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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.

Physical fitness is a fundamental determinant of athletic performance and is strongly influenced by dietary intake and lifestyle behaviors. Adequate protein consumption is essential for muscle development and energy metabolism, whereas smoking has detrimental effects on lung function and aerobic capacity. This study aimed to explore the relationship between protein intake and smoking habits with physical fitness, measured by maximal oxygen uptake, among athletes of Persela Football Academy under-eighteen. A quantitative approach with a cross-sectional design was applied, involving adolescent male athletes. Protein intake was assessed using a semi-quantitative food frequency questionnaire, smoking habits were obtained through structured interviews, and maximal oxygen uptake was measured using the multistage fitness test. Findings revealed that the average daily protein intake of athletes was relatively high, while the mean maximal oxygen uptake score fell within the good category. Correlation analysis demonstrated a significant association between protein intake and aerobic fitness, as well as between smoking habits and aerobic fitness. The results indicate that lower protein intake and higher smoking frequency are linked to reduced physical fitness capacity. This study highlights the importance of nutritional interventions and healthy lifestyle promotion as integral components in the development of youth athletes to optimize performance and prevent decline in fitness.

This study aims to analyze corn consumption substitution as an alternative carbohydrate source and to measure the demand elasticity of corn in response to fluctuations in corn and rice prices at Ciawitali Market, Garut Regency. Primary data were collected through observations and interviews, along with secondary data from West Java Central Statistics Agency processed using simple linear regression and cross-elasticity analysis with SPSS. Results show that changes in corn prices explain 99.7% of variation in corn demand with a positive coefficient of 0.827, indicating a substitution effect with rice, which experienced a concurrent price increase. The cross-elasticity value of 1.64 confirms the elastic substitution relationship between corn and rice. These findings highlight the potential of corn as a substitute for rice in maintaining stable food consumption despite fluctuations in staple commodity prices.       

The development of value-added corn-based beverages representation an emerging opportunity within the agribusiness sector, particularly for student-led entrepreneurial initiatives seeking to utilize local agricultural resources. This study examines consumer perceptions of Zeagrain corn milk, a sweet-corn-derived drink positioned as a healthy, practical, and affordable alternative within the ready-to-drink market segment. The research aims to identify key attributes influencing consumer interest, evaluate perceived product performance, and assess the potential competitiveness of Zeagrain as a new agribusiness product. Data were collected using an online quantitative survey targeting respondents aged 17–35 years who represent potential urban consumers. The questionnaire measured demographic characteristics, consumption patterns of similar beverages, perceived importance and performance of product attributes, and purchase intention. The findings are expected to provide insights into consumer expectations regarding taste, packaging, nutritional value, and price. The results further serve as empirical input for improving product development strategies and enhancing the market readiness of Zeagrain. Ultimately, this study contributes to strengthening the commercialization prospects of corn-based beverages and supports innovation efforts among young agripreneurs seeking to optimize local commodities.  

This study analyzes the strategic role of digital transformation in accelerating the development of the green economy in Azerbaijan. As global economic systems shift toward sustainability-oriented models, Azerbaijan has begun integrating digital technologies—such as smart energy systems, geographic information platforms, and digital monitoring tools—into its environmental and economic policies. These initiatives are designed to reduce carbon intensity, enhance resource efficiency, and modernize industrial sectors in alignment with international climate standards. The study employs a qualitative library-based approach supported by content analysis to assess state programs, institutional reforms, and policy documents related to digital governance and renewable energy deployment. The findings indicate that digital solutions facilitate transparent decision-making, optimize energy consumption, and support ecological innovations, making them essential components of Azerbaijan’s national development agenda. However, the transition remains constrained by infrastructural disparities, limited technological competencies, and regulatory gaps. The study argues that sustainable development goals cannot be fully realized without comprehensive digital integration, institutional coordination, and capacity-building initiatives. Thus, digitalization is not merely a supportive tool but a foundational mechanism for the advancement of the green economy and long-term socio-economic transformation in Azerbaijan.

The development of e-commerce and social commerce has driven significant changes in student shopping behaviour, including at FEB UNDARIS. Ease of access, digital promotions, and the influence of social media have led students to shop online more frequently, even impulsively. This study aims to analyse how attitudes, subjective norms, and perceived behavioural control interact in shaping students' online shopping behaviour using the Theory of Planned Behaviour (TPB) framework. This study uses a descriptive qualitative method with in-depth interviews with ten students who actively shop online. The data were analysed to understand the experiences, perceptions, and social factors that influence their decisions in digital transactions. The results show that positive attitudes towards efficiency and promotions, social pressure from friends and influencers, and high perceived behavioural control due to technological convenience work simultaneously to reinforce online shopping intentions and actions. These three TPB components support each other and trigger increasingly impulsive consumption patterns in the digital environment.

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.

Digital transformation through adoption cloud technology has become catalyst in effort efficiency energy and reduction greenhouse gas emissions glass (GHG). Research This aim for analyze contribution cloud technology against efficiency operational and impact the environment in framework economy green. With use approach studies literature and secondary data analysis from report institution international and journals scientific, research This find that migration to cloud computing can reduce consumption energy up to 84% and emissions carbon up to 88% compared to with traditional IT infrastructure. These results show that cloud computing is not only solution technology, but also important strategy in support development sustainable.

In today's digital era, recommendation systems have become an integral part of supporting consumer purchasing decisions, including in the food and beverage industry. This study aims to develop a product recommendation system for snacks and beverages using the item-based collaborative filtering method. This method was chosen due to its ability to handle large-scale user and product data, as well as its efficiency in providing relevant recommendations based on user consumption patterns. In this study, the system calculates the average user rating and implements   Cosine Similarity to measure the similarity between products, resulting in more accurate recommendations. The system also evaluates the accuracy of recommendations using the Mean Absolute Error (MAE) metric. Based on the results obtained, which is 0.285403 for the average error on 17 items, the developed recommendation system can improve consumers' shopping experience, help them find products that suit their tastes, and support the sales of snacks and beverages products in the market

This study examines the emerging paradigm of federated intelligence architectures as a secure, privacy-preserving, and scalable foundation for data-driven innovation across AI, IoT, and cloud ecosystems. With billions of interconnected devices generating massive heterogeneous data, traditional centralized machine-learning models face critical limitations, including privacy risks, regulatory constraints, latency, and single points of failure. Through a qualitative content-analysis approach, this paper synthesizes contemporary research on federated learning, blockchain integration, zero-trust governance, and edge intelligence to formulate a comprehensive understanding of distributed AI infrastructures. The findings highlight that federated learning enables collaborative model training without exposing raw data, significantly enhancing privacy, security, and compliance. Moreover, combining blockchain with federated learning strengthens auditability, model integrity, and trust, while zero-trust principles provide continuous verification and adaptive security enforcement across devices. Edge-AI integration further reduces latency and bandwidth consumption, enabling real-time analytics in resource-constrained IoT environments. Collectively, these elements contribute to the formation of cognitive ecosystems capable of autonomous, interoperable, and context-aware operations. The study underscores the transformative potential of federated intelligence while identifying critical gaps that inform future research trajectories.

This research is motivated by the increasing amount of waste caused by high levels of public consumption, limited waste management facilities, and low environmental awareness. Lyfe With Less, an eco-friendly community, utilizes the function of Public Relations to deliver information and raise public awareness. This study aims to (1) identify the #SalingSilang campaign message conducted by Lyfe With Less, (2) examine the attitudes of Instagram followers of @lyfewithless toward the campaign, and (3) measure the influence of the #SalingSilang Public Relations campaign message on followers’ attitudes. The research applies the Campaign Message Design Theory, which includes message content, structure, and framing, as well as the Attitude Component Theory, which covers cognitive, affective, and conative aspects. A quantitative approach was used with a survey method by distributing questionnaires to 81 respondents selected randomly through probability sampling. The results show that the #SalingSilang campaign message received positive responses and had a significant and strong influence on followers’ attitudes. Within the Public Relations campaign message, the key message was found to be the most influential factor in the message content dimension, while in followers’ attitudes, the conative component showed the greatest change, particularly in reducing overconsumption and encouraging the optimal use of products.

The oil and gas industry plays a crucial role in meeting global energy needs, with crude oil from production wells being the primary product of upstream operations. Prior to further processing, crude oil requires pretreatment at the production site, one of the key stages being phase separation using a flash separator. This study examines the effect of variations in cooling temperature on the performance of liquid phase separation and energy requirements in the flash separation process of light hydrocarbons. The analysis was conducted through process simulation using Aspen HYSYS version 14.2 with the Peng Robinson property package. The feed stream had a mass rate of 10,000 kg per hour, a temperature of 50°F, and atmospheric pressure, with compositions of ethane, propane, isobutane, and normal butane. The process configuration included compression, cooling, and phase separation in a flash separator at a constant pressure of 50 psia. Variations in cooling temperature were applied at 20, 10, and 0°C. The simulation results indicated a thermodynamic critical point at 10°C. At 20°C, no liquid phase was formed, while at 10°C, significant liquid yield was obtained with moderate energy consumption. Lowering the temperature to 0°C dramatically increases liquid recovery, but the cooling energy requirement also increases sharply. Sensitivity analysis confirms a strong inverse relationship between temperature and condensation yield, as well as a surge in energy consumption at low temperatures. The optimal operating condition is set at 10°C, providing a balance between separation efficiency and energy efficiency in accordance with sustainable manufacturing principles.

This study aims to analyze and compare the price responsiveness of broiler chicken meat and native chicken meat in relation to household consumption patterns in Tarogong Kidul District, Garut Regency. A quantitative approach was employed using simple linear regression analysis based on primary data obtained through observations and interviews conducted in traditional markets. The analysis examines the extent to which price changes influence the demand for both commodities. The results indicate that broiler chicken shows a very strong relationship between price and demand, reflected in an R² value of 0.963. Statistical testing further demonstrates that price has a significant effect on broiler chicken demand (0.018 < 0.05), indicating that its demand is elastic and highly sensitive to price fluctuations. In contrast, native chicken shows an R² value of 0.698 and an insignificant price effect on demand (0.164 > 0.05), suggesting inelastic demand that remains relatively stable despite price changes. These findings reveal that consumers adjust their broiler purchase quantities more quickly in response to price changes, whereas native chicken consumption is more strongly influenced by taste preferences and habitual factors. The study concludes that there is a clear difference in price sensitivity between the two types of chicken. The implications of this research include the need for government price stabilization policies for broiler chicken to maintain household affordability, as well as quality improvement and marketing strategies for native chicken producers to strengthen competitiveness amid changing consumer demand.

The National Food Assistance Program (Non-Cash Food Assistance/BPNT) is one of the social policy instruments designed by the Indonesian government to enhance food security and improve the welfare of poor households. This research aims to analyze the effectiveness of this program by assessing its accessibility, targeting accuracy, commodity quality, and its impact on household expenditure and stability of food consumption.The research methodology uses a descriptive-analytical approach, combining secondary data from official government reports and academic literature with primary data in the form of a limited survey of beneficiaries.The results of the analysis indicate that the program is quite effective in increasing poor households' access to staple foods, primarily through the more transparent and flexible non-cash distribution mechanism. However, several constraints are still found, including inaccurate targeting of beneficiaries, variation in food quality at the e-warung level, and the limited digital literacy of some households.Nevertheless, the program is proven to be able to reduce the burden of food expenditure and improve consumption quality, thereby contributing positively to the welfare of poor households. This research suggests improving the validation of beneficiary data, supervising distribution, and expanding food and digital education for the community to further optimize the program's effectiveness.

Cognitive concentration constitutes a pivotal determinant within the educational process; when an individual exhibits impaired attentional capacity, the instructional input received is unlikely to be effectively encoded into neural pathways or long-term memory, thereby rendering the expenditure of effort, time, and resources essentially futile. This investigation sought to elucidate the associative dynamics among breakfast consumption patterns, levels of physical activity, and sleep quality in relation to academic concentration among students in Grades X and XI within the North Bogor District. Employing a cross-sectional methodological framework, the study encompassed 101 participants whose selection adhered to an observational analytic approach. Empirical data pertaining to breakfast behavior, physical activity, sleep quality, and concentration performance were acquired through standardized self-administered questionnaires. Analytical procedures were conducted using the chi-square statistical test. The inferential findings demonstrated a statistically significant association between breakfast habits (p = 0.002) and sleep quality (p = 0.008) with learning concentration, whereas physical activity exhibited no significant correlation (p = 0.831). Accordingly, the study substantiates that breakfast regularity and sleep quality are meaningfully interrelated with students’ concentration levels, while physical activity does not manifest a measurable relationship with concentration outcomes

This study aims to describe the implementation and outcomes of training on making herbal elixir beverages from nine spice butterfly pea ingredients for exercise mothers as an effort to improve knowledge and skills in processing healthy drinks. The activity was motivated by the limited use of herbal beverages after exercise and the low level of public understanding regarding the benefits of butterfly pea flowers and traditional spices as natural stamina enhancers. The study applied a descriptive qualitative approach through observation and documentation conducted from November 22 to December 5, 2025. A total of 25 exercise mothers participated in the training, which consisted of demonstrations and direct practice in preparing elixirs using dried butterfly pea flowers combined with ginger, turmeric, galangal, lemongrass, cinnamon, cloves, betel leaves, and brown sugar. The results show that participants were able to follow all training stages properly and demonstrated increased understanding of herbal benefits, ingredient functions, dosage accuracy, and processing procedures. Achievement indicators reveal that 92 percent of participants were able to independently prepare the elixir according to the demonstrated steps, 84 percent were able to explain the function of each ingredient correctly, and all groups successfully produced elixir products with color, aroma, and taste that met the expected standards. Participants also responded positively and expressed interest in reapplying the recipes at home and developing flavor variations for personal consumption or small scale business opportunities effectively.

The advancement of information technology has transformed consumption patterns, including shopping activities that have increasingly shifted to digital platforms or e-commerce. Bukalapak, as one of the early players in this industry, is currently facing challenges in the form of declining market share and user complaints related to digital service quality (e-service quality). This research aims to analyze the effect of electronic service quality on consumer loyalty (e-loyalty), with electronic satisfaction (e-satisfaction) as a mediating variable among Bukalapak users in Denpasar City. The sampling technique employed a non-probability sampling method with a purposive sampling approach, and the number of samples was determined based on the number of indicators used. The research findings indicate that electronic service quality has a positive and significant effect on both user satisfaction and user loyalty. Electronic satisfaction is also proven to significantly affect user loyalty and serves as a partial mediator in the relationship between service quality and loyalty. These findings affirm that improving the quality of digital services can enhance customer satisfaction and ultimately build loyalty toward the Bukalapak platform

Sugar consumption in Indonesia remains high, with diabetes affecting 20.4 million people. This condition has prompted the government to introduce an excise policy on Minuman Berpemanis Dalam Kemasan (MBDK) to reduce sugar intake. Social media, particularly the X platform, serves as a medium for the public to express their opinions regarding this policy. This study aims to analyze public sentiment toward the MBDK excise policy using a lexicon-based approach for data labeling and the Multinomial Naive Bayes algorithm with unigram and bigram feature extraction. The initial results show that the highest performance was achieved using 5-Fold Cross Validation, with an average accuracy of 83%, precision of 84%, recall of 75%, and an F1-Score of 77%. After applying data balancing using Stratified Cross Validation combined with Borderline-SMOTE and limiting the features to the 700 most frequent terms, the model’s performance improved. The best results were obtained with 10-Fold Cross Validation, achieving 86% accuracy, 84% precision, 83% recall, and an F1-Score of 83%. These findings indicate that the Multinomial Naive Bayes model can effectively classify public sentiment regarding the MBDK excise policy after the data balancing process.

The International Maritime Organization (IMO), as one of the key organizations contributing to the reduction of carbon emissions in the maritime sector, offers several options that maritime industry stakeholders can utilize to measure carbon emissions, one of which is calculating the Energy Efficiency Operational Indicator (EEOI). The statistical x-bar control chart, employed as a monitoring instrument for the EEOI quality parameter, indicates that one container ship trip recorded an EEOI value of 0.00104, which exceeded the upper control limit of 0.00098. The results of process capability analysis on the initial dataset sample revealed that the value of Cp < 1, indicating that energy efficiency performance was not satisfactory. Process control was subsequently applied by eliminating anomalous data, which demonstrated a potential reduction in fuel consumption and EEOI by approximately 25%, as reflected in the improvement of the Cp value. The potential for enhancing the ship’s operational capability, however, still requires further control measures to improve energy efficiency performance. The reduction in fuel consumption directly contributes to lower emission levels, thereby supporting the realization of a sustainable shipping industry.

Food loss and food waste (FLW) constitute systemic challenges in modern food systems, with direct implications for resource efficiency, environmental sustainability, and food security, particularly in developing countries where horticultural food loss persists upstream while food waste increases in downstream tourism sectors. This review synthesizes literature from 2015 to 2025 on horticultural food loss, tourism-related food waste, and the role of universities in cross-sectoral FLW reduction, using Sembalun, West Nusa Tenggara, as an illustrative agrarian–tourism landscape. The review is based on a multi-database search of academic sources (ScienceDirect/Elsevier, SpringerLink, Wiley Online Library, Taylor & Francis Online, MDPI, and Emerald Insight), complemented by key policy documents from FAO, UNEP, and UNWTO. Thematic synthesis indicates that upstream food loss and downstream food waste reflect structural mismatches between local production systems, tourism consumption patterns, and food governance, and therefore cannot be effectively addressed through isolated sectoral or technical interventions. The review highlights universities as strategic knowledge brokers that facilitate penta-helix collaboration, generate empirical evidence, and support the design of integrated interventions. This study underscores the need to strengthen universities' role in bridging agriculture, tourism, and policy to advance FLW reduction and support sustainable tourism development in rural destinations such as Sembalun, West Nusa Tenggara.