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This article develops a conceptual model that explains how social capital and digital literacy interact in shaping Islamic financial literacy in the digital era. Through a comprehensive literature review, this study synthesizes theories, empirical findings, and thematic patterns derived from reputable academic journals, scholarly books, and institutional publications. The analysis shows that social capital functions as a value foundation encompassing trust, collective norms, and behavioral orientations that influence individuals’ initial acceptance of sharia-based financial practices. Information obtained through family, religious communities, and social networks becomes a crucial entry point that shapes early perceptions and preferences toward Islamic financial products. Meanwhile, digital literacy strengthens individuals’ ability to access, evaluate, and verify Islamic financial information independently through various digital content such as online articles, infographics, educational videos, and Islamic fintech platforms. The interaction between these two dimensions creates a layered learning process in which social capital provides contextual value and trust, while digital literacy deepens technical understanding in a more objective manner. This article contributes theoretically by proposing the Social Capital–Digital Literacy Integrative Model and offers practical implications for Islamic financial institutions, regulators, and fintech providers in designing more effective strategies to enhance Islamic financial literacy in society.

The transformation of the post-pandemic education system has crystallized online learning as a permanent component, with parents assuming an unprecedented instructional role at the elementary level, particularly at Madrasah Ibtidaiyah (MI). This qualitative case study aims to analyze in depth the dynamics and implications of the role of these parents during the transition period. Data was collected through in-depth interviews with parents, students, and teachers from two MIs in Blora, enriched by observation and analysis of communication documents. The findings of the study reveal three crucial things: first, there is a transformation of the role of parents into "substitute teachers" which creates a significant psychological burden due to the gap between the demands of the role and pedagogical capacity. Second, the communication pattern between schools and parents is still one-way and administrative, and has not built a collaborative three-way partnership by involving students. Third, the quality of parental assistance is very diverse and highly dependent on their digital literacy capacity and educational background, which directly affects the development of students' self-regulated learning. This study concludes that the effectiveness of parental roles is determined by psycho-educational support, the quality of communication channels, and the level of personal capacity, so policy implications must move towards a differentiated and empowerment-oriented approach.

Iwan Fals’ song "Bento" offers social criticism, which is analyzed using Teun A. Van Dijk's critical discourse analysis model. Released in 1989, the song critiques the social conditions and behaviors of the wealthy elite during the New Order era, highlighting issues of arrogance, corruption, and social inequality. This qualitative descriptive study applies the Analisis Wacana Kritis (AWK) method, analyzing the lyrics of "Bento" through three dimensions: text, social cognition, and social context. In the text dimension, the analysis reveals the main theme as a depiction of the fictional character "Bento," portrayed as an arrogant and corrupt figure. The text structure employs a narrative persona pattern, with semantic elements describing the luxury of New Order rulers and the exploitation of the common people. The stylistic devices, including anthropomorphism and rhetoric, emphasize the selfish enjoyment of the elite. In the social context, the song is a response to the corruption, collusion, and nepotism (KKN) that characterized the New Order regime. Through satire, "Bento" critiques the dominance of the elite and their disregard for the common people. Overall, the song exposes the power dynamics and corruption under the New Order regime.

This study aims to describe the forms and social functions of code-switching and code-mixing in the film Hujan Bulan Juni and to explain how language choice represents identity and social differences among the characters. The film was chosen because it portrays interactions between characters from different cultural backgrounds Javanese and Manadonese which allows for complex patterns of language contact. The study employed a descriptive qualitative method using observation and note-taking techniques on dialogues containing Indonesian, Javanese, and Manadonese linguistic elements. The data were analyzed using the sociolinguistic frameworks of Gumperz (1982) and Wardhaugh (2015) to uncover the social functions and identity meanings reflected in the speakers’ language choices.The findings reveal that code-switching from Indonesian to Manadonese serves to reinforce ethnic solidarity, emotional closeness, and cultural pride, while switching from Indonesian to Javanese reflects politeness, intimacy, and social hierarchy. Meanwhile, code-mixing between Indonesian and Manadonese marks distinctive speech styles and expresses regional identity, whereas code-mixing between Indonesian and Javanese functions to soften utterances and portray the speakers’ courteous demeanor. Overall, language choice in Hujan Bulan Juni is not merely a communicative tool but also a representation of identity and social differentiation within Indonesia’s multilingual society.

