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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 examines customer churn prediction in subscription-based telecommunications from a digital marketing perspective using machine learning. The analysis utilizes a secondary dataset of 7,043 customer records that simulate behavioral, contractual, and financial attributes commonly found in telecom services. Three classification algorithms Logistic Regression, Random Forest, and Gradient Boosting are applied to model churn behavior. Data preprocessing includes handling missing values, encoding categorical variables, and splitting data into training and testing sets. Model performance is evaluated using accuracy, recall, and ROC-AUC, with emphasis on recall due to its importance in identifying at-risk customers. The results show that Gradient Boosting achieves the highest overall performance with an ROC-AUC of 0.84, while Logistic Regression provides relatively higher recall. Key drivers of churn include short-term contracts, higher monthly charges, and lower service engagement. However, recall remains moderate, indicating limitations in capturing complex behavioral factors. These findings suggest the need to combine predictive models with behavioral insights and highlight the importance of early customer engagement and long-term retention strategies.

The digital era demands a fundamental transformation in the role of early childhood educators, shifting from passive technology consumers to active architects of digital literacy. However, the dominance of technocentric views often acts as a substantial psychological and pedagogical barrier for teachers in regional areas. This collaborative community service project aims to reconstruct the paradigm of 50 kindergarten teachers in Bulukumba Regency by integrating "unplugged coding" logic and deep learning into play-based learning. Utilizing a Product-Based Intensive Training method with a "Logic over Laptop" strategy, the program focused on deconstructing technology-related stigmas and reconstructing teachers' ability to transform abstract concepts into safe, concrete media for children. Data analysis revealed a significant shift in teacher paradigms; while the majority were initially in the "less successful" category, 100% of participants reached positive categories (successful and very successful) post-intervention. Statistically, the program's effectiveness was evidenced by a dramatic increase in mean scores from 18.04 to 31.24 (p < 0.05) and an N-Gain score of 0.778, classified as highly effective. Furthermore, the partner satisfaction index reached 4.82 (very satisfied), confirming that the tri-campus collaboration model (STAI Al-Gazali, UNM, and Unismuh) is highly relevant to the implementation of the Merdeka Belajar curriculum. This project concludes that strengthening digital literacy through non-digital algorithmic reasoning effectively dismantles technical barriers for teachers while ensuring the safety of child development in the digital age.

This study examines the implementation of Integrated Marketing Communication (IMC) at NailedShape, a Bali-based nail art micro-enterprise, as a strategy to foster customer loyalty. NailedShape operates under a home-service and home studio model, primarily using Instagram for promotion and customer engagement. The study utilizes a descriptive qualitative method, collecting data through interviews and observations with the owner, customers, and micro-influencers. The research findings show that NailedShape successfully employs IMC techniques, such as visual content, customer testimonials, and collaborations with digital influencers, to capture attention and create strong emotional connections with customers. This integrated approach helps in building a positive brand image and maintaining customer engagement. However, the study also highlights challenges, such as limited resources and frequent changes to social media algorithms, which hinder consistent communication and marketing efforts. Despite these obstacles, the study concludes that a well-executed IMC strategy remains effective in enhancing customer loyalty, reinforcing the importance of an integrated communication approach for small and medium enterprises (SMEs) in the beauty industry. By utilizing digital platforms effectively, NailedShape can compete in a highly dynamic market. The findings suggest that beauty-based MSMEs can benefit greatly from IMC in the digital era, as it not only enhances brand perception but also helps in building lasting customer relationships.

This study aims to analyze the role of marketplace in encouraging digital internationalization and product development at PT Bungas Food Nusantara. The research uses a qualitative approach with a case study method. Data was obtained through in-depth interviews with company management, observation of activities on the marketplace platform, and supporting documentation. The results of the study show that marketplaces function not only as digital distribution channels, but also as strategic infrastructure that allows companies to reach international markets without conventional export mechanisms. Internationalization occurs gradually through increased demand from overseas consumers facilitated by the platform's algorithmic system and global visibility. In addition, the marketplace's reviews, ratings, and analytics features are used as the basis for product development, including packaging adjustments, variant innovation, and data-driven promotional strategies. These findings show that marketplaces play a role as a catalyst for internationalization as well as a driver of product innovation in the context of the digital economy.

This study aims to analyze how the TikTok and Instagram Reels algorithms play a role in the distribution of multimedia content and their implications for content visibility, user engagement, and digital marketing practices. The research method used is a qualitative approach through a Systematic Literature Review by analyzing articles from accredited national journals and reputable international journals published in the period 2020-2025. The literature search process was carried out systematically through openly accessible scientific databases, then selected using inclusion and exclusion criteria to ensure the relevance and quality of the sources. The research findings show that the TikTok and Instagram Reels algorithms both rely on analysis of user behavior, initial engagement levels, and the characteristics of short-form audiovisual content in determining content distribution. TikTok emphasizes an interest-based recommendation system that allows content from new creators to gain broad reach, while Instagram Reels combines algorithmic recommendations with established social networks. The implications of this study emphasize that understanding the mechanics of algorithms is a strategic factor for content creators, business actors, and digital marketing practitioners in designing effective, adaptive, and sustainable multimedia content distribution strategies.

