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Background: Dietary adherence is a crucial component in the management of patients with chronic kidney disease (CKD) undergoing hemodialysis. Non-adherence may lead to metabolic imbalance, increased morbidity, and reduced quality of life.Objective: To identify factors associated with dietary non-adherence among patients with CKD undergoing hemodialysis at Imelda Hospital, Medan. Methods: A cross-sectional study was conducted among patients undergoing routine hemodialysis. Data were collected using structured questionnaires assessing knowledge, attitudes, and family support related to dietary adherence. Statistical analysis was performed using chi-square tests and logistic regression with a significance level of p < 0.05. Results: Knowledge, attitudes, and family support were significantly associated with dietary non-adherence (p < 0.05). Family support was identified as the most influential factor. Conclusion: Dietary non-adherence among hemodialysis patients is influenced by knowledge, attitudes, and family support. Strengthening patient education and family-centered nursing interventions is essential to improve dietary adherence.

The goal of this research is to explore the relationship between stock prices, liquidity, profitability, and leverage. This study focuses on transportation and logistics companies that were registered in the Indonesia Stock Exchange from 2021 to 2023. A quantitative approach was taken, utilizing secondary data derived from the annual financial statements of companies that were active during this time frame. The sample comprised 45 data points, selected using a purposive sampling technique. The independent variables include leverage, measured with the Debt to Equity Ratio (DER), profitability, assessed through Return on Assets (ROA), and liquidity, evaluated via the Current Ratio (CR). The dependent variable for this research is the stock price. The findings from this partial analysis reveal that liquidity significantly and negatively impacts stock price, with a t-count of -2.264 and a significance level of 0.029. However, the correlation between stock price and profitability was found to be insignificant, indicated by a significance value of 0.071 and a t-count of -1.853. Similarly, leverage does not significantly affect stock price, as evidenced by a t-count of -0.657 and a significance level of 0.515. Nonetheless, when considered collectively, the three factors of leverage, profitability, and liquidity do influence stock prices. According to the coefficient of determination (R2) test, these three variables account for 13.9% of the volatility in stock prices, leaving the remaining 86.1% to be attributed to external factors not examined in this study.

Hypertension is a major global health risk that requires accurate early detection, yet conventional methods struggle with complex and imbalanced health datasets. This study aims to optimize hypertension prediction using a Logistic Regression model integrated with Borderline-SMOTE to enhance recall and provide model transparency through SHAP (Shapley Additive Explanations). The method utilizes the BRFSS dataset, applying Borderline-SMOTE to address class imbalance at the decision boundary and XAI techniques for global and local interpretation. The findings show that the model achieved an accuracy of 0.719, an AUC of 0.800, and a significantly improved recall of 0.756. SHAP analysis identified age, high cholesterol, and BMI as the most influential risk factors, while waterfall plots successfully clarified individual risk extremes, ranging from 1.72% to 99.43% probability. These results imply that the proposed approach provides a sensitive and transparent screening tool for public health practitioners, effectively balancing statistical efficiency with clinical accountability.

The scarcity of real-world data in Air-Conditioning (AC) fault diagnosis necessitates the use of synthetic data; however, rule-based synthetic datasets often suffer from a significant sim-to-real domain gap. To address this, we propose a Model-Data Coevolution (MDC) framework that employs a Simulated Annealing (SA) controller to optimize augmentation parameters. We introduce a novel technique, Stochastic Feature Decoupling (SFD), which applies independent noise to raw and derived features, contrasting it with traditional Logically-Consistent Augmentation (LCA). Empirical results show that SFD significantly outperforms LCA, achieving a weighted F1-score of 0.93 and increasing NORMAL class recall to 82%. We demonstrate that by breaking deterministic feature links, SFD acts as a robust regularizer, utilizing "physically impossible" data to enhance generalization in complex real-world environments.

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.

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.

This study explores how nascent entrepreneurs in Indonesia can improve their business innovation performance by utilizing volunteerism and digital competencies, particularly in the context of financial and technological limitations. These challenges significantly hinder their capacity for effective innovation, especially in resource-limited settings where access to tools and expertise is often scarce. A quantitative approach was employed, using data from 156 nascent entrepreneurs, which was analyzed through Structural Equation Modeling (SEM). The results indicate that the voluntary exchange of ideas and competences, framed through the Service-Dominant Logic (S-DL) perspective, plays a critical role in overcoming resource constraints and enhancing innovation outcomes. By facilitating collaboration and knowledge-sharing via volunteerism, nascent entrepreneurs can strengthen their digital and managerial capabilities, which are essential for driving innovation. The study highlights the importance of creating ecosystems that support stakeholder-driven volunteer initiatives, which help develop strategic digital competencies among emerging entrepreneurs, thereby fostering greater innovation capacity and ensuring long-term business sustainability.