Customer satisfaction has become a major focus in the development of modern services as the role of the service sector in the regional economy increases, including in the city of Balikpapan. However, the literature discussing customer satisfaction models shows conceptual and methodological fragmentation, requiring a systematic synthesis to identify theoretical patterns and current research developments. This study aims to map customer satisfaction models in the service industry through a Systematic Literature Review (SLR) approach using the PRISMA guidelines. A total of 20 articles selected from the last five years were analyzed to identify dominant constructs, methodological approaches, and relevant research trends. The review results show that customer satisfaction models have evolved from traditional service quality-based approaches to models that integrate customer experience, perceived value, trust, and digital dimensions such as personalization and AI-based services. The findings also emphasize the importance of local context, especially in the service sector in Balikpapan, where cultural factors, customer behavior, and the dynamics of city growth influence the structure of satisfaction models. Overall, this study provides a synthesis framework that can be used as a theoretical and practical foundation for designing service quality improvement strategies and developing a further research agenda in the service sector.

Agrarian conflicts in Lampung illustrate that land disputes are not only about ownership but also about how language shapes public perceptions of power and justice. This study aims to explain the changing patterns of media reporting on agrarian conflicts and the social meanings emerging from these changes. The research uses a descriptive qualitative approach with Fairclough’s critical discourse analysis and Lederach’s conflict transformation theory. Data were obtained from online news reports on agrarian conflicts in Lampung published between 2010 and 2025. The results show that earlier reports emphasized control and security, while later coverage shifted toward issues of justice, land rights, and community recognition. This change indicates that language in media reporting plays a crucial role in transforming public perspectives from a logic of authority toward a consciousness of justice and humanity. The study highlights the importance of fair and empathetic public communication as a foundation for peaceful and sustainable conflict resolution.

Measurement is a fundamental domain of mathematics that connects formal mathematical concepts with everyday experiences. Despite its practical relevance, students often experience persistent difficulties in understanding measurement conceptually, tending to approach it as a procedural activity rather than as a process of reasoning about quantities, units, and comparisons. These challenges indicate that learning measurement is influenced not only by individual cognitive factors but also by the social dynamics that shape classroom learning environments. This study aims to examine classroom social dynamics in learning measurement by providing empirical evidence from contextual learning situations. This study employed a qualitative research approach to explore how social interaction, scaffolding, and participation mediate students’ understanding of measurement in contextual learning environments. Data were collected through classroom observations, video recordings of learning activities, analysis of students’ written work, and interviews with selected students and the teacher. Contextual measurement tasks were designed to encourage collaboration, dialogue, and justification, enabling the examination of student–student and teacher–student interactions as they naturally occurred in the classroom. Data analysis was conducted iteratively to identify patterns of interaction, forms of scaffolding, and students’ learning progression within the Zone of Proximal Development. The findings reveal that students initially engaged with measurement tasks in a predominantly procedural manner, with limited conceptual understanding and minimal peer interaction. After the implementation of contextual learning situations, classroom social dynamics changed substantially. Students became more actively involved in discussion, collaborative problem-solving, and collective meaning-making. Peer interaction supported the articulation and refinement of students’ reasoning, while teacher scaffolding guided learning by extending students’ thinking without providing direct solutions. These social processes facilitated students’ movement from their actual level of understanding toward higher levels of conceptual competence within the Zone of Proximal Development. The study further shows that contextual learning tasks alone are insufficient to promote meaningful understanding unless they are supported by productive social interaction and adaptive scaffolding. Conceptual understanding of measurement emerged through socially mediated processes rather than through task completion alone. This study contributes to mathematics education research by emphasizing the central role of classroom social dynamics in contextual learning and by offering insights into how interaction and scaffolding can be orchestrated to support students’ conceptual understanding of measurement.

