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Parental involvement is widely acknowledged as a key factor in student academic success, particularly in second language acquisition. However, its impact at the university level, especially among pre-service English teachers, remains underexplored. This study investigates the relationship between parental involvement and English language achievement among first-year English Education students at Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin (UNISKA). Employing a quantitative survey design, data were collected from 36 purposively selected participants using a structured Likert-scale questionnaire. The instrument measured both the forms and frequency of parental involvement and students’ self-reported performance in English-related subjects. Data were analyzed using descriptive statistics and Pearson Product-Moment Correlation via SPSS 26. Findings indicate that students generally perceive moderate to high levels of parental involvement, especially in providing academic resources, financial support, and attending university-related events. However, involvement in educational decision-making and career discussions was notably low. A significant positive correlation was found between parental involvement and students' academic performance, particularly in aspects such as discipline, assignment completion, and encouragement. Emotional impacts such as increased motivation or reduced anxiety showed more mixed responses. These findings highlight the enduring influence of parental support in higher education and suggest further exploration of its emotional dimensions.

The increasing volume of online hotel reviews provides valuable insights into customer perceptions but poses challenges for manual analysis due to its unstructured nature. This study aims to compare the performance of Recurrent Neural Network (RNN) and Bidirectional Encoder Representations from Transformers (BERT) in hotel review sentiment analysis. A total of 20,491 TripAdvisor hotel reviews were classified into three sentiment categories: negative, neutral, and positive. The research methodology includes text preprocessing, stratified data splitting, class imbalance handling using Random Over-Sampling, tokenization, and supervised model training. Model performance was evaluated using a confusion matrix and classification metrics. The results indicate that BERT outperforms RNN, achieving an accuracy of 80.54%, while RNN reached 62.21%. BERT demonstrated superior capability in capturing contextual and semantic information in hotel reviews. These findings suggest that transformer-based models are more effective for sentiment analysis of complex textual data in the hospitality domain and can support data-driven service improvement strategies.    

Website Accessible Jambi City Population and Civil Registry Service https://disdukcapil.jambikota.go.id. The problem with the Jambi City Population and Civil Registry Service website is that not all information is available, especially on the Profile menu there is a Media Information sub-menu, Data menu and Facilities and Infrastructure menu. On the Information Media sub-menu, there is a Demographic Data sub-menu, where the contents of the sub-menu are still empty, preventing users from obtaining information. On the Public Facilities and Infrastructure menu from the sub menu, the data cannot be accessed so that it makes users unable to get information. And in the appearance of the Jambi City Population and Civil Registry Service, when accessed via Google Chrome, the appearance is disorganized, so users have to open the website using a laptop/PC to get a website display that is orderly and easy for users to understand. Quality measurement is carried out based on user satisfaction point of view in order to improve the quality of service to the community and make optimal use of the website. In analyzing user satisfactionwebsite DUKCAPIL Jambi using the webqual 4.0 method, there are 4 variables, namely usability (usability), information quality (information quality), interaction quality (interaction quality), and user satisfaction (user satisfaction) and using the software (software) SPSS. Of the 3 hypotheses proposed, all hypotheses were accepted in this study.

The implementation of the Electronic-Based Government System (SPBE) is essential for achieving efficient, transparent, and accountable village governance. Sido Rukun Village in Merangin Regency, Jambi Province, has begun using several government applications but lacks a structured enterprise architecture aligned with the national SPBE framework. This study aims to develop an enterprise architecture for SPBE in the business process domain at Sido Rukun Village. The research employs the TOGAF ADM (The Open Group Architecture Framework – Architecture Development Method) approach, involving stages such as identifying current business processes, designing a target architecture, and conducting a gap analysis between the as-is and to-be states. The findings include a business process architecture blueprint compliant with Presidential Regulation No. 95 of 2018 and Presidential Regulation No. 132 of 2022 on the National SPBE Architecture. This blueprint encompasses BPMN-based business process models and supporting artifacts that serve as a foundation for integrated information systems at the village level. The study’s implications are significant: it provides Sido Rukun Village with a practical and standardized technical blueprint for implementing a sustainable electronic-based government system, thereby supporting its transformation toward a Smart Village capable of adapting to evolving information and communication technology trends.

