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The presence of Generation Z, who grew up entirely in the digital era, has triggered a fundamental transformation in Muslim religious practices, where social media has replaced conventional religious institutions as the primary source of religious information. This condition creates a paradox: Gen Z has become a generation that is highly religious online, yet is often disconnected from physical communities and traditional religious authorities. This study aims to analyze the character of Muslim Gen Z religiosity, identify its forming factors, and examine the impact of the digital era on their religiosity. This study employed a descriptive qualitative approach using a library research method. The findings indicate that Muslim Gen Z religiosity is characterized by personalization, flexibility, and digital spirituality, strongly influenced by social media. These characteristics are shaped by massive digital technology accessibility, the effectiveness of contextual Islamic preaching on platforms such as TikTok, as well as spiritual needs and social pressure from the digital environment. The digital era brings positive impacts in the form of increased accessibility and religious literacy, but also negative impacts including shallow religious understanding, vulnerability to information bias, and potential exposure to extreme ideologies. This study implies the importance of an integrated digital religious literacy strategy through critical thinking-based Islamic Religious Education curriculum reform, enhancement of educators' digital capacity, and cross-sector collaboration to strengthen Gen Z's moderate and reflective religious understanding.

This study aims to develop a financial saving application to improve the saving habits of students, particularly in Islamic boarding schools, through an adaptive challenge approach. The system integrates a mobile iOS application with a backend service and Large Language Model (LLM) processing via Ollama. Transaction data entered by users is processed by the backend to generate contextual and personalized saving challenges, applying Reinforcement Learning concepts in an adaptive and data-driven manner. The research adopts a descriptive quantitative method using surveys and system testing with 50 respondents. Results indicate that the application functions as designed, with no significant bugs detected. User evaluation shows high satisfaction, with an average score of 4.3 out of 5, covering ease of use, interface design, and increased awareness of saving. The combination of gamification, reward systems, and adaptive personalization successfully motivates users to save regularly. This system demonstrates the potential of integrating AI-driven personalization to strengthen financial literacy and healthy financial habits among students in a fun and interactive way.methods, and a summary of the results. The abstract should end with a comment about the significance of the results or conclusions brief.

The rapid growth of digital commerce has encouraged companies to integrate digital and physical marketing channels to create seamless and consistent customer experiences. This study aims to analyze the role of integrated marketing channels through omnichannel strategies, the utilization of Artificial intelligence (AI), and their impact on customer experience in the context of digital commerce. The study employs a Systematic literature review (SLR) approach by examining relevant scholarly articles related to omnichannel marketing, AI technologies, and customer experience. The findings indicate that integrated marketing channels supported by AI enhance service personalization, customer engagement, operational efficiency, and the quality of interactions between companies and customers. Furthermore, the implementation of omnichannel strategies contributes to higher customer satisfaction and loyalty by providing a more connected experience across multiple customer touchpoints. However, the implementation of integrated marketing channels still faces several challenges, including fragmented channel integration, technological complexity, high investment requirements, and concerns regarding customer data privacy and security. Therefore, effective management of integrated marketing channels is essential for improving customer experience while creating sustainable competitive advantages for companies in an increasingly dynamic digital era.

This study aims to examine the role of customer trust as a mediating variable in the relationship between digital marketing strategies and consumer behavior. As digital marketing evolves, companies are required not only to create engaging content but also to build strong trust to influence purchase intention, loyalty, and customer engagement. This research employs a systematic literature review (SLR) following PRISMA guidelines, selecting 52 empirical articles from reputable international databases such as Scopus, Web of Science, EBSCOhost, and ScienceDirect, published between 2015 and 2026. The analysis involved thematic and descriptive synthesis to assess the strength of digital marketing’s impact on customer trust and consumer behavior outcomes. The results indicate that digital marketing has a significant positive effect on customer trust formation (β=0.652; p<0.001). Customer trust functions as a partial mediator that strengthens the impact of digital marketing on purchase intention, loyalty, and engagement. The direct effect of digital marketing on consumer behavior is weaker when trust is not optimally established. These findings emphasize that effective digital marketing strategies must focus on transparency, security, credibility, and personalization to maximize consumer behavior outcomes. Practically, this study provides important implications for companies and digital marketing practitioners, highlighting that successful campaigns rely not only on content and visibility but also on the ability to build customer trust. The study also opens avenues for future research to examine more specific trust dimensions, including platform integrity, information quality, and social proof, within increasingly complex digital marketing contexts.

This study aims to analyze the effect of personalized marketing on customer satisfaction and customer retention, as well as to explain the role of customer satisfaction as a mechanism linking marketing personalization to customers’ decision to remain with a brand. The background of this study is based on the increasing use of data-driven marketing strategies, product recommendations, personalized promotions, and digital communication tailored to customer preferences. In an increasingly competitive business environment, companies are required not only to attract new customers but also to retain existing customers through relevant, convenient, and valuable experiences. This study employed a quantitative explanatory approach, with the population consisting of customers who had received personalized marketing from a particular company or brand. The sampling technique used was purposive sampling, with the criteria that respondents had received personalized promotions and had made repeat purchases. The total sample consisted of 110 respondents. Data were collected using a structured questionnaire with a five-point Likert scale and analyzed using Partial Least Squares Structural Equation Modeling. The findings show that personalized marketing has a positive and significant effect on customer satisfaction. This indicates that promotions, recommendations, and marketing messages that are relevant to customer needs can create more positive customer experiences. Customer satisfaction is also found to have a positive and significant effect on customer retention, meaning that satisfied customers are more likely to make repeat purchases, continue using products or services, and avoid switching to competitors. In addition, personalized marketing has a direct effect on customer retention, although its effect becomes stronger when mediated by customer satisfaction. The implications of this study emphasize that companies need to develop personalization strategies that are not only data-driven but also relevant, ethical, non-intrusive, and oriented toward customer value. Therefore, personalized marketing can serve as an important strategy for improving customer satisfaction and maintaining long-term customer retention.

Digital transformation has positioned artificial intelligence (AI) as a major driver of organizational change and innovation. This study aims to analyze the influence of AI implementation on transformational leadership dynamics and the shifting role of leaders in managing human resources through a Systematic Literature Review of reputable studies published within the last five years. The findings indicate that AI acts as a catalyst in strengthening the dimensions of intellectual stimulation and individualized consideration through predictive analytics and talent personalization. The automation of administrative and repetitive tasks enables leaders to focus more on strategic vision, organizational innovation, decision-making, and emotional engagement with employees. However, the effectiveness of AI implementation is highly dependent on leaders’ digital literacy, adaptive capabilities, and readiness to integrate technology into organizational processes. This study contributes by proposing a hybrid leadership framework that combines artificial intelligence with human emotional intelligence to support more effective leadership practices. The practical implications emphasize the importance of leadership development that prioritizes empathy, ethical awareness, and algorithmic transparency in order to maintain trust, encourage sustainable innovation, and strengthen organizational resilience in increasingly dynamic and volatile environments.

Algorithmic technologies are widely used in contemporary marketing strategies due to the growth of the digital economy. Digital companies can evaluate consumer activity data in real time and provide highly personalized digital experiences thanks to artificial intelligence-based solutions, especially machine learning. In addition to examining how algorithmic governance and surveillance capitalism affect algorithmic personalization, this study looks into how these mechanisms affect consumer engagement, purchase intention, and perceptions of hyperreality within the digital market ecosystem. 356 active users of digital platforms, such as social media and e-commerce, were surveyed as part of this study's quantitative methodology. The links between the constructs in the suggested conceptual model were examined through data analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that the development of algorithmic personalization systems is strongly influenced by data-driven capitalism practices and algorithmic governance. Additionally, it has been demonstrated that algorithmic personalization improves customers' sense of hyperreality and increases their interaction with digital platforms. Additionally, the study shows that the most powerful factor influencing purchase intention is consumer interaction. By combining viewpoints from technology, the political economics of data, and hyperreality theory into a thorough empirical framework, these findings add to the body of knowledge on digital marketing.

This study aims to analyze the marketing strategies of maternal and child healthcare services in hospitals to enhance patient experience, emphasizing a shift from traditional promotional approaches toward the creation of a positive and empathetic patient experience. This research employs a systematic literature review of relevant studies published between 2021 and 2025, with analysis conducted through identification, selection, and thematic synthesis to determine key factors influencing patient satisfaction and loyalty. The findings indicate that the quality of interpersonal interactions and the efficiency of service processes are the primary determinants of patient experience, where factors such as staff empathy, clear communication, reduced waiting times, and well-structured service flows have a greater impact than the technical aspects of medical care. Hospitals should therefore prioritize people- and process-oriented strategies by implementing empathy training, enhancing communication effectiveness, and regularly measuring patient satisfaction, while also integrating digital services, ensuring cost transparency, and developing continuity of care programs to strengthen the patient experience holistically. This study proposes a holistic marketing framework that integrates empathy, efficiency, data-driven personalization, and environmental sustainability, highlighting a shift from a purely clinical orientation to an experiential marketing approach that places human values at the core of a hospital’s competitive advantage.

This study aims to analyze the implementation of Artificial Intelligence (AI)-based learning media and its implications for student learning motivation in Islamic Religious Education (PAI). This study uses a systematic literature review approach by examining various reputable scientific articles discussing the integration of AI in education and the dynamics of learning motivation in the context of PAI. The results of the study indicate that the use of AI through adaptive learning systems, educational chatbots, gamification, and learning analytics can increase the effectiveness, personalization, and interactivity of learning. This implementation has a positive impact on cognitive motivation through increased conceptual understanding, affective motivation through active participation and emotional engagement, and spiritual motivation through strengthening reflection and internalization of Islamic values. However, ethical challenges, the risk of depersonalization of the teacher's role, and inequality in digital access are crucial issues that require policy attention and human-centered pedagogical design. Theoretically, this study offers an integrative conceptual framework that combines technological innovation with Islamic educational epistemology. Practically, the results of this study provide recommendations for teachers, schools, and policymakers to develop AI-based PAI learning models that are adaptive, ethical, and oriented towards character building.

Dementia is a progressive neurocognitive disorder often accompanied by behavioral and psychological symptoms such as agitation, anxiety, and depression. Pharmacological treatments provide only modest benefits while introducing significant risks, which highlights the need for safer, non-pharmacological alternatives. This literature review examines the role of virtual reality in dementia care, with a focus on its integration with therapies such as music, reminiscence, sensory stimulation, and cognitive training. Evidence from prior research suggests that virtual reality can enhance cognitive functions, reduce symptoms, and improve emotional well-being while also strengthening patient–caregiver interaction. However, challenges related to usability, accessibility, cost, and long-term effectiveness continue to limit adoption. Gaps in research, including limited cultural diversity, inconsistent reporting of intervention design, and a lack of large-scale longitudinal trials, emphasize the need for future work exploring cross-cultural feasibility and AI-driven personalization. Overall, virtual reality represents a promising and evolving non-pharmacological intervention that has the potential to transform dementia care by improving quality of life and reducing reliance on medication.

This meta-analysis assesses the effectiveness of mobile health (mHealth) applications in trauma management in the Middle East region, based on a systematic review of 47 empirical studies with a total of 12,486 participants published between 2015 and 2024. The quantitative synthesis results indicate that implementing mHealth has a statistically significant impact on improving trauma management, with a strong pooled effect size (g=0.78, 95% CI [0.65, 0.91], p<.001). Subgroup analyses reveal that the highest effectiveness is observed in interventions targeting Post-Traumatic Stress Disorder (PTSD) (g=0.86), followed by physical trauma management (g=0.74) and general psychological trauma (g=0.69). Further meta-regression findings identify the duration of application use (β=0.42, p<.001) and the level of intervention personalization (β=0.38, p<.01) as significant moderators influencing the magnitude of intervention effects. From an implementation perspective, user engagement reached 76.4%, and the retention rate was 68.2% after 6 months of use. Clinical outcome analyses demonstrate a significant reduction in PTSD scores with a mean difference of -14.6 points (p<.001) as well as a substantial improvement in quality of life (d=0.82). Comparatively, these findings extend the results of Goreis et al. (2020) and Kayrouz et al. (2018) by delineating more specifically the effectiveness of interventions in Middle Eastern populations. However, they differ from Yeager and Benight (2018) regarding the optimal duration of use. The principal contribution of this study lies in elucidating the central role of cultural adaptation, which shows a strong correlation with the effectiveness of mHealth applications (r=0.56, p<.001) in the context of trauma management in the Middle East.

This Community Service Activity (PKM) aims to strengthen interpersonal communication strategies in increasing donor trust in the Grandma Foundation as a social institution engaged in elderly services. The main problems identified include communication patterns that are not systematic, lack of personalization, and lack of transparency of information, so that it has an impact on the level of trust and loyalty of donors. Through a qualitative-educational-participatory approach, PKM activities are carried out through the delivery of effective communication materials, interpersonal communication simulations, the preparation of donor communication flow standards, and assistance in digital communication practices based on social media and instant messaging. The results of the activity showed a significant increase in the attitude and communication skills of the management, the formation of donor communication operational standards, the improvement of digital communication skills, and the positive response from donors which was reflected in the increase in interaction and trust. These findings confirm that interpersonal communication based on empathy, transparency, and consistency plays an important role in building long-term relationships with donors. Thus, a structured interpersonal communication strategy can be an effective model for philanthropic institutions in managing donor relationships and maintaining the sustainability of social programs.

The transformation of political communication in the digital era has fundamentally altered the ways political parties and their affiliated wing organizations interact with party cadres and the broader public. In Indonesia, party wing organizations such as Angkatan Muda Pembaharuan Indonesia (AMPI), Angkatan Muda Partai Golkar (AMPG), and other youth wings increasingly rely on social media as the primary medium for political cadre formation. However, this shift has not only created new opportunities for participation but has also generated structural problems, including the dominance of symbolic communication, the personalization of political elites, and the subordination of ideological discourse to the algorithmic logic of digital platforms. This article aims to critically examine how the digital political communication of party wing organizations operates within the context of Indonesia’s representative democracy, the extent to which it constitutes a deliberative public sphere for young cadres, and how such practices affect the quality of political cadre formation. Employing a critical paradigm and a transdisciplinary qualitative approach, the study integrates Habermas’s theory of the public sphere, Aeron Davis’s evaluation of democratic communication, and the concept of the mediatization of politics. The findings indicate that the digital communication of party wings tends to function primarily as an instrument of symbolic consolidation and loyalty mobilization rather than as an arena for dialogical political education. Consequently, digital cadre formation produces representational identities more than critical political consciousness. This article therefore recommends a reorientation of the digital political communication of party wing organizations toward deliberative and emancipatory models in order to strengthen internal party democracy and promote substantive political regeneration.

The development of artificial intelligence technology is a great opportunity for the fashion industry, especially in designers based on personalization and consumer needs. This study aims to examine Midjourney's AI technology in the design personalization process by integrating solid data and consumer style preferences. This research is expected to support the concept of mass customization in the fashion industry and increase the relevance of design to user character. This research uses a mixed method method by combining quantitative data and qualitative data. The research stages include body data collection and style preferences, prompt formulation, data-driven prompt formulation, design generation using Midjourney, design validation by experts and consumers, and integrated data analysis.The results showed that the majority of the designs produced were considered feasible in terms of construction (83%) and in accordance with the character of the consumer's body (75%). The modest and minimalist style categories received the highest personalization scores. The qualitative findings reinforce the quantitative results, showing that consumers feel the fit of the style and proportions of the design with the character of their bodies.The study concludes that Midjourney's AI integration in the fashion design process is able to effectively support design personalization, although it still requires the role of designers in technical refinement. This approach has the potential to be an innovative solution in the development of data-driven fashion design.

This research aims to critically examine the ethical integration of artificial intelligence (AI) in education through the perspective of maqāṣid al-sharīʿah, emphasizing the alignment between technological innovation and Islamic moral principles. The methods used are a systematic literature review and thematic content analysis against peer-reviewed publications for the period 2015–2025, which discuss the application of AI in primary, secondary, and higher education. The study identified dominant ethical issues, such as data privacy, algorithmic bias, accountability, human agency, and moral development, which were then mapped to Islamic ethical goals, including ʿadl (justice), amānah (belief), karāmah al-insān (human dignity), and ḥifẓ al-ʿaql (protection of reason). The results of the analysis show that the adoption of AI in education often emphasizes efficiency, personalization, and predictive analytics, but has the potential to reduce learners' autonomy and ethical reasoning. The mapping of maqāṣid al-sharīʿah shows a strong normative conformity, so that Islamic principles can be a moral foundation as well as a practical guide for AI governance. The research contribution is theoretical by bridging the literature on AI ethics and Islamic educational philosophy, as well as practical by offering an integrative framework for AI policymakers, educators, and developers. The integration of maqāṣid al-sharīʿah in AI governance ensures justice, trust, inclusivity, and the development of the whole human being (insān kāmil).

The development of artificial intelligence has revolutionized higher education by increasing the efficiency and personalization of learning, but it has also posed a major challenge in the form of a decline in students' critical thinking skills due to their dependence on technology. Therefore, an in-depth philosophical study through the post-positivism, critical theory, and constructivism paradigms is needed to understand its impact on cognitive and epistemological processes. This study aims to analyze how these three paradigms guide the development of critical thinking in the context of AI. It uses a descriptive-analytical method based on secondary data from academic literature such as journals and books that have been critically synthesized. The findings show that post-positivism views AI as a tentative critical realism tool for empirical verification. Critical theory critiques power relations, ideology, and the ethics of technological domination. Constructivism emphasizes the construction of social knowledge through human-centered design that supports creativity and collaboration. The positive impacts of AI include instant feedback and content adaptation, while the negative impacts include social isolation, weak digital literacy, and data privacy. Therefore, the implication is the wise use of AI with the assistance of teaching staff to strengthen reflective analysis, ethical literacy, and paradigm adjustments in accordance with the exact or social sciences to create multidimensional learning in the digital era.

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

This study aims to analyze user sentiment toward the integration of Artificial Intelligence (AI) in online learning platforms, which are increasingly expanding in the digital era. With the growing use of AI technologies in education—such as learning chatbots, material recommendation systems, and automated assessments—it is essential to understand users’ perceptions and reactions to these implementations. The research employs sentiment analysis based on text mining using user review data collected from various online learning platforms. The analysis process includes data preprocessing, sentiment classification using machine learning algorithms, and interpretation of results based on the proportion of positive, negative, and neutral sentiments. The findings indicate that most users express positive sentiments toward AI integration, as it enhances learning efficiency and personalization. However, some users raise concerns regarding data privacy and the lack of human interaction. This study is expected to serve as a reference for educational platform developers to design AI systems that are more adaptive, transparent, and user-centered

Implementation Artificial Intelligence as a supporting model for e-learning still faces several challenges. This is due to several aspects, such as concerns about loss spiritual touch, low digital literacy educators, limited technological infrastructure in educational institutions, and so on. On the other hand, the interaction that occurs between students and teachers is an emotional and moral dimension that occurs. The purpose study is to analyze the use AI as supporting model for e-learning in Islamic education. In this study, the method used is descriptive qualitative research. The findings study are (1) Views Islamic education practitioners on Artificial Intelligence, one which is that the existence Artificial Intelligence is not absolute replacement between students and teachers. However, Artificial Intelligence is considered means or tool in understanding learning; (2) The results  analysis explain that several AI (Artificial Intelligence) in e-learning in Islamic education have been present in several forms, including increasing access and inclusivity, translating and understanding classical manuscripts, analyzing learning and automatic assessment, material recommendation systems and learning personalization, as well Chatbots and virtual learning assistants; (3) Concept Islamic education is not only oriented towards the transfer knowledge (ta'lim), but also the formation of morals and spirituality (tarbiyah and ta'dib).

The development of the digital economy has driven major changes in consumer behavior, from traditional transactions to online interactions. These changes present both challenges and opportunities for businesses, particularly in the e-commerce sector, where consumer trust, data privacy, and digital technology adoption are important factors in decision-making. This study aims to map global trends in online consumer behavior research in the context of the digital economy using bibliometric analysis. Data was collected from the Scopus database using the keyword “online consumer behavior” for the period 2020-2025. The dataset was exported in CSV format and analyzed using VOSviewer and R Studio (Biblioshiny). The analysis included annual publication trends, identification of authors, journals, countries, as well as keyword mapping and citation networks. The results show a significant increase in publications after 2020, with China, the United States, and India as the main contributors. Keyword mapping reveals four research clusters: consumer trust and data privacy, e-commerce and digital platform adoption, consumer experience and personalization, and social commerce and social media influence. These findings confirm a growing research focus on issues of digital trust and opportunities for utilizing new technologies such as artificial intelligence and social media. This study provides a comprehensive overview of global trends in online consumer behavior and an important contribution to academics, practitioners, and policymakers.