A wall follower robot is a type of autonomous robot that is designed to move by following a wall at a certain distance. This research aims to design and build a Wall follower robot equipped with a Fuzzy-PID control system to improve navigation performance. The robot uses five HC-SR04 ultrasonic sensors to detect the distance to the wall and the surrounding obstacles. The data from the sensor is then processed by a Fuzzy-PID algorithm that combines the advantages of conventional PID control with fuzzy logic, resulting in a more adaptive response to environmental conditions. The test results showed that the robot with Fuzzy-PID control was able to maintain the stability of the distance to the wall more consistently compared to the pure PID control. In addition, the system exhibits better adaptability to complex environmental conditions, such as sharp turns, uneven wall surfaces, and the presence of resistance variations. The application of Fuzzy-PID control has been shown to improve the stability, response speed, and accuracy of the robot's navigation. These findings are expected to contribute to the development of robotic navigation systems for a wide range of practical applications, including automated cleaning robots, environmental exploration, and industrial systems that require reliable autonomous mobility.

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.

This study aims to design the User Interface (UI) and User Experience (UX) on the VINIX Showcase Website as a personal branding platform and digital Skill Passport for participants of the VINIX Seven Aurum Program using the Design Thinking method. The background of this research is the absence of an integrated digital platform that can systematically and easily document and display participants' skills, projects, certificates, and professional identity. The design process is carried out through five stages of Design Thinking, namely Empathize, Define, Ideate, Prototype, and Test, starting with exploring user needs, formulating problems, developing solution ideas, creating Prototypes, and Usability Testing. The results of the study consist of the UI/UX design of the VINIX Showcase Website, which includes registration and Login features, user Dashboard, Skill Passport, project upload, public Showcase, and automatic CV generation feature. Testing using the Usability Testing method showed that the resulting design has a good level of ease of use and comfort and is acceptable to users. This research is expected to be an effective digital solution in supporting personal branding, skills documentation, and improving the professionalism of VINIX Seven Aurum Program participants.

The use of the VSCO application continues to face technical issues, including errors during editing, limited feature access, and login problems that affect user satisfaction. This study analyzes user satisfaction with the VSCO application using the End User Computing Satisfaction (EUCS) method. The study involved 385 VSCO users as respondents, with data collected through questionnaires and analyzed using SmartPLS 3.0. In this research, Accuracy variable does not affect user satisfaction, whereas the Content, Format, Ease of Use, and Timeliness variables have a significant effect on user satisfaction. The study shows that content quality, interface design, ease of use, and system timeliness are the main factors influencing user satisfaction with the VSCO application.

The rapid growth of e-commerce platforms in Indonesia, particularly Tokopedia, has resulted in a large volume of consumer reviews containing valuable information regarding customer perceptions and satisfaction. However, manual analysis of such reviews is inefficient and prone to subjectivity, necessitating an automated approach based on machine learning. This study aims to classify the sentiment of sports product reviews on Tokopedia into positive, negative, and neutral categories by applying Logistic Regression, Support Vector Machine (SVM), and Random Forest using the Term Frequency–Inverse Document Frequency (TF-IDF) approach. The data were collected through web scraping of Indonesian-language sports product reviews and processed through several preprocessing stages, including data cleaning, case folding, tokenization, stopword removal, and stemming. Feature representation was performed using TF-IDF to transform textual data into numerical vectors, after which the dataset was divided into training and testing sets with an 80:20 ratio. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. The results indicate that the application of TF-IDF significantly improves the performance of all models, with SVM consistently achieving the most optimal performance compared to Logistic Regression and Random Forest. These findings demonstrate that classical machine learning algorithms combined with TF-IDF remain highly effective for sentiment analysis of Indonesian-language text. The implications of this study are expected to assist sellers in understanding customer opinions, support consumers in making informed purchasing decisions, and serve as a foundation for the development of sentiment analysis and recommendation systems on e-commerce platforms.

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.

Digital portfolios are a crucial tool for professionally showcasing abilities and learning objectives. Nevertheless, the projects and certificates of participants in the Independent Study program at VINIX7 are still kept apart and are not controlled by an integrated system. This requirement is the basis for the research's design and development of a website-based digital portfolio system that will serve as participants' key platform. Requirements analysis, system design, implementation, and testing are all steps in the Waterfall approach of system development. The Laravel framework was used to create the VinixPort website, which is backed by a MySQL database. The system has tools for managing portfolio material, talent evaluation, user registration and login, and data presentation via analytics. The study's findings show that the VinixPort website was created successfully and that all of the system's primary features work as intended. This service helps users create organized digital portfolios that are readily available and prepared for both professional and academic use.

