversation emphasizes that effective asset management relies on the implementation of adaptive governance, motivation for public service, and precise performance assessment systems. The research indicates that the integration of digital innovation, professional skills, and a robust commitment to public accountability is crucial for creating transparent and sustainable governance in police logistics

This study aims to explore students’ perceptions of using Canva as a digital storytelling platform to enhance their visual and written narrative skills in English writing. The research employed a descriptive qualitative method involving 34 students who participated in a questionnaire consisting of eight closed-ended statements and two open-ended questions. The data were analyzed descriptively, using percentages to support qualitative interpretation. The findings revealed that most students perceived Canva as an accessible, enjoyable, and effective tool for developing writing skills. Students agreed that Canva helps them visualize ideas, organize stories logically, and combine words with images creatively. Moreover, Canva was found to improve students’ motivation, confidence, and emotional expression in English writing. These results are consistent with previous studies by Utami and Suriyani (2022), Febriansyah et al. (2023), Siregar et al. (2024), Herwani (2024), Eragamreddy and Joseph (2025), Hafidzin et al. (2025), and Jayanti et al. (2025), which collectively highlight Canva’s role in supporting writing engagement, creativity, and organization. The study concludes that Canva transforms traditional writing into a multimodal and meaningful process, combining linguistic and visual literacy. Therefore, Canva can be considered an innovative pedagogical tool that promotes creative thinking, digital competence, and expressive communication in the English writing classroom.

This study aims to evaluate the performance of digital information systems, including websites and mobile applications, used by national expedition companies in Indonesia, using standardized technical indicators from Google Web.dev. This research employs a descriptive and evaluative approach with purposive sampling. The research objects comprise five major national expedition companies: JNE, J&T Express, SiCepat, Pos Indonesia, and Lion Parcel. The evaluation is conducted using four main indicators: Performance, Accessibility, Best Practices, and Search Engine Optimization (SEO). The results indicate that, in general, the digital information systems of national expedition companies function adequately; however, there are notable performance variations among companies, particularly in terms of loading speed and mobile performance. Pos Indonesia demonstrates the most balanced overall performance, while several other companies require further optimization, especially in performance efficiency and SEO. This study contributes to the literature by providing an objective technical evaluation of expedition information systems and offering practical recommendations to improve digital service quality, enabling faster, more secure, and more responsive logistics services in a highly competitive industry.

This research benchmarks multiple machine learning (ML) algorithms for large-scale loan default prediction using a real-world dataset of 255,000 borrower records, where default cases represent only ~9–12% of total observations. The study addresses the persistent gap in comparative analyses of ML models that balance predictive accuracy, interpretability, and computational efficiency for credit risk assessment. Six algorithmic families were evaluated Logistic Regression, Random Forest, XGBoost, LightGBM, CatBoost, Artificial Neural Networks (ANN), and Stacked Ensemble—using standardized preprocessing, hybrid imbalance handling (SMOTE, class weighting, under-sampling), and comprehensive evaluation metrics (AUC, F1, Recall, Precision, PR-AUC, and Brier Score). Empirical results show Logistic Regression achieved the highest AUC of 0.732, outperforming nonlinear models under the baseline configuration, while LightGBM attained perfect recall (1.0) but low precision (0.116), indicating over-prediction of defaults. Gradient boosting models demonstrated robust calibration (Brier ≈ 0.114–0.116) and the best computational efficiency, with LightGBM showing the fastest training and lowest memory use. CatBoost exhibited strong recall but the slowest computation, and ANN underperformed on tabular data (AUC ≈ 0.56). The Stacked Ensemble delivered balanced results with AUC = 0.664 and improved overall stability. These findings confirm that boosting-based models, particularly LightGBM and CatBoost, offer superior scalability and calibration, whereas Logistic Regression remains a valuable interpretable baseline. The study concludes that effective default prediction requires integrating rebalancing, calibration, and threshold optimization to enhance recall and operational deployment reliability in large-scale credit ecosystems.