Jambi Province is one of the largest natural rubber producing regions in Indonesia; however, rubber factories under GAPKINDO Jambi still face productivity issues, particularly the gap between production capacity and actual output, and productivity assessment that is still conducted manually by GAPKINDO Jambi. This study employs Decision Tree, Random Forest, KNN, and SVM algorithms within a structured pipeline involving preprocessing, feature selection, standardization, data balancing using SMOTE, and hyperparameter tuning. The proposed solution applies productivity level classification both individually and through paired combinations (ensemble voting). The results show that the Decision Tree + Random Forest model achieves the best performance with an accuracy of 0.84 and an F1-score of 0.83, confirming the effectiveness of ensemble methods in supporting productivity improvement decisions.

The development of information technology has encouraged restaurants and cafés to function not only as dining places, but also as venues for hosting various events. However, the event reservation process at Rumah Makan Ny. Hartini and Café Rain is still carried out manually through logbooks, telephone calls, and WhatsApp, resulting in problems such as unorganized data, delayed confirmations, and miscommunication with customers. In addition, the manual system limits access to information regarding venue availability, reservation schedules, and additional facilities required by customers. This study aims to develop a web-based event reservation information system using the prototyping method. The system design was carried out using Unified Modeling Language (UML), including use case diagrams, activity diagrams, and class diagrams to model user interactions, process flows, and system structure. The results of the study show that the developed system is able to automate the reservation process, customer data recording, reservation confirmation, schedule management, and additional facilities management. This system improves operational efficiency, data accuracy, and service quality, while also making it easier for customers to make reservations independently and obtain information quickly and accurately.

Public complaint services are an essential part of public service delivery in supporting the government’s rapid response to various social issues and emergency situations. In West Tanjung Jabung Regency, public complaint services are provided through the HALO USTAD 112 Call Center managed by the Department of Communication and Informatics. However, the existing service still faces several limitations, including the lack of optimal integration in complaint data management, inadequate documentation of reports based on regional classifications, and limited capabilities in storing and retrieving complaint data. This study aims to optimize the HALO USTAD 112 Call Center service through the design of a mobile-based public complaint information system, so that the processes of receiving, managing, and monitoring reports can be carried out more effectively and in a structured manner. The system development applies the Waterfall method, which consists of requirement analysis, system design, implementation, and testing stages. The designed information system includes key features such as user and admin login, complaint submission, report management and verification, report monitoring, statistical visualization of complaint data, and regional-based report recapitulation. The application is developed using the Flutter framework with the Dart programming language, while Supabase is utilized as the backend integrated with a PostgreSQL database. The results of this study are in the form of a system design and prototype that are expected to improve the quality of public complaint services and support more accurate, integrated, and efficient data management.

Chronic Kidney Disease (CKD) is a heterogeneous disorder that gradually affects the structure and function of the kidneys, is difficult to recover, and causes the body to be unable to maintain metabolism and fail to maintain fluid and electrolyte balance, leading to increased urea levels. Chronic kidney disease data was obtained from Kaggle, in this study a comparison was made between two classification algorithms, namely Naïve Bayes Classifier (NBC) and Random Forest because it is not yet known what algorithm is best in classifying chronic kidney disease (CKD). Both algorithms are evaluated based on performance metrics such as accuracy, precision, recall, and confusion matrix. The results of the evaluation showed that in a dataset of 400 samples, the performance  of the Naïve Bayes Classifier (NBC) algorithm obtained an accuracy of 94%, while Random Forest had an accuracy of 93%. Then in the small dataset (158 data), Random Forest got a better accuracy score with 87% compared to the Naïve Bayes Classifier (NBC) of 78%. Based on the results of the evaluation, Random Forest has a more stable performance on small datasets, while Naïve Bayes Classifier (NBC) provides higher performance on larger datasets in the context of chronic kidney disease classification.