This study used a qualitative approach with a Systematic Literature Review (SLR) as the data collection technique. This study examined the institutional factors causing long dwelling times at Tanjung Emas Port and mitigation efforts. The analysis revealed that the main root of the problem lies in the lengthy administrative and goods inspection (customs) processes, particularly in the red, yellow, and green inspection lanes. Obstacles include the lack of data integration (such as PIB and SPPB dates) between the Semarang Container Terminal (TPKS) and Customs, as well as incomplete documents by service users. A significant impact was felt on imports, where dwelling times were longer due to complicated quarantine and customs inspections, while exports were relatively unaffected.

This study discusses the phenomenon of digital entrepreneurship in the era of global climate awareness, focusing on the integration of artificial intelligence (AI) ethics, sustainable technology, and green innovation. The main issues raised are the fragmentation of analysis between digital business ethics, green economic opportunities, and technological challenges such as greenwashing, high AI energy consumption, and the digital divide. The purpose of this study is to formulate an interdisciplinary framework that combines ethical, technological, and sustainability dimensions to strengthen the role of digital entrepreneurs in achieving low-carbon development. The methods used include critical literature analysis, bibliometrics of 200 publications (2018-2025) using VOSviewer, and fuzzy logic-based simulations using the UNESCO AI ethics framework (2021) and the sustainable business model of Bocken et al. (2014). The results show four main research clusters: AI for Sustainable Innovation, Ethical Digital Business, Blockchain for Green Supply Chain, and Circular Digital Economy. The application of AI ethics increases the efficiency of green business decisions by up to 20%, consumer trust by 17%, and MSME participation by 14%. The synthesis of findings confirms that AI ethics acts as a conceptual mediator that strengthens the link between technological innovation and sustainability. In conclusion, ethical digital entrepreneurship has great potential as a driving force for Indonesia's green economy, but it requires digital ethics audit policies and the adoption of low-carbon technologies to address ethical and environmental risks in the AI era.

This paper analyzing how reshaping the future of global trade, explore the transition from traditional online retail models toward sustainable e-commerce ecosystems. By examining the integration of circular economy principles, green logistics, and ethical supply chain manajement, the study identifies the core drivers behind this transformation

This study aims to evaluate the effects of profitability, leverage, liquidity, and cash-flow shocks on the financial distress of companies in the hotel, restaurant, and tourism subsector listed on the Indonesia Stock Exchange during the period 2021 to 2024. The research approach employed is quantitative, using logistic regression analysis. The data analyzed are secondary data obtained from the annual financial statements of the respective companies. The results of the study indicate that, simultaneously, the four independent variables significantly influence financial distress. However, based on partial testing, each variable, namely Return on Assets (ROA), Debt to Equity Ratio (DER), Current Ratio (CR), and cash flow shock, does not show a significant relationship with financial distress. These findings imply that the risk of financial distress in this industry cannot be explained solely through a single financial indicator; instead, a more holistic approach is required. This study provides essential contributions to both management and investors in assessing companies' financial condition and formulating appropriate strategic decisions.

This study aims to explore the implementation of Standard Operating Procedures for immigration services at TPI Tanjung Priok Port and examine its impact on service effectiveness in Indonesia's maritime sector. The research employed a qualitative approach to analyse the gap between formal SOP guidelines and on-the-ground practices, examining internal and external factors, including resource limitations, technological constraints, and inter-agency coordination issues. The findings reveal significant disparities that lead to both positive and negative discretion amongst frontline Immigration officers, influencing service consistency, efficiency, and transparency. Negative discretion results in procedural deviations that compromise reliability and potentially foster corruption, delays, and inefficiencies. In contrast, positive discretion emerges as adaptive responses indicating weaknesses in SOP design or infrastructure. The study concludes that enhancing frontline officers' competence, motivation, and accountability is essential for achieving desired outcomes, whilst integrating technological solutions such as digital documentation and real-time monitoring is vital for streamlined, transparent, and accountable procedures. Improving SOP adherence, coupled with better resource allocation and inter-institutional cooperation, can significantly reduce vessel turnaround times, lower logistics costs, and bolster maritime competitiveness. The research advocates for dedicated training programmes, supervisory systems, and technological innovations to ensure SOP compliance, minimise discretion-driven deviations, and promote accountability, thereby optimising maritime service delivery and supporting Indonesia's strategic maritime development objectives.

This Community Service Program was conducted to enhance the competencies of supervisors in the logistics and transportation division of an international cargo company through leadership training tailored to the characteristics of Generation Z. The program aimed to strengthen participants’ capabilities in managing workplace dynamics, improving team communication, and promoting more effective performance through a flexible leadership approach. The training was held on November 18, 2025, at the company’s head office in Bekasi and was attended by 16 supervisors. The methods used included material presentations, group discussions, case study analysis, and an interactive question-and-answer session. The results indicate an increased understanding among participants regarding Generation Z work behavior, appropriate leadership principles, and more adaptive management strategies. This program is expected to provide sustainable benefits for human resource development and to enhance leadership effectiveness within the logistics sector.