This study aims to analyze the transformation of tourist behavior in mountain hiking activities in the Sindoro, Sumbing, and Slamet (3S) area of Central Java within the context of nature-based tourism trends and digital mediation. A descriptive qualitative approach was employed, involving eight purposively selected hikers. Data were collected through semi-structured interviews, participant observation, and analysis of social media posts. The findings reveal a shift in motivation from physical challenge-oriented goals toward self-fulfillment, personal reflection, and psychological balance. Mountain hiking has also become normalized as part of an urban modern lifestyle. Furthermore, social media plays a significant role in shaping aspirations, documentation practices, and the reproduction of tourist behavior, extending the experience of nature beyond physical engagement into digital representation. These findings indicate that contemporary tourist behavior is constructed through the interaction of intrinsic motivation, social needs, and the logic of digital representation in nature-based tourism.

This article explores mathematical logic as a fundamental discipline within mathematics that systematically investigates the principles of valid, coherent, and consistent reasoning. Mathematical logic serves as an essential foundation for developing structured thinking and constructing well-grounded, persuasive arguments supported by clear justification. It primarily focuses on the processes of reasoning, argumentation, and formal proof, enabling individuals to distinguish between valid and invalid conclusions. By establishing precise rules and logical structures, mathematical logic provides a rigorous framework for assessing the strength and consistency of arguments. The discipline emphasizes clarity, objectivity, and analytical accuracy in examining propositions and their relationships. In practice, mathematical logic is presented through the use of symbolic representations, formal logical statements, connectives, quantifiers, and truth tables to analyze patterns of reasoning and verify the truth values of statements. These systematic tools allow complex ideas to be evaluated methodically, prevent logical fallacies, and ensure that conclusions are derived from sound and demonstrable reasoning principles.

The phenomena of cyberbullying and digital intolerance among young people are increasingly alarming in the era of technological disruption, and Christian Religious Education (CRE) is called to provide an adequate pedagogical response to this ethical crisis. This study aims to analyze the relevance of Emmanuel Levinas's ethics of responsibility toward the Other for the formation of students' digital character within CRE, and to formulate a pedagogical framework capable of transforming students' digital behavior from egocentric tendencies toward persons who uphold human dignity. A qualitative method with a library research design was employed, utilizing thematic content analysis of relevant academic sources. The findings indicate that Levinas's concepts of the face (le visage) and asymmetrical responsibility hold profound relevance for CRE, as they directly challenge the egocentric logic underlying destructive behavior in digital spaces. The pedagogical framework of CRE is formulated through three pillars: face-to-face pedagogy, alterity-based digital ethics literacy, and spirituality of responsibility as the foundation of transformation. The implications of this study affirm that CRE holds strategic potential to become a space for cultivating digital moral resilience, grounded in the affirmation of imago Dei and a transformative relational ethics.

This study explores the influence of career factors and economic independence on the phenomenon of late marriage in early adult women (aged 25-35 years) in Indonesia, especially in urban areas of North Sumatra such as Medan. Adopting a mixed-methods design, the study involved a quantitative survey of 250 career female respondents (with age criteria above 25 years old, unmarried, and a minimum income of the city UMR) using the Likert scale to measure career priorities as well as the financial independence index, complemented by logistic regression analysis to test causal relationships. Semi-structural interviews with 20 key informants uncovered an in-depth narrative about the trade-offs between professional ambitions (such as job promotion and income stability) and traditional marriage expectations. Key findings show that women with a bachelor's degree and above and an income of 1.5 times UMR tend to postpone marriage until the average age of 31.4 years, driven by the desire to achieve economic independence (regression coefficient β=0.42, p<0.01) as well as the flexibility of living without partner dependence. However, moderator factors such as Batak or Malay cultural pressures in Medan create internal conflicts, with 68% of respondents reporting social stress from family. Theoretically, the results support role conflict theory in modern family dynamics, while implications include recommendations for work-life balance-based pre-marital counseling programs and corporate policies to support high-quality marriages. This research contributes to the Indonesian family relations literature by highlighting the paradigm shift from patriarchal norms towards gender equality.