This study examines Japanese advertising and product-information texts on Shiseido Japan’s official website (www.brand.shiseido.co.jp) that grammatically prevent readers from construing statements as universal claims (“always” or “true for everyone”). It addresses two problems: how universal readings are blocked through grammatical construction in this register, and how the main blocking mechanisms differ in limiting generalisation and managing scope. The data consist of sentence-level usage, precautionary, and quality-related statements that plausibly invite broad general interpretations. Seven analytically representative tokens are used as illustrative evidence, covering wake-negation, baai-based case framing, and event/occasion packaging with V-ru koto ga aru, including rare-event calibration with mare ni and layered conditional framing. The study employs qualitative, theory-driven grammatical analysis focusing on clause structure, embedding, nominalisation, connective relations, and the compositional contribution of key markers. The results identify recurring templates with distinct structural signatures. Wake-negation blocks over-strong uptake by denying a candidate inference (…to iu wake de wa arimasen). Case framing with baai shifts categorical commitments into situation-restricted possibility (…baai ga arimasu), including complex variants that add causal linkage, avoidance marking, and directive closure. Event/occasion packaging with koto plus existential predication (…koto ga arimasu) presents anomalies as contingent occurrences, and it can be triggered by causal conditions (e.g., temperature change) or conditional frames (…to). Rare-event marking with mare ni further calibrates frequency and often co-occurs with contrastive reassurance about quality. Overall, universal-blocking emerges as a set of non-redundant grammatical routes that constrain inference, situational domain, and event profiling in a compact public informational genre.

This study aims to analyze the implementation of the Merdeka Curriculum in Fiqh subjects and how its application affects the improvement of students' understanding. Using the library research method, this study reviews various recent literature in the form of scientific articles, accredited journals, academic books, and relevant policy documents. The results of the study show that the Merdeka Curriculum is conceptually aligned with the principles of Islamic education, especially in terms of character development, freedom of learning, and student-centered learning. However, the implementation of this curriculum in Fiqh learning still faces a number of challenges, such as teachers' limited understanding of the new curriculum approach, a lack of project-based contextual teaching materials, and difficulties in conducting authentic assessments on aspects of worship and morals. Technical challenges such as the availability of facilities and access to technology also hamper the effectiveness of learning. This study emphasizes the need for continuous teacher training, the development of open-access learning resources, and improved infrastructure support in order to strengthen the implementation of the Merdeka Curriculum. Overall, this curriculum has significant potential to improve students' understanding of Fiqh if it is supported by appropriate and collaborative implementation strategies.

Islamic character education faces dual challenges: declining moral values among students and conventional teaching methods inadequate for developing higher-order thinking skills. This study examines the implementation of a smart learning environment (SLE) model to enhance metacognitive understanding in Aqidah Akhlak (Islamic Creed and Ethics) instruction among eighth-grade students at MTs Salafiyah Merakurak. Employing a mixed-methods action research design, involved 16 eighth-grade students divided into two groups. Data collection utilized classroom observations, semi-structured interviews, and learning documentation. The SLE model integrated Google Classroom, interactive video content, WhatsApp Group discussions, and Google Forms assessments to create a technology-enhanced learning ecosystem. Findings revealed substantial improvements in students' metacognitive capacities: planning skills increased from 25% to 75%, monitoring abilities rose from 31% to 81%, and evaluation competencies grew from 19% to 69%. Students demonstrated enhanced learning autonomy, active participation in collaborative discussions, and improved self-reflection on content comprehension. The SLE approach successfully fostered engaging learning experiences while facilitating deeper internalization of Islamic ethical values. However, implementation encountered constraints including limited technological infrastructure and varied digital literacy levels among students. This research underscores the critical need for developing teachers' digital competencies and strengthening madrasah technological infrastructure to optimize technology-integrated Islamic education.

The study of the Qur'an in the West has a long history. It began with the tradition of orientalism in the Middle Ages and has evolved into a modern academic approach that relies on philology, historical, and hermeneutical. In the West, the study of the Qur'an was initially dominated by apologetic and polemic reasons. However, since the 19th century, scientific approaches have begun to dominate thanks to the research of figures such as Theodor Nöldeke, Ignaz Goldziher, and John Wansbrough. After that, the focus of modern research turned to the linguistic analysis and structure of the Arabic language of the Qur'an. It includes the study of semantics (Toshihiko Izutsu), stylistic analysis, and comparative studies between pre-Islamic Arabic dialects and the language of the Qur'an. Western scholars have diverse views on the Qur'an in Arabic. Some question the structure, origin, and cohesiveness of the text, while others acknowledge its uniqueness, coherence, and rhetorical power. Despite epistemological differences, this article analyzes the history of Qur'an study in the West, identifies the main methods used to analyze the Qur'an in Arabic, and outlines the various critical perspectives and appreciation of Western scholars on the linguistic character of the Qur'an. The results of the analysis show that, from the polemic paradigm, the study of the Qur'an is increasingly moving towards a more interdisciplinary scientific approach.

 The development of modern education requires a strong philosophical foundation to ensure that learning processes are not merely technical but oriented toward holistic human formation. This article aims to comprehensively analyze the role of the philosophy of science within contemporary education through a conceptual exploration grounded in an extensive literature review. The philosophy of science with its three major pillars: ontology, epistemology, and axiology serves as an analytical framework for understanding the nature of human beings, the structure of knowledge, and the values embedded within educational objectives. The research methodology employs the Miles and Huberman data analysis model, consisting of data reduction, data display, and conclusion drawing/verification. The findings indicate that the philosophy of science plays a strategic role in providing direction and orientation for the development of humanistic, adaptive, and globally responsive education. Moreover, this study reveals that the advancement of scientific knowledge encounters significant challenges, including ontological complexity, epistemological crises driven by digital disruption, moral degradation, and shifting scientific paradigms. In the age of artificial intelligence and globalization, the philosophy of science emerges as an ethical and methodological compass to ensure that scientific progress remains aligned with human welfare. This study underscores the urgency of reconstructing educational paradigms by integrating humanistic values, local wisdom, and modern scientific thought to realize a future of science that is ethical, sustainable, and dignified.

This study examines the influence of foreign ownership, return on assets (ROA), and firm size on environmental, social, and governance (ESG) disclosure among energy sector companies listed on the Indonesia Stock Exchange (IDX) during 2022–2024. The sample was selected through purposive sampling, including firms that consistently published annual and sustainability reports in accordance with the Global Reporting Initiative (GRI) standards. ESG disclosure was measured as the proportion of disclosed GRI indicators to the total applicable indicators. Multiple linear regression analysis shows that foreign ownership and firm size significantly enhance ESG disclosure, while ROA has no significant effect. These results support legitimacy theory, suggesting that companies increase ESG transparency primarily to secure societal acceptance and maintain their social license to operate. In the energy sector, where environmental sensitivity and public scrutiny are high, ownership structure and firm scale emerge as stronger determinants of ESG disclosure than short-term profitability.

This study examines the influence of work discipline, training, and motivation on employee performance at PDAM Tirta Ayu, Tegal Regency. In a public service organization such as PDAM, employee performance is crucial to ensure customer satisfaction and strengthen institutional competitiveness. A quantitative survey method was used with questionnaires distributed to all 115 employees using a saturated sampling technique, as the entire population was included. The independent variables analyzed were work discipline (attitude, compliance with rules, responsibility), training (materials, methods, instructor competence, duration, facilities), and motivation (intrinsic and extrinsic). Employee performance, as the dependent variable, was measured using indicators of work quality, work quantity, teamwork, and problem-solving ability. The data were processed through multiple linear regression to assess simultaneous and partial effects. The research findings revealed that work discipline, training, and motivation each have a positive and significant impact on employee performance, but for training has a positive and insignificant effect, this is shown by the significant results of each significant level for work discipline sig value = 0.000 (<0.05), training sig value = 0.632 (>0.05) and motivation with sig value = 0.000 (<0.05). These results highlight the importance of strengthening employee discipline, implementing well-structured and sustainable training programs, and fostering sustainable motivation strategies. This research provides practical implications for PDAM Tirta Ayu management in designing policies to improve overall employee performance, thereby improving service quality and organizational competitiveness.  

This study seeks to evaluate the extent to which profitability, leverage, independent commissioners, and political links influence tax avoidance in Indonesian mining companies for the 2021–2024 timeframe. The mining sector was chosen because it contributes significantly to national income but is typically associated with the practice of tax avoidance. The novelty of this study lies in the addition of the political connections variable, which has rarely been studied in the context of Indonesian mining. The research data were obtained from annual reports and financial statements of companies obtained through purposive sampling, resulting in 77 observations. Multiple linear regression analysis under a quantitative method was applied, and the evidence suggests that profitability contributes positively to tax avoidance, as higher profits are associated with a stronger tendency for companies to minimize tax payments. Conversely, political connections have a negative effect, indicating that political and military experience shapes loyalty to the interests of the state, thereby encouraging tax compliance. Meanwhile, leverage and independent commissioners do not exert any influence on tax avoidance. The outcomes of this research may serve as a reference for regulators, scholars, and investors to better comprehend the determinants of tax avoidance and to contribute to enhancing governance structures and refining tax policy.

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.

The objective of this study is to directly analyze and illustrate the compositioneof the auditecommittee, which consists of financial knowledge, independence and the quantity of members on the committee, concerning the financial statement quality of energy sector industries listed on the IDX in 2023-2024.High-quality financial statements are a crucial component reflecting the outcome of the accounting process and are vital for stakeholders in decision-making. Despite regulatory requirements for audit committees, corporate financial statements in Indonesia often contain earnings management or accounting irregularities, indicating that the audit committee's very existence is insufficient to guarantee financial statements' quality. A numerical approach with a causal-comparative approach is utilized in this investigation. The secondary quantitative data are obtained from companies’ yearly financial statements, annual reports, and corporate governance disclosures published on the official IDX website. The data are examined using EViews software for panel data regression, going through many steps, including descriptive statistics, classical assumption testing, panel data model selection, and regression analysis for hypothesis testing. The audit committee's size, objectivity, and financial acumen make up the study's independent variables. Meanwhile, financial statement quality as the dependent variable is measured through earnings quality proxy using the discretionary accruals calculation approach (Jones model or Modified Jones model). Specifically, this research seeks to deliver theoretical and practical benefits for regulators in formulating corporate governance policies, give companies a comprehension of the importance of an effective audit committee, and help investors make informed investment choices.

Shaping central banking for sustainability has become increasingly relevant as climate change and the pursuit of sustainable development challenge the conventional scope of monetary policy. Green monetary policy reflects efforts to align central banking with environmental and economic objectives, yet the scholarly literature on this issue remains fragmented. This study employs a bibliometric approach using R Studio (Bibliometrix) to analyze publications indexed in Scopus from 2015 to 2025. The dataset comprises more than 1,200 documents with an annual growth rate of nearly 12%, signaling the rapid expansion of research in this field. Bibliometric techniques, including citation mapping, co-authorship analysis, and keyword co-occurrence, are applied to identify influential authors, sources, and thematic clusters. The results indicate a steady increase in international collaboration and a consolidation of research themes, reflecting the growing importance of sustainability in central banking discourse. This study is expected to contribute by providing a structured overview of the intellectual landscape of green monetary policy, clarifying its links with sustainable development and climate change, and offering guidance for future research and policy innovation in sustainable central banking.

The digital economy and e-commerce are rapidly transforming global markets, driving efficiency, inclusivity, and innovation. However, these developments also produce unintended consequences, particularly regarding environmental sustainability. This study aims to examine the relationship between digital transformation, the expansion of e-commerce, and their impact on carbon emissions and socio-economic outcomes. Using bibliometric analysis and VOS Viewer to map and analyze research trends from leading academic databases, this paper identifies key themes, knowledge clusters, and research gaps in the intersection of digital economy, logistics, and sustainability. The findings indicate that technological advances foster economic growth and greater accessibility but simultaneously contribute to rising energy consumption, logistics intensity, and carbon footprints. These results highlight the dual nature of digitalization as both a catalyst for inclusive development and a driver of environmental pressures. The study argues that an integrated policy framework is crucial to leverage the benefits of digital transformation while mitigating its environmental costs. It emphasizes the importance of green innovation, sustainable infrastructure investment, and inclusive e-commerce practices as key strategies for ensuring long-term socio-economic resilience. Ultimately, the paper contributes to the policy discourse by positioning innovation, inclusivity, and environmental stewardship as complementary rather than competing forces, thereby offering a pathway for future digital economy development that is both equitable and sustainable.