The dynamic changes in weather patterns in Jambi City require an accurate temperature prediction system, thus this study aims to compare the performance of Random Forest and Support Vector Regression (SVR) algorithms in predicting daily maximum temperatures using weather data from 2020–2024 obtained from OpenMeteo with the application of Feature Engineering including lag and rolling window features. The test results indicate that the SVR model with a Radial Basis Function (RBF) kernel optimized using Grid Search (C=10, epsilon=0.2, gamma=0.01) significantly outperforms Random Forest based on a statistical Paired T-test (p-value < 0.05), yielding an R-squared (R²) value of 87.46%, Mean Absolute Error (MAE) of 0.3818 °C, and Root Mean Squared Error (RMSE) of 0.4964 °C compared to Random Forest's R² of 84.05%, where the previous day's temperature (lag) and three-day rolling average were identified as the most dominant predictors, leading to the recommendation of SVR as the more effective method for temperature prediction in the study area.

The interval between 2018 and 2025 represents a defining epoch in financial assurance, characterized by a systemic collision between traditional audit methodologies and the exponential sophistication of fraudulent actors. This research employs a comprehensive library research methodology, utilizing Systematic Literature Review (SLR) to evaluate the evolving landscape of audit and fraud. The study traces the theoretical migration from Cressey’s Fraud Triangle to multidimensional frameworks like the Fraud Pentagon, which emphasizes the roles of arrogance and competence. Through a forensic examination of catastrophic audit failures including Wirecard, FTX, and the emerging risks of crypto-assets, the research identifies recurring patterns of auditor failure in assessing operational risks and internal controls. Furthermore, the report analyzes the dual-edged impact of Artificial Intelligence (AI); while machine learning algorithms offer enhanced detection capabilities, the rise of Generative AI (GenAI) and deepfake technology has empowered perpetrators to execute sophisticated "synthetic reality" frauds. The study critically evaluates regulatory responses, particularly the revision of International Standard on Auditing (ISA) 240, which mandates a more proactive "fraud lens." The findings suggest that the auditing profession faces an existential crisis of relevance, necessitating a fundamental shift toward a forensic mindset supported by advanced technological integration.

This study aims to classify customer payment methods at 17 Coffee & Eatery using machine learning algorithms, namely Naïve Bayes and Support Vector Machine (SVM). The increasing use of digital and non-cash payments has generated large volumes of transaction data that are rarely analyzed optimally, even though such data contain valuable information for business decision making. This research used secondary transaction data collected from January to March 2025, consisting of 10,147 transaction records. The dataset included several attributes such as order time, payment time, transaction type, total sales, number of items, and payment method. Data preprocessing was performed through data cleaning, feature engineering, normalization, and label encoding before being divided into training and testing sets with an 80:20 ratio. The Naïve Bayes and SVM models were then trained and evaluated using accuracy, precision, recall, F1-score, and ROC–AUC metrics. The results show that both algorithms were able to classify payment methods effectively, but SVM achieved higher accuracy and more stable performance than Naïve Bayes. These findings indicate that SVM is more suitable for handling complex and heterogeneous transaction patterns. The implementation of machine learning for transaction classification can support more efficient financial management and data-driven decision making for small and medium enterprises in the culinary sector.

Climate risk finance has emerged as an increasingly important field of research along with the growing urgency to address climate change and its impacts on the global financial system. Climate change poses real risks to the stability of the international economy and financial systems. Climate risk finance represents an approach that encompasses various financial instruments in supporting climate change mitigation and adaptation. Although the term climate risk finance has not been widely used explicitly as a single keyword, the concept that integrates climate risk and financing is reflected in related keywords such as climate risk, climate finance, and climate change. This study employs a bibliometric analysis method using the Scopus database, supported by analytical tools such as VOSviewer and R Studio, to explore the development of research on climate risk finance. The study identifies publication patterns, international collaborations, and emerging themes within the related literature. The findings show that the publication rate on climate risk finance is relatively moderate each year, but has experienced growth in the last decade. The evolving understanding in this field is expected to strengthen the resilience of financial systems and support sustainable strategies to address long-term climate risks.