Financial distress is a condition of declining financial health of a company that can develop gradually and lead to business failure if not detected early. With the increasing complexity of the business environment and the limitations of conventional statistical methods, Artificial Intelligence/AI is increasingly being adopted in the development of early warning systems (EWS) to predict financial distress. This study aims to examine the development of AI-based EWS research, identify the most widely used algorithms, and evaluate the effectiveness of AI models compared to conventional methods in predicting financial distress. The method used is a comprehensive systematic literature review of 15 relevant scientific articles. The results show that the paradigm has shifted from statistical models to machine learning and deep learning. Random Forest and Artificial Neural Network are the most widely used algorithms and have better predictive performance. This study offers a conceptual synthesis of the progress, effectiveness, and challenges of applying AI in predicting financial distress and opens opportunities for further research on the development of contextual and interpretative EWS.

The development of digital technology has significantly transformed music consumption and marketing strategies in the creative industry. The shift from physical media to digital platforms, especially short-form video-based social media like TikTok, has created a new ecosystem that emphasizes interactivity, community participation, and organic music distribution. TikTok allows users to incorporate song snippets into creative content, positioning music as both entertainment and a symbol of digital identity. This shift reveals that music popularity is now primarily driven by recommendation algorithms and user-generated content rather than traditional promotion. This study adopts a qualitative descriptive approach with phenomenological analysis to explore the relationship between music consumption behavior and marketing strategies on TikTok. Findings indicate that algorithms act as digital curators, influencing audience preferences, while user participation accelerates the viral spread of songs through challenges, remixes, and content reproduction. Effective music marketing strategies must be data-driven, trend-responsive, and capable of leveraging users' emotional and social engagement. TikTok thus serves not only as a distribution platform but also as a space for constructing global popular culture. This study contributes to digital media scholarship and offers practical implications for designing sustainable marketing strategies in the ever-evolving digital ecosystem.

The era of globalization and the rapid advancement of information technology have transformed the landscape of dakwah (Islamic propagation), shifting from conventional pulpits to virtual communication platforms (social media, podcasts, streaming). This transition, in line with the Diffusion of Innovation Theory, enables Islamic messages to reach a broad audience without geographical boundaries. Digital dakwah is highly relevant and urgent to research given the dominant use of social media by Muslim Youth, a group that seeks attention but also possesses a tendency toward critical thinking. This research has a dual aim: (1) to analyze the Interpretation of Muslim Youth towards virtual dakwah studies, and (2) to analyze the Effectiveness of Implementing Dakwah Studies through social media platforms. The accessibility of fragmented and competitive content makes the interpretation process active and crucial, where youth are no longer passive recipients but choose sources based on algorithms and their own interests. This study uses the Constructivism Paradigm to understand a dynamic and complex social reality, employing a Descriptive Qualitative Approach and the Online Ethnography Method. Data is collected through Observation, Interviews, and Documentation, with Data Triangulation (source, technique, and time) to ensure the validity of the findings. Social media holds great potential as an effective and inclusive dakwah tool. However, the effectiveness of its expansion must be balanced with the quality of the content and the capacity of Muslim Youth to perform critical, contextual, and responsible interpretation.

The use of Artificial Intelligence (AI) in higher education learning has increased significantly, particularly among Informatics Engineering students. Although AI provides various benefits in supporting the learning process, its utilization also raises ethical concerns, especially related to algorithmic bias and responsible use of technology. This study aims to analyze the perceptions of Informatics Engineering students regarding bias and ethics in the use of artificial intelligence in learning. The research employed a quantitative descriptive approach. Data were collected through a Likert-scale questionnaire distributed to 80 Informatics Engineering students who had experience using AI in learning activities. Descriptive statistical analysis was conducted using mean scores and percentages. The results indicate that students demonstrate a high level of ethical awareness and responsibility in using AI; however, their perception of potential bias in AI systems remains at a moderate level. These findings reveal a gap between normative ethical awareness and critical understanding of algorithmic bias. This study recommends strengthening contextual and applied AI ethics literacy within the Informatics Engineering curriculum to promote responsible and ethical use and development of artificial intelligence technologies.

The utilization of digital technology in the Industry 4.0 era has become crucial for vocational high school (SMK) students to build economic independence. However, partners at SMKN 1 Selo still face obstacles in optimizing social media and digital platforms as effective promotional tools for student work and self-development. This community service activity aims to enhance students' understanding and skills in using social media (Instagram, TikTok) and other digital platforms as creative marketing instruments. The method employed is a descriptive qualitative approach through participatory training, which includes material presentation on digital branding strategies, visual content creation practices, and copywriting techniques. The results of the activity indicate a significant improvement in students' technical abilities, where they demonstrated the capacity to produce engaging promotional content and understand social media algorithms to reach a wider audience. This study aims to describe the process and impact of utilizing social media and digital platforms as promotional tools for SMKN 1 Selo students. The primary focus of this activity is to provide a deep understanding of personal branding strategies and creative product marketing in the digital age. Through this program, it is expected that SMKN 1 Selo students will possess higher digital competitiveness and the ability to leverage the digital ecosystem to support the promotion of vocational products and their professional profiles in the future.

This study aims to analyze the role of internet technology in enhancing the competitiveness of ebusiness in Indonesia, particularly in the sector of small and medium enterprises (SMEs). Based on theoretical reviews, internet technology, e-business, technology adoption (TAM), and the concept of competitiveness serve as the main foundations for understanding the ongoing digital transformation. The research employed a descriptive qualitative method with a purposive sampling technique, involving five informants consisting of digital SME owners, online store managers, and users of service platforms. Data were collected through interviews and observations, then analyzed using the Miles and Huberman model through the stages of data reduction, data presentation, and conclusion drawing. The findings reveal that the internet plays a crucial role as an essential infrastructure that enhances marketing effectiveness, expands market reach, and improves operational efficiency. Marketplaces, social media, and delivery-service platforms contribute significantly to sales growth and service quality. However, challenges such as low digital literacy, platform commission fees, changes in social media algorithms, and uneven infrastructure development still limit optimal utilization. From a policy perspective, the study recommends strengthening digital infrastructure and improving national digital literacy. This research emphasizes that the success of e-business depends on technology access, human resource competence, and support through public policy. It can be concluded that internet technology serves as a vital foundation for e-business competitiveness in the digital era.

This study examines the short story "Click that Kills" by Taufiqurohman to reveal the position of humans in the increasingly dominating digital algorithm environment. Using a descriptive qualitative approach that focuses on structural analysis and literary psychology based on Freud's psychoanalytic theory, this study thoroughly analyzes the intrinsic elements as well as the inner conflicts of the characters. The findings of this study show that the AIDA system poses a profound existential crisis, where individual freedom is threatened due to systemic information manipulation. The characters of Dito and Genta experience a serious conflict between id, ego, and superego when dealing with the figure of "Shadow User" who is a real symbol of the shift in human dignity through raw data. In terms of structure, the storyline conveys a deep social critique of the loss of human self-control in cyberspace. This research shows that this short story is a premonious criticism of the importance of maintaining the essence of humanity in the midst of the prevalence of mechanical algorithms. The phenomenon emphasizes that digital technology can potentially alienate the moral consciousness of individuals in modern society.

The use of Large Language Models (LLMs) in scientific research is becoming increasingly widespread, but presents epistemic risks that are not yet fully understood. This article discusses how the probabilistic mechanisms of LLM can produce outputs that appear correct and justified but are actually dependent on epistemic luck, thus resembling the Gettier case pattern. Through a conceptual study approach, this research clarifies concepts, analytically reconstructs the generative structure of LLM, and conducts a normative analysis of its implications for scientific accountability and authorship. The results of the analysis show that Algorithmic Gettier Cases (AGCs) occur when linguistic coherence deceives users and creates the impression of justification, even though the truth that emerges is statistical coincidence and is not supported by valid causal relationships. This condition poses a serious challenge to the attribution of knowledge and author responsibility in the production of academic texts. To address this issue, this article proposes the principle of Hyper-Justification Obligation, which is the ethical obligation for researchers to actively verify and causally reason every AI output before using it in scientific works. This research provides a theoretical contribution to understanding the epistemic risks of LLM and offers an ethical foundation for academic practice in the era of generative AI.

This study conceptually analyzes how blockchain technology reshapes the mechanisms of transparency and trust in global Islamic trade from the perspective of Islamic economics. The digitization of financial systems encourages a shift from trust based on social integrity and human relations, which traditionally form the foundation of muamalah practices, to an algorithmic trust model governed by code. In this context, this study examines how core values such as amanah and 'adl can be supported and even strengthened when economic interactions are increasingly mediated by technology. The research approach employs a qualitative-descriptive method, based on a literature review, with Miles and Huberman's analysis used to interpret the data and combine it with the normative principles of Islamic economics, thereby supporting the substance of Sharia. The main findings of this article show that blockchain has significant potential to enhance transparency, efficiency, and accountability through distributed ledgers and smart contracts, aligning with the objectives of maqāṣid al-sharī‘ah. However, despite its ability to reduce informational gharar, this technology also gives rise to new uncertainties that are technical, epistemic, and social in nature. Cases such as the DAO hack and the Terra–Luna failure confirm that technical transparency does not automatically lead to substantive justice. As a contribution, this study offers a Digital-Trust Maqāṣidiyyah framework, which positions blockchain as a means to strengthen Sharia ethics through adaptive contracts, Sