Publication Search

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.

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 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

Introduction: Experiential marketing has become a growing trend in promotional activities by emphasizing personalization and active customer involvement. Preliminary observations indicate a decline in outpatient visits among patients with general insurance and non-JKN coverage in 2023, which may be influenced by a decrease in their intention to use outpatient services. This condition highlights the need for hospitals to implement experiential marketing strategies to enhance patient interest and experience. Objective: This study aims to empirically examine the influence of patient experience and service perception on the intention to use outpatient services, with Strategic Experiential Modules (SEMs) as an intervening variable. Methods: This quantitative research employs a causal design involving outpatient service users as the population. A non-probability sampling technique was used, yielding 249 respondents. Data were collected using a questionnaire and analyzed using Structural Equation Modeling (SEM) with AMOS software. Results: The findings reveal that patient experience and service perception simultaneously have a significant positive influence on the intention to use outpatient services through SEMs. Service perception directly shows a significant positive effect on both SEMs and intention to use outpatient services, while SEMs also significantly enhance usage intention. Service perception emerges as the dominant variable in increasing SEMs and usage intention, whereas patient experience has the weakest effect. Conclusion: Patient experience and service perception collectively influence the intention to use outpatient services with SEMs as an intervening variable. Strengthening Customer Relationship Management is essential by improving human resources and optimizing service asset.

The rapid development of digital technology has significantly transformed commercial activities, particularly through the emergence of marketplaces as platforms for online transactions. The vast number of products available in a marketplace often creates difficulties for users in finding items that suit their needs and preferences. To address this challenge, a recommendation system is required to provide personalized and relevant product suggestions. This study discusses the implementation of a product recommendation system in a marketplace using the Collaborative Filtering method. This method works by leveraging information from users’ previous behavior, such as purchase history, ratings, and similarity of preferences with other users, to generate more accurate product recommendations. The Collaborative Filtering approach has proven effective in identifying user preference patterns based on relationships between users as well as between items. This study employs user interaction data such as ratings and shopping activities as the processing foundation. The process involves data collection, preprocessing, calculation of similarity between users or products, and generating recommendation lists. The results indicate that this method enhances the shopping experience by providing relevant product suggestions tailored to user interests, thereby increasing customer satisfaction and potentially improving sales performance in the marketplace. Thus, the application of a Collaborative Filtering-based recommendation system not only simplifies product discovery for users but also offers strategic advantages for marketplace operators in digital business competition

Artificial Intelligence (AI) has significantly transformed the design industry by introducing innovative tools that enhance efficiency, creativity, and personalization in the design process. This article explores the impact of AI technologies on the practice of modern designers, from the early stages of idea generation to the final execution of projects. By analyzing case studies, conducting surveys, and reviewing recent literature, the study reveals that AI functions not only as a tool but also as a collaborator that expands the boundaries of human creativity. It allows designers to explore new possibilities and push the limits of traditional design processes. However, the integration of AI into design practices also raises important ethical and professional challenges, such as concerns about job displacement, data privacy, and the potential loss of human touch in the creative process. Despite these concerns, the findings highlight that embracing AI is crucial for designers to remain competitive and sustain their careers in the rapidly evolving digital era. Adapting to AI technologies, understanding their capabilities, and effectively incorporating them into creative workflows will enable designers to stay relevant and thrive in a landscape where technology continues to reshape the industry. This study provides insights into the evolving relationship between human designers and AI, offering recommendations for future research and practice in the field of design.

This study discusses the phenomenon of silent lead in digital marketing strategy Amanah Bunda Daycare Semarang. This phenomenon refers to potential customers who have made an initial interaction through WhatsApp Business After seeing Meta Ads ads, but then do not continue communication or convert into customers. The phenomenon of silent leads is an important concern because although the digital marketing process manages to reach the target audience and trigger an initial response, the interaction does not continue until the purchase or registration stage of the service. This study uses a descriptive qualitative approach to explore the characteristics of passive behavior. The Data was collected through in-depth interviews with the internal manager of Amanah Bunda Daycare and five informants identified as silent leads. The results showed that the passive attitude of potential customers is influenced by several main factors, namely the location that is considered less strategic or too far, the perception of prices that are considered high, personal conditions such as changes in plans or time constraints, as well as the quality of customer service communication that is perceived to be less than optimal in providing responses, information, and personal approach. This phenomenon has not been fully accommodated in classic conversion models such as Aida (Attention, Interest, Desire, Action) and model 5A (Aware, Appeal, Ask, Act, Advocate). This shows that there are gaps in marketing communication strategies, especially in managing potential customers who initially respond positively but stop before conversion. Therefore, this study recommends the development of a more empathetic, structured and sustainable approach to communication. Suggested strategies include improving customer service systems based on quick response and personalization, implementing polite but consistent follow-up strategies, and composing marketing content that is able to build trust and emotional connection with potential customers. With these measures, it is expected that silent leads can be minimized and conversion rates increased significantly.

This study examines the role of Artificial Intelligence (AI) in piano education through a qualitative review of six recent academic sources. AI technology has brought about significant transformations in music learning methods, particularly for the piano instrument. Various AI applications such as automated performance feedback systems, musical accompaniment generators, technical error detection devices, and adaptive learning platforms have enabled new approaches to teaching and learning. AI provides instant feedback, tailored exercises to individual abilities, and creates more interactive and flexible learning environments. These innovations are considered to support the development of students' technical skills more effectively, while increasing learning motivation through personalization and ease of access. Furthermore, this study examines the information systems that support these AI applications, including human-computer interaction, audio signal processing, and the use of machine learning models to recognize playing patterns and technical errors. While AI offers significant benefits, concerns arise regarding its limitations in understanding and responding to the emotional aspects of music. AI is not yet capable of fully supporting the development of subjective and complex musical expression. Over-reliance on this technology is also feared to undermine students' critical thinking, artistic sensitivity, and creativity. Therefore, this study emphasizes the importance of a balanced integration between AI technology and human pedagogical roles, with the teacher remaining the primary facilitator in fostering expression, interpretation, and artistic values in piano learning. The study recommends further research on emotionally responsive AI, blended learning models, and long-term evaluation of AI's impact on students' artistic and musical development.

The research examined interactive text as a possible interactive form of pictorial communication for generation z meaningfully engaging on online platforms. By adopting a three-phase methodology towards design, realización and evaluation, the research examines how much movement, responsiveness and user interactivity influences the interpretation of the the communicative message and the emotional. The research uses an interweaving of methodologies. Methodology usability testing, engagement analytics and qualitative indicators, which indicate kinetic text, format variations, and animation responsive were more interesting, easier to understand, and shareable than static texts. Findings suggest participants read as a participant and active, as opposed to passive, which wasn't related to their use of interactions. At last the results deliver positioning for interactive text read as a new thinking strategies for the needs of generation z for authenticity and enable discourse regarding potential opportunities for augmented reality and artificial intelligence-enabled personalization

This study aims to determine the relationship between perfectionism and academic burnout among final-year students in Jakarta. Academic burnout is defined as stress arising from the learning process that results in emotional exhaustion, depersonalization, and low academic performance (Sagita & Meilyawati, 2021). Perfectionism is considered a personality disposition characterized by concerns about self-evaluation, overly critical self-assessment, and striving to achieve perfect personal standards (Hill, 2017). This study employs a quantitative approach, involving final-year university students in Jakarta aged 20–25 years who are in their 7th–9th semesters. The sampling technique used is purposive sampling. The measurement tools used were the Multidimensional Perfectionism Scale developed by Flett and Hewitt (1991) and the School Burnout Inventory developed by Salmela-Aro, Kiuru, Leskinen, and Nurmi in 2009. The results of the correlation test using Pearson Correlation yielded a value of r = 0.854, with significance 0.000 p < 0.05. These results indicate that there is a relationship between perfectionism and academic burnout among final-year students in Jakarta. Based on the correlation test per dimension, the results show that there is a relationship between perfectionism and all dimensions of academic burnout, especially the exhaustion dimension. Additionally, there is a relationship between academic burnout and all dimensions of perfectionism, particularly the socially prescribed perfectionism dimension. This indicates that the higher an individual's level of perfectionism, the higher their level of academic burnout.

The development of information technology has encouraged university libraries to innovate in disseminating information more effectively. Institutional repositories are present as one of the information repackaging products that aim to collect, manage, and disseminate scientific works of academicians in digital form. Repositories can be viewed as valuable assets of an institution that function as a means to improve the reputation of the institution. This study was implemented through a quantitative approach with a descriptive method. This approach was chosen to provide a systematic, factual, and accurate picture of the effectiveness of the directory as an information repackaging product at the Padang State University Library. The results of the study indicate that the use of information repackaging is in the high category in terms of reasons for use, interaction, and results felt by users, although there are still challenges in the completeness and personalization of content. This study recommends the need for continuous evaluation, development of more diverse information formats, and increasing librarian competence in understanding user needs so that the repository can function optimally as a medium for disseminating information and supporting the position of the institution.

This study aims to examine the role of biomechanics in preventing injuries in karate athletes through a systematic review. The research method follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework with a literature search in the Science Direct database, Google Scholar, and the use of tools such as VOSviewer and Publish or Perish. Studies that met the inclusion criteria (10 articles) were analyzed to identify injury patterns, biomechanical factors, and prevention strategies. The results showed that the most common injuries in karate athletes were contusions, calf muscle strains, and finger sprains, which were related to force distribution, extreme joint angles, and postural control. Biomechanical analysis (motion capture, EMG, force plate) proved that technique correction, proprioception training, stabilizing muscle strengthening, and balance training could reduce the risk of injury by up to 20%. Significant differences were found between novice and elite athletes in terms of movement consistency and neuromuscular control. The integration of biomechanical principles with karate philosophy (mushin, zanshin, kime) was also emphasized to maintain a balance between performance and cultural values. Limitations of the study include heterogeneity of measurement instruments and potential publication bias. Future recommendations include longitudinal studies, development of portable devices (IMUs), and personalization of training programs based on individual biomechanical profiles

Digital transformation is one of the essential needs in the development of sharia cooperatives in the Industrial Revolution 4.0 era. Rapidly developing information technology requires microfinance institutions such as cooperatives to adapt, in order to remain competitive, efficient, and relevant in meeting the needs of their members. Two main technologies that play an important role in this transformation are big data and cloud computing. This article aims to examine in depth how the use of big data and cloud computing can support the digital transformation process in sharia cooperatives. Using a literature review approach from various scientific sources, this article analyzes the basic concepts, potential benefits, case studies, and challenges of implementing both technologies in the context of sharia-based cooperatives. The results of the study show that big data can improve data-based decision making, risk management efficiency, and personalization of services to members. Meanwhile, cloud computing provides flexibility, cost efficiency, and accessibility of cooperative information systems widely, even in areas with minimal IT infrastructure. However, the success of implementing this technology is greatly influenced by the readiness of human resources, digital infrastructure, and compliance with sharia principles. This article also provides practical recommendations and a further research agenda as a contribution to the development of technology-based sharia cooperatives.    

This study investigates how artificial intelligence (AI) is transforming Islamic journalism and digital da’wah by analyzing the ethical challenges posed by algorithmically mediated media. Employing a critical-interpretive approach, the research examines how algorithmic logic impacts the production, visibility, and ethical dimensions of Islamic content on platforms such as YouTube and TikTok. The findings reveal a growing tension between Islamic communication principles—sidq (truth), amanah (trust), and hikmah (wisdom)—and the operational values of AI systems that prioritize virality, personalization, and engagement metrics. This paper contributes to global discourse by proposing a hybrid ethical framework that bridges Islamic communication ethics with digital media accountability. It argues for an integrative model where spiritual integrity, transparency, and justice guide the development and use of AI in Islamic media contexts.

The development of artificial intelligence (AI) has significantly changed the digital advertising landscape. However, consumer trust in the use of AI in digital advertising is a crucial issue to understand. This study aims to analyze the influence of perceived intelligence, transparency, and personalization of AI-based advertising on consumer trust levels. Using a quantitative approach through a survey of 500 respondents who are active social media users in Indonesia, the data were analyzed using Structural Equation Modeling (SEM). The results of the study indicate that perceived intelligence and transparency have a significant positive influence on consumer trust, while personalization has a moderate influence. These findings provide theoretical contributions to the digital marketing literature and provide practical guidance for marketers in designing AI-based advertising strategies that are trusted by consumers.

This research presents a personalized, context-aware recommender system to suggest Places of Interest (POIs) using a hybrid approach combining Bayesian inference and collaborative filtering. The system explicitly addresses the cold-start problem that new users face and improves recommendation accuracy by considering contextual variables such as user mood, budget, companion, and location. The system collects real-time contextual inputs for new users with no historical data and applies Bayesian inference to generate relevant POI suggestions. As users begin to interact and provide ratings, the system progressively shifts to a collaborative filtering mechanism, leveraging cosine similarity to identify similar users within comparable contexts. The recommender system focuses on three categories of POIs: restaurants, hotels, and landmarks. These locations are retrieved through the Google Maps API, and only mapped locations are considered. The system was implemented on Android devices and evaluated through a user study involving 25 participants from diverse backgrounds, including software developers, IT students, and general users. Evaluation metrics such as normalized Discounted Cumulative Gain (nDCG) and classification accuracy were used to assess recommendation quality. Results demonstrate that the system performs better than traditional methods, with nDCG improvements reaching up to 83 percent. Users reported high satisfaction regarding the recommendations' accuracy, ease of use, and contextual relevance. While the system offers significant improvements, it also has certain limitations. Its dependency on Google Maps data may restrict its scope, and using only four contextual factors limits the system’s adaptability to more complex user preferences. Future enhancements could include additional dynamic contexts such as weather, POI popularity, and time-related trends, as well as integrating more advanced models to increase personalization and flexibility in real-world applications.

Bouquets have evolved from mere flower arrangements into a work of art that combines elements of aesthetics, creativity, and innovation. This study aims to examine bouquets as an art form by highlighting aesthetic elements, arrangement techniques, and their role in the creative industry. The method used in this study is descriptive qualitative with a literature study approach from various relevant journal references and articles. The results of the study indicate that bouquets not only have aesthetic value but also reflect artistic expression through the selection of colors, shape compositions, and various arrangement techniques. Innovations in making bouquets, such as the use of flannel, snacks, and recycled materials, are expanding the scope of bouquet art in the creative industry. In addition, bouquet art also contributes to the development of the community's economy through increasing business opportunities. Although bouquet art faces challenges such as market competition and fluctuations in raw material prices, its prospects remain promising with the development of technology and product personalization trends. Therefore, continuous innovation is needed so that bouquet art remains relevant and can continue to develop as part of the wider creative industry.

This research aims to analyze the role of Customer Relationship Management (CRM) implementation in increasing customer loyalty in the digital era. With the rapid advancement of technology, CRM has become an essential component of an effective digital marketing strategy. This research uses a qualitative descriptive method with a case study approach involving several companies that use CRM as a strategy to maintain and increase customer loyalty. Data was collected through in-depth interviews, surveys and secondary data analysis from companies using CRM platforms. Research findings reveal that effective CRM implementation—through personalization, regular communication, and leveraging customer data—can significantly increase customer satisfaction and loyalty. Additionally, this research highlights that the use of CRM allows companies to better understand customer needs and preferences, thereby providing more customized services. As a result, implementing CRM in the digital era has proven to be an important strategy for businesses to compete in an increasingly competitive market.  

Optimizing human resources (HR) in digital marketing through the synergy between creativity and technology is an important strategy to create effective and innovative marketing campaigns in the digital era. Creativity plays a crucial role in producing engaging and relevant content, which is able to build an emotional connection with consumers as well as strengthen the brand identity. Meanwhile, technology allows for personalization, data-driven analysis, and efficiency in the implementation of marketing strategies. This study examines how the combination of human resource creativity and the use of digital technology can create a competitive advantage for companies. The results of the study show that companies that successfully integrate these two elements can increase consumer engagement, customer loyalty, as well as the effectiveness of marketing campaigns. From a conceptual perspective, this approach is changing the way companies view innovation and cross-functional collaboration within organizations, which in turn improves responsiveness and adaptability to market changes. The practical implications of this research are the importance of investing in the development of creative and skilled human resources in technology, to create a sustainable digital marketing strategy and be able to compete in an increasingly competitive global market.