Rapid adoption of cashless payments has reshaped everyday spending, especially among young consumers. While e-wallets deliver speed and convenience, constant exposure to discounts, cashbacks, and one-click checkouts may also foster more frequent discretionary purchases. This study examines the relationship between e-wallet usage intensity and consumptive lifestyle, focusing on how convenience and promotional stimuli relate to spending tendencies. Using a cross-sectional online survey of students and early-career workers, we collected self-reports on payment habits and consumption patterns with validated Likert-type instruments. Data were screened and analyzed with correlation and linear regression after basic assumption checks. The results indicate a positive and statistically meaningful association between e-wallet usage and consumptive lifestyle; respondents who transact more often via e-wallets tend to report stronger preferences for instant gratification, hedonic purchases, and impulse buying. Convenience features (e.g., stored cards, fast checkout) and promotional exposure (e.g., limited-time deals) emerged as salient correlates of the relationship. The findings add contextual evidence from Indonesia’s digital economy and suggest practical implications for users, platforms, and educators. Financial-wellbeing interventions such as digital budgeting tips, in-app nudges, spend limits, or post-purchase reflections may help align seamless payments with healthier consumption decisions. Future work can test causal mechanisms and evaluate design features that encourage prudent, goal-consistent spending without diminishing user experience.

Digital entrepreneurship has become a transformative phenomenon in the modern economy, changing the way businesses are developed and run through digital technology. Although the literature on digital entrepreneurship is growing rapidly, comprehensive mapping of the evolution of knowledge and research patterns is still limited. This study analysis the development of digital entrepreneurship in academic literature through bibliometric analysis of the Scopus database to identify research trends, knowledge structures, and future directions. The analysis was conducted on 1,815 publications from 681 sources (1988-2025) written by 8,023 researchers, using R Studio (bibliometrix) and VOSviewer. The results show exponential growth with an annual growth rate of 17.22%, as well as five main theme clusters: digital business models, digital innovation, social entrepreneurship, e-commerce, and fintech. Thematic evolution shifted from traditional entrepreneurship (1988–2010) to digital transformation (2011-2018) to new technology integration (2019-2025). The level of international collaboration reached 26.39%, with the United States, China, and the United Kingdom as the main contributors. These findings provide a research roadmap for identifying research gaps, collaboration opportunities, and trending topics in digital entrepreneurship.

Historically, water resource management in Indonesia has faced significant complexities, often dominated by commercialization and investment-oriented policies that threaten the fundamental rights of farmers. The Constitutional Court’s decision to annul the previous Water Resources Law marks a crucial turning point, demanding a comprehensive policy reformulation. This entails a shift from a market-based paradigm to one grounded in human rights and social welfare, reaffirming state sovereignty over water for the prosperity of the people. The urgency of this reformulation is compounded by the imminent threat of climate change, which introduces high uncertainty into the hydrological cycle—manifesting as extreme droughts and floods—thereby directly impacting the agricultural sector. This research aims to formulate a climate-adaptive water resource management policy that secures the priority rights of farmers. Employing a Normative Legal Research Method with Statutory and Conceptual Approaches, the findings present a new, holistic legal and institu-tional framework. This framework centers on two pillars: first, the firm assertion and absolute legal protection of irrigation water allocation for farmers, even during periods of scarcity; and second, the adoption of a Climate-Adaptive Governance Model. This governance model integrates a unified climate monitoring system, resilient water infrastructure, and the empowerment of Water User Associations (P3A) at the grassroots level to independently respond to shifting climate patterns. This reformulation is essential for achieving water management that is just, sustainable, and effective in maintaining national food security

Digital payment systems have become one of the main innovations in financial transformation. Over the past few years, these systems have gained significant traction and are now at the forefront of reshaping financial landscapes globally. Currently, digital payment systems have changed global transactions by slowly replacing the transaction patterns of societies that were previously dominated by conventional transactions, offering more efficiency, security, and accessibility. This transformation is closely related to the development of fintech, which has given rise to instruments in the form of electronic money and blockchain technology. These advancements have not only changed the way payments are made but also enabled the inclusion of previously underserved populations in the financial ecosystem. This study uses a bibliometric approach to analyze scientific publications, with the main sources coming from Scopus using the keywords “digital payment systems,” “electronic money,” and “fintech.” By utilizing Biblioshiny in the VOSviewer application, this study aims to examine publication trends, contributions from various countries, institutions involved, and thematic connections between topics. In conclusion, this study contributes to expanding the understanding of the development of digital payment systems, while also presenting a global research map that can be used as a reference for academics, researchers, and policymakers involved in financial innovation.

Automatic motorcycle spare part sales have increased along with the high use of automatic two-wheeled vehicles in the community. To support optimal sales strategies and stock management, customer purchasing pattern analysis is required. This study uses the FP-Growth algorithm to identify association patterns between automatic motorcycle spare part products that are frequently purchased together. FP-Growth was chosen because of its ability to efficiently find frequent itemsets without the need to generate candidate itemsets as in the Apriori algorithm. Transaction data is processed to form an FP-Tree which is then extracted to find relationships between items. The analysis results show combinations of products that frequently appear together, such as brake pads and engine oil, which can be used as a basis for compiling sales packages, product placement, and product recommendations. By implementing the FP-Growth algorithm, spare part stores or workshops can improve service and efficiency in sales management.

Green innovation has become a crucial approach to addressing sustainability challenges within global economic and environmental contexts. This study maps the development of green innovation research through a bibliometric analysis using data from the Scopus database covering the period 2021–2024. Bibliometric techniques were applied with VOSviewer and R Studio to examine publication trends, citation patterns, author collaboration, and keyword networks. The results show a significant growth of publications in the last five years, with major themes focusing on sustainable development, environmental technology, and economic implications of green innovation, while leading contributions come from China. Influential journals in innovation and environmental management are identified as key publication outlets, and keyword analysis reveals the integration of green innovation into sustainability strategies and economic policy discussions. This study contributes to a clearer understanding of the intellectual structure and emerging directions of green innovation research, offering insights for scholars, business practitioners, and policymakers in advancing sustainable innovation practices.

This study aims to analyze hematocrit values ​​using a micro method with capillary blood samples in pregnant women with anemia at the Sidodadi Kisaran Barat Community Health Center. This study is a descriptive study with a cross-sectional approach involving 15 pregnant women as respondents. Data collection was carried out through hematocrit laboratory examinations and data collection of respondent characteristics. The results showed that 60% of respondents had hematocrit levels below normal values, while 40% of respondents had hematocrit levels within normal limits. Low hematocrit levels in pregnant women are influenced by several factors, including age, education level, employment status, and level of knowledge about anemia during pregnancy. This condition has the potential to increase the risk of pregnancy complications if not optimally managed. Therefore, it is recommended that health workers continue to increase educational efforts regarding anemia prevention, the importance of regular pregnancy check-ups, and encourage pregnant women to maintain a balanced nutritional consumption pattern and adequate iron intake to support maternal and fetal health.

This study investigates Qur’an-based healing practices within the Jakarta Qur’anic Structure Studies Community, focusing on the understanding of the Qur’an as Asy-Syifā’ (a source of healing) and the therapeutic application of Qur’anic verses through the Qur’anic Structure method. Employing a qualitative, descriptive-analytical design within a Living Qur’an and phenomenological framework, data were collected through participant observation, in-depth interviews with three key informants, and questionnaires administered to 23 practitioners. The findings show that the community positions the Qur’anic Structure method as an alternative approach to both physical and spiritual healing by treating the entire Qur’an as a medium of cure. This practice is operationalized through four principal patterns: the ‘Ain Structure, Page Structure, Alphabet Structure, and Surah Structure, all of which refer to the 18-line mushaf published by PT Taj Company (Karachi, Pakistan). Practitioners’ testimonies indicate perceived improvements in physical and psychological conditions, framing this method as a form of Qur’anic self-healing (ikhtiar) while reaffirming that ultimate healing belongs solely to Allah SWT.

This study examines the role of mathematics learning in improving logical thinking skills in early childhood. The background of this study is based on the importance of logical thinking skills as a foundation for children's cognitive development, which can begin at an early age through appropriate mathematics learning. The purpose of this study is to analyze how mathematics learning can stimulate the development of logical thinking in early childhood and explore effective learning strategies. The methods used are library research and observation of several models of mathematics learning for early childhood in early childhood education institutions. The findings indicate that fun and concrete activity-based mathematics learning can improve children's abilities in critical thinking, constructing patterns, drawing conclusions, and solving simple problems. The implications of this study emphasize the need for the application of creative and interactive mathematics learning methods to support the development of logical thinking from an early age, while also encouraging educators to integrate mathematics into children's daily activities. This study also recommends the development of learning media appropriate to children's developmental stages for optimal results.