The Indonesian hospitality industry is currently facing a post-pandemic "profitability paradox," a phenomenon where increased occupancy rates do not guarantee a proportional increase in net profit margins due to persistent operational cost inflation. This study aims to evaluate operational cost efficiency strategies and their impact on profitability across three star-rated hotels with contrasting locational and market characteristics: @Hom Hotel Kudus (Central Java), Grand Verona Samarinda (East Kalimantan), and FUGO Hotel Banjarmasin (South Kalimantan). This research adopts a descriptive qualitative approach with a comparative multiple-case study design. Data were collected through in-depth interviews with top management, participant observation, and financial document analysis. The results reveal that geographical characteristics and market segments are the primary determinants in selecting efficiency strategies. (1) Hom Hotel Kudus, located in a secondary industrial area, implements Lean Operations strategies through workforce multi-skilling to address market price sensitivity. (2) Grand Verona Samarinda, in the East Kalimantan business hub, focuses on Supply Chain Engineering by localizing raw materials to mitigate high logistical costs. (3) FUGO Hotel Banjarmasin, in the lifestyle segment, adopts Technology-Driven Efficiency to suppress utility costs without degrading the guest experience. The study concludes that sustainable profitability is achieved not through aggressive cost-cutting, but through strategic cost management adaptive to local contexts. These findings provide a new managerial framework for the hospitality industry to shift from a revenue-centric orientation to value optimization.

Advances in information technology have driven the transformation of banking services towards digitalization through mobile banking. Bank Central Asia (BCA), one of the largest private banks in Indonesia, offers m-BCA services to facilitate quick, practical, and efficient customer transactions. However, issues such as delayed notifications, system disruptions, and login problems still exist. This study aims to evaluate m-BCA user satisfaction using the PIECES Framework, which consists of six dimensions: Performance, Information, Economy, Control and Security, Efficiency, and Service. A descriptive quantitative approach was used, with a questionnaire distributed to 105 active m-BCA users in South Jakarta. Data were analyzed using mean values to assess satisfaction levels for each dimension, and validity and reliability tests were conducted. The results showed average scores of 4.02 for Performance, 4.08 for Information, 4.08 for Economy, 4.18 for Control and Security, 4.20 for Efficiency, and 4.09 for Service. The overall score of 4.10 falls into the "Satisfied" category. The highest score was for Efficiency, indicating strong support for users’ banking activities, while the Performance dimension scored lower, suggesting room for improvement. Overall, users are satisfied with m-BCA, but system performance improvements are needed for service stability and sustained satisfaction.

Occupational Health and Safety (OHS) is an important element in creating a safe, healthy, and sustainable work environment. PT. X as a logistics and port operations company has potential occupational hazards originating from physical, chemical, and biological factors that need to be managed optimally. This study aims to evaluate the implementation of OHS at PT. X based on the results of measurements of physical, chemical, and biological factors of the work environment and their compliance with the provisions of the Minister of Manpower Regulation No. 5 of 2018. This study uses a descriptive method with an evaluative approach to work environment monitoring data in 2025 in the generator and office areas. The parameters analyzed include noise, lighting, hot work climate (ISBB), inhalable and respirable dust exposure, and microbiological air quality in the form of total bacteria and fungi. The results show that most parameters meet the specified standards, with the exception of the generator area which exceeds the noise limit and the hot work climate which exceeds the Action Level (AL). The implementation of OHS at PT. X has been running quite well, indicated by most of the work environment parameters that meet the standards. However, strengthening risk controls, particularly regarding noise and hot working conditions in operational areas, is still necessary. This evaluation is expected to serve as a basis for continuous improvement in the implementation of Occupational Health and Safety (OHS) to protect workers from potential occupational hazards and support the productivity and sustainability of company operations.

This study comprehensively analyzes the impact of sectarian conflict on mental health in Kirkuk through an ethnoreligious meta-analysis of 42 studies with a total of N=15,427 participants published between 2003 and 2023. The quantitative synthesis indicates a PTSD prevalence of 47.3% (95% CI: 44.2–50.4) among victims of sectarian conflict, with an uneven distribution across groups, where the Turkmen minority records the highest prevalence at 56.8%, exceeding Arab Sunni at 43.2% and Kurdish at 41.5%. Logistic regression analysis demonstrates that direct exposure to sectarian violence increases the risk of major depression by 3.4 times (OR=3.42, p<.001), anxiety by 2.8 times (OR=2.83, p<.001), and psychosomatic disorders by 2.5 times (OR=2.54, p<.001). Further meta-regression identifies duration of conflict exposure (β=.426, p<.001) and intensity of sectarian violence (β=.389, p<.001) as significant predictors of symptom severity. In contrast to the findings of Cummings et al. (2013) and Eltally (2019), which emphasize the general impact of conflict, this study reveals specific intergenerational trauma patterns within distinct ethnoreligious communities, with the highest transmission observed among families of sectarian massacre victims (d=0.82), while simultaneously highlighting variations in communal resilience across groups as a differential determinant of post-conflict psychosocial dynamics.

Hospital nutrition services are an integral component of improving the quality of patient health. This descriptive observational study aims to evaluate the achievement of Minimum Service Standards (MSS) for nutrition at RSUD Dr. H. Slamet Martodirdjo Pamekasan, specifically focusing on the accuracy of diet types, timeliness of food distribution, and patient food waste. Data were collected over a single menu cycle (10 days) from November 24 to December 4, 2025, involving 44 patients per day. Research instruments included observation sheets and the Comstock visual method, with data analyzed based on the Decree of the Minister of Health (Kepmenkes) No. 129 of 2008. The results indicated that the timeliness of food distribution reached 96% and the accuracy of diet types reached 100%, both of which met the MSS requirements (≥ 90% and 100%, respectively). However, the average patient food waste was 25%, which does not yet meet the maximum standard of ≤ 20%. In conclusion, while logistical aspects have fulfilled the established standards, the hospital needs to conduct further evaluations regarding food flavor factors and patients' clinical conditions to reduce food waste in accordance with the applicable standards.

The concept of science according to Ibn Rushd emphasizes the harmony between religion and philosophy, as well as the importance of using rational thinking methods to achieve the truth. He divides human intellectual abilities into three levels, namely rhetoric, dialectical, and demonstrative, and distinguishes science into theoretical and practical sciences. According to Ibn Rushd, knowledge is obtained through cooperation between the senses, imagination, and intellect, so that the human thought process must run systematically and logically. This research uses the library research method to examine the relevance of Ibn Rushd's thought to Islamic boarding school education in the modern era. The results of the study show that Ibn Rushd's ideas can be the basis for integration between religious science and science, encourage the strengthening of students' critical reasoning, and avoid scientific dichotomy. In addition, the application of his thinking has the potential to improve the quality of learning for Islamic boarding schools to be more contextual, inclusive, and adaptive to the development of science and technology. Thus, the concept of Ibn Rushd's knowledge can strengthen the direction of pesantren education towards a holistic and civilization-oriented education system.

This study presents ReflectAI, a web-based system designed to automate the creation of teaching materials tailored to students' learning styles using behavior data from a Learning Management System (LMS). Student digital activity data—such as logins, material access, forum participation, assignment submission, and quiz results—are extracted and processed using a Hierarchical Clustering algorithm to categorize students into three learning styles: visual, auditory, and kinesthetic. Based on the clustering results, the system automatically generates personalized learning modules using generative AI (ChatGPT API), aligned with each student's learning preferences. Employing a data-driven system development approach, the system was tested with data from 230 students in a mathematics course. The results show diverse learning style distributions and relevant, tailored content generation. ReflectAI is designed to reduce teachers’ administrative workload and enhance personalized and adaptive learning. This system contributes to educational transformation through deep, data-driven technology integration.

Software Defined Network is a popular computer network concept today because of the ease of managing network traffic with the control plane. Massive internet usage makes web server services on SDN networks overloaded. There are many load balancing concepts to overcome this problem, one of which is implementing the K-NN algorithm. This study aims to maximize the performance of the K-NN algorithm on SDN networks by optimizing the K value using Grid Search Cross Validation, and adding server status selection logic based on the smallest disk if the server status calculated by K-NN has the same. All implementations of the load balancing concept in this study were created virtually using Open vSwitch and virtualbox. Testing was carried out using CPU, MEMORY, and DISK parameters sent by the server with the help of the psutils component. JMeter software was used for testing by sending data using the POST method. The data type is text/plain with a data size of 1MB, testing was carried out in stages with threads 100, 200, 300, 400. The test results showed that the performance of the K-NN algorithm was running optimally. There was no significant difference in the distribution of the load to the server, this made the optimization and addition of logic successful.