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The rapid progress of technology, increasing globalization, and shifting socio-economic conditions pose major challenges for education in the digital age. This study investigates how holistic education fosters competencies aligned with future demands. Utilizing a qualitative method, it conducts a literature review with descriptive analytical techniques. Holistic education plays a crucial role in nurturing creativity, critical thinking, effective communication, and collaboration. It serves as a strategic response to global issues such as technological innovation and fast-paced societal transformations. Beyond equipping students to navigate digital challenges, holistic education also cultivates adaptability, leadership skills, and strong work ethics to handle unexpected changes. More than merely delivering academic content, holistic education aims to build character and prepare future generations to thrive as capable and competitive leaders.

Local fashion brands in Indonesia are gaining popularity due to their affordable prices and competitive quality compared to imported products. One successful example is Arkline, a local fashion brand that effectively uses digital marketing, particularly TikTok, to reach its target market. This study aims to analyze Arkline’s sales growth strategy using a qualitative descriptive approach. Data were collected through digital observations and official online sources. The findings reveal that TikTok is a highly effective platform for engaging Generation Z, who prefer visual, interactive, and authentic content. Arkline’s strategy includes creating trend-based videos, using TikTok Live for real-time interactions, and collaborating with influencers who have large followings. These methods help increase brand awareness, strengthen customer engagement, and drive purchasing decisions. Additionally, the TikTok Shop feature enables seamless in-app transactions, which boosts conversion rates. Overall, TikTok serves as a powerful tool for Arkline to build stronger relationships with consumers, expand its market reach, and stay competitive in the fashion industry. With the right digital marketing strategy and adaptability to current trends, local brands like Arkline can fully leverage TikTok’s potential as an effective platform in today’s digital era.

This study analyzes the effectiveness of competency certification training programs for students of the Faculty of Islamic Economics and Business (FEBI), UIN KHAS Jember, in enhancing their job readiness. Using a qualitative approach and case study design, the research gathered data through interviews, observations, and documentation of training processes and outcomes. The findings reveal that the training significantly improved students' technical skills, self-confidence, and adaptability to workplace dynamics. Moreover, the national certification issued by the National Professional Certification Agency (BNSP) provided added value in terms of industry recognition. The study highlights the strategic role of partnerships with certified training institutions in aligning academic learning with industry demands. It also underscores the need for continuous curriculum updates and institutional support to maximize the training's impact on student career development.

This study aims to analyze the meanings embedded in the Fana Coffee logo using Roland Barthes' semiotic theory. The Fana Coffee logo features visual elements such as a bean sprout, soft typography spelling "Fana", and a dominant green color. The research adopts a descriptive qualitative approach through documentation, observation, interviews, and literature review. The analysis reveals that each element in the logo carries denotative, connotative, and mythological meanings. The green color symbolizes freshness and health, the sprout represents strength, simplicity, and adaptability, while the word “Fana” conveys impermanence and peace, aligning with the cozy ambiance of the coffee shop. Overall, the logo effectively reflects the identity and vision of Fana Coffee as a comfortable, natural, and welcoming place for visitors. This study is expected to provide insights for designers in creating meaningful and brand-relevant logos.

This study analyzes the relationship between intercultural communication competence and cultural empathy in Madura ethnic nomadic students. As a group that often faces challenges in cross-cultural communication, migrant students need to have high adaptability in order to interact effectively in diverse academic and social environments. This study aims to understand how the process of cross-cultural communication can shape the cultural empathy of Madura ethnic nomadic students, as well as how factors such as cross-cultural awareness, ease of perspective, feelings of empathy, and expressions of empathy contribute to their adaptation. This study uses a qualitative approach with an in-depth interview method of Madurese ethnic nomadic students spread across several provinces in Indonesia. The results of the study show that effective cross-cultural communication can help students in adjusting to a new environment, increasing comfort in interacting, and strengthening cultural empathy. Key factors contributing to this process include the ability to understand cultural differences, language skills, as well as a willingness to participate in the local culture.

In Indonesia, housing design policies are increasingly adopting a human-centered approach, recognizing that a home is deeply connected to the preferences of its occupants. These preferences are highly personal and diverse. While housing design is becoming more tailored to the characteristics of residents, few designs take into account the profession of the homeowner as a basis for classification. This research was conducted through direct field observations and interviews with homeowners. It focused on houses owned by individuals from 10 different professional fields in Indonesia. The goal was to explore how different professions influence the design and organization of living spaces. The study revealed that a homeowner's profession significantly impacts home design. Key findings include the addition of specialized rooms based on hobbies or interests, spatial arrangements that reflect the owner’s priorities, and increasing adaptability in design to account for climate change. These observations highlight the importance of considering profession-specific needs in housing design. The results suggest that the existing Indonesian National Standards (SNI) for housing and settlements need to be updated. The current standards focus primarily on minimum space requirements, but they should be expanded to include factors related to the homeowner's profession, which significantly shape the character of the design. Integrating these factors would lead to more personalized, functional, and sustainable housing designs.

Sustainable business transformation has become a cornerstone of modern corporate strategy in addressing environmental, social, and economic challenges. The Sustainability-Led Innovation (SLI) approach provides an innovation framework that embeds sustainability principles into business models, fostering organizational adaptability and long-term value creation. This study aims to (1) identify the mechanisms for integrating SLI into sustainable business models, (2) evaluate SLI’s contribution to competitive advantage, and (3) analyze the development of dynamic capabilities to support sustainability initiatives. By combining the Sustainability-Driven Business Model Innovation (SBMI), Dynamic Capability Theory (DCT), and Triple Bottom Line (TBL) frameworks, this qualitative research utilizes in-depth interviews and document analysis of culinary SMEs in Malang. Findings reveal that organizations adopting SLI achieve higher operational efficiency, respond more agilely to regulatory changes, and attract stronger consumer loyalty. These insights underscore the necessity of embedding sustainable innovation strategies into long-term business planning to secure resilient competitive advantage.

This community service activity was carried out to improve the psychosocial capacity of Indonesian Migrant Workers (PMI) in Taiwan through online education that focuses on work stress management, adaptability, and achievement motivation. The activity was carried out in collaboration with the GANAS Community Taiwan and was attended by 35 participants who are members of the community. The implementation was carried out online using Zoom Meeting, with three webinar sessions, each discussing one main topic. Evaluation was carried out to measure the increase in participants' understanding of the material presented. The results of the activity showed a fairly good increase in understanding for the topics of stress management, work adaptation, and achievement motivation. Participants also provided positive feedback on the delivery method and the relevance of the material to the situations they experienced. This activity shows that a webinar-based educational approach can be an effective strategy in increasing PMI's knowledge and awareness of the psychosocial issues they face in the country of placement. Follow-up in the form of similar activities periodically is needed to strengthen the impact and reach more migrant worker communities in the future.

In the context of Indonesian culture, living with parents or in-laws is quite common, especially for young couples who are not yet financially independent. However, dynamics in the household such as differences in values, habits, and privacy boundaries often pose psychological challenges for wives. This study aims to describe the psychological well-being of wives who live with their in-laws after marriage. This study uses a qualitative approach with an in-depth interview method with one of the informants who meets the criteria, namely women who have been married and have lived with their in-laws for at least one year. The results of the study indicate that there are various aspects of psychological well-being that are influenced by the condition of living with in-laws, including self-acceptance, autonomy, positive relationships with others, and mastery of the environment. Factors such as partner support, open communication, and adaptability are the main determinants in maintaining the psychological well-being of wives in this situation. This study is expected to provide insight for young couples and families in building harmonious relationships in a household involving more than one generation..

Entrepreneurship plays a significant role in global economic growth. However, not all entrepreneurs achieve success. This study aims to deeply examine the mindset and character that serve as the fundamental basis for entrepreneurial success, as well as the influencing factors and strategies for fostering these qualities based on a literature review. Through a literature review method, it was found that successful entrepreneurs possess a growth mindset, are solution-oriented, and adaptive, supported by specific thinking methods like BETSCA (Bricolage, Effectuation, Think Structurally, Cognitive Adaptability). Furthermore, key characters such as commitment, creativity, resilience, risk-taking propensity, and networking ability are crucial elements. The study also identified various driving factors and types of motivation (intrinsic-extrinsic) in entrepreneurship. Another important finding is that the entrepreneurial spirit and character can be learned and developed through personal commitment, a supportive environment, education, and continuous learning processes. The conclusion of this study asserts that the combination of the right mindset and strong character, along with the ability to continuously develop both, is essential for increasing the chances of success in the world of entrepreneurship.

This research uses a qualitative method to explore the integration of Artificial Intelligence (AI) in marketing tactics and its impact on the development of marketing skills among the new generation. The main focus is on the use of AI in analyzing consumer behavior, content personalization, campaign automation, and data-driven decision-making. The findings reveal that AI not only enhances operational efficiency but also drives a transformation in the skill sets required by modern marketers, such as data analysis capabilities, technological literacy, and adaptability to intelligent systems. Through in-depth interviews with marketing practitioners and digital document analysis, it was discovered that the new generation of marketers is required to develop more complex digital competencies and engage in multidisciplinary collaboration. Furthermore, adaptation to technological change becomes a key factor in the success of AI-based marketing strategies. The integration of artificial intelligence in marketing practices not only reshapes work patterns but also creates new demands for continuous training and marketing education. Therefore, this research emphasizes the importance of collaboration between educational institutions, industry, and technology developers to create a competitive AI-based marketing ecosystem.

Organizational culture is a collection of values, rules, and beliefs held by members of an organization, influencing the way they think and act in achieving goals. This study aims to describe the basic concepts, roles, impacts, and challenges in implementing organizational culture in educational institutions. The type of research is a literature study. Data were collected from accredited national books and journals using Google Scholar and PoP, with an analysis of 15 articles filtered into 5 main articles. The results of this study (1) Organizational culture in educational institutions contributes to creating a conducive work environment, increasing the professionalism of educators, and strengthening work discipline, (2) A strong culture can improve performance, collaboration, and adaptability, while a culture that is not in line with the vision and mission can cause disorientation and (3) Challenges in implementing organizational culture include resistance to change, understanding organizational values, differences in understanding between members and technological adaptability.

With 65 million entities, micro, small, and medium enterprises (MSMEs) form the backbone of the Indonesian economy, contributing around 61% of the country's gross domestic product (GDP) and employing 97% of the working population. Despite their strategic role, most MSMEs still face various challenges, such as low adaptability to changes in the business environment, lack of planning strategies, minimal innovation, and limitations in utilizing technology. On the other hand, current consumer behavior increasingly demands quality products and practical services, including in terms of payment systems. Along with the development of the digital era, non-cash payment systems, such as e-money and QR codes, have experienced rapid growth and become important elements in encouraging financial inclusion and transaction efficiency. QRIS (Quick Response Code Indonesian Standard) is present as an innovative solution that allows MSMEs to make transactions quickly, safely, and easily by simply scanning a QR code. Realizing the importance of utilizing this technology, the community service (PkM) team conducted training activities on the creation and use of QRIS for the "Zea Ice" Orange Juice micro business actor in Deltasari Indah, Sidoarjo, East Java. This activity includes QR code creation, printing, and attaching barcodes to kiosks, as well as technical education related to their use. This initiative is expected to increase transaction efficiency, encourage the implementation of digitalization, and increase the competitiveness of MSMEs in an increasingly competitive market.

This study examines the adaptive strategies employed by small and medium-sized enterprises (SMEs) in Shenzhen in response to the decoupling trend associated with the new US tariff policy. Given the' increasing complexity and unpredictability of international trade dynamics, Shenzhen SMEs must innovate and diversify their operational approaches to sustain competitiveness. The re-search highlights the significance of enhancing innovation capabilities, which enable SMEs to de-velop new products and services that meet shifting market demands. Additionally, the study empha-sizes the importance of market diversification and supply chain flexibility, allowing SMEs to miti-gate risks related to tariff impacts. Collaborative networks facilitate resource sharing and knowledge exchange, further bolstering adaptability. The findings indicate that by fostering a proactive entre-preneurial orientation and engaging with policymakers, Shenzhen SMEs can effectively navigate the challenges posed by the US tariff policy, ensuring long-term sustainability and growth in a competi-tive landscape through a sample of 190 SMEs in April of 2025.

The integration of solar powered IoT irrigation systems in precision agriculture offers a sustainable solution to address water scarcity and enhance crop productivity. By leveraging real time data from soil sensors, weather APIs, and machine learning algorithms, these systems optimize irrigation schedules and improve water use efficiency. This research explores the potential of integrating renewable energy sources, such as solar power, with edge computing in smart irrigation systems to promote sustainable agricultural practices. The study aims to evaluate the performance of the proposed system in terms of water savings, crop yield, energy efficiency, and adaptability to varying climate conditions. Literature Review: Previous studies highlight the importance of smart irrigation systems in reducing water waste and improving crop yield through real time monitoring and automated decision making. However, existing systems often lack the integration of renewable energy and edge computing, which are critical for ensuring sustainability and operational efficiency in rural agricultural settings. The combination of renewable energy with IoT devices offers a promising solution to reduce energy costs and carbon emissions, while edge computing enhances real time data processing, ensuring prompt and accurate irrigation adjustments. Materials and Method: The proposed system integrates solar powered IoT devices, soil moisture sensors, weather data APIs, and edge computing devices to manage irrigation. Machine learning algorithms and evapotranspiration models are used to predict irrigation needs and optimize scheduling based on real time data. The system's performance is evaluated through metrics such as water savings percentage, crop yield improvements, and energy consumption, with a comparative analysis against traditional irrigation methods. Results and Discussion: The results indicate that the system successfully reduces water usage by 30% to 40%, increases crop yield by 25%, and operates with energy autonomy, powered entirely by solar energy. The system's adaptability to varying climate conditions ensures optimal crop growth, even under environmental stresses. The integration of renewable energy and edge computing significantly enhances the sustainability and efficiency of irrigation systems.

Introduction: The integration of Digital Twin (DT) technology and the Internet of Things (IoT) into Building Energy Management Systems (BEMS) offers a transformative approach to optimizing energy consumption in buildings. This study explores the development of a Digital Twin based BEMS prototype, which leverages real time data collection, predictive analytics, and machine learning to enhance energy efficiency, reduce costs, and support sustainability goals in modern buildings. The research also addresses key gaps in current energy management systems, including real time adaptive control and integration with smart grid platforms. Literature Review: Previous research highlights the limitations of traditional BEMS, which often rely on static control strategies and lack real time adaptability. Recent advancements, including predictive maintenance and machine learning integration, have improved energy optimization. However, challenges such as data interoperability, scalability, and cybersecurity remain. This review consolidates current approaches and identifies opportunities for enhancing BEMS through the integration of DT technology, IoT, and machine learning. Materials and Method: The methodology employed involves the design of a Digital Twin based BEMS prototype, incorporating IoT sensors for real time data collection on variables such as HVAC load, occupancy, and environmental factors. The system uses time series forecasting and adaptive control strategies to optimize energy consumption. A case study building is used for validation, with performance metrics such as energy savings, CO₂ footprint reduction, and peak load reduction assessed to evaluate the system's effectiveness. Results and Discussion: The results demonstrate a significant reduction in energy consumption (up to 50%) compared to traditional BEMS, along with improved forecasting accuracy and sustainability performance. The prototype achieved a high R² score in predicting energy usage, validated through real world application in the case study building. The economic feasibility analysis showed substantial cost savings and a strong return on investment, making the system a financially viable solution for energy efficient building management.

Introduction: Achieving carbon neutrality in industrial systems is essential for mitigating climate change and promoting sustainability. The increasing demand for energy optimization and carbon emission reduction has driven the development of advanced technologies, particularly hybrid machine learning (ML) models. These models, combining ensemble learning and reinforcement learning (RL), offer significant promise in optimizing industrial processes, reducing energy consumption, and improving environmental performance. This study explores the application of hybrid ML models in achieving carbon neutral goals through dynamic process optimization and energy control in industrial settings. Literature Review: Hybrid ML models integrate different machine learning techniques to handle complex and dynamic environments effectively. Ensemble learning methods, such as boosting, bagging, and stacking, combine multiple algorithms to improve predictive performance and robustness. Reinforcement learning (RL), on the other hand, enables real time decision making and adaptation based on trial and error interactions with the environment. In energy optimization, these models are used to reduce energy intensity and carbon emissions, enhancing overall operational efficiency. Previous studies have demonstrated the effectiveness of ML models in energy management, but challenges such as data quality, model integration, and computational complexity remain. Materials and Method: The study applies hybrid ML models combining ensemble learning and RL to optimize energy consumption and minimize carbon emissions in industrial processes. Data from real time sensors and operational parameters are used to train the models. The ensemble learning component improves the accuracy of energy predictions, while RL ensures dynamic process adjustments in response to fluctuating energy demand. The models were tested in various industrial settings, including manufacturing processes, smart grids, and microgrid systems. Performance metrics such as energy efficiency, carbon emissions reduction, and operational costs were evaluated to assess the effectiveness of the models.  Results and Discussion: The hybrid ML models achieved significant reductions in energy intensity (15-20%) and carbon emissions (18-25%). The real time adaptability of the RL component allowed the models to adjust energy consumption patterns dynamically, improving energy efficiency and reducing waste. The models demonstrated their ability to adapt to varying operational conditions, ensuring optimal energy use. A cost-benefit analysis showed that the hybrid models provided substantial energy savings and reduced operational costs, with a return on investment (ROI) of 30-35% within the first year of deployment. However, challenges such as computational complexity and data quality issues were identified, highlighting the need for further refinement in model development.

This study aims to examine the application of situational leadership theory by the principal of SMP Negeri 2 Sampanahan, Kotabaru Regency, and its impact on organizational behavior within the school environment. A qualitative approach with a case study method was employed, involving in-depth interviews with the principal, teachers, and students. The main focus of the research is to understand how the principal adapts leadership styles according to the needs and conditions of the individuals being led. The findings reveal that the principal successfully applied various leadership styles—ranging from directive, supportive, participative, to delegative—flexibly based on the specific situations encountered. This adaptability positively influenced the organizational climate, fostered harmonious working relationships, and enhanced the motivation and active participation of both teachers and students. The school environment became more conducive and collaborative, ultimately leading to overall performance improvement. These findings highlight the importance of adaptive leadership in education to support the achievement of organizational goals and the development of human resources within schools. This study contributes to the development of leadership practices in educational settings, particularly in the context of educational management that is responsive to both internal and external institutional dynamics.

Social competence is the ability of teachers to communicate and interact with students during the learning process. This competence is very important so that teachers can be good examples for students, help students develop individuals who are full of empathy, attention, and concern for others. This study aims to assess in detail the influence of social competence possessed by classroom teachers. This study uses a qualitative approach. The main subjects of the study, namely teachers and supporting objects, namely students. Data collection techniques through observation, interviews, and documentation. Data were analyzed using Miles and Huberman's theory, including data reduction, data presentation, and drawing conclusions. The results of the study showed that teacher social competence, including inclusive attitudes, polite communication, adaptability, and communication with the professional community, had a positive effect on the learning process. Teachers who are effective in social competence create a pleasant learning atmosphere, increase comfort, motivation, and student learning achievement. This study concludes the importance of strengthening social competence in improving the quality of the learning process in the classroom.

This qualitative study aims to gain insights into how English lecturers perceive and integrate generative Artificial Intelligence (AI) in their teaching, an increasingly relevant topic in education. Guided by the Technology Acceptance Model (TAM), the research involved two lecturers from a higher education context. Findings reveal a shift in perception: although both participants were initially reluctant due to unfamiliarity and concerns about learning quality, they gradually embraced AI after firsthand experience. They now recognize its potential to support teaching while maintaining careful oversight to ensure it does not compromise the learning process. Their evolving views highlight the importance of adaptability and critical awareness in incorporating AI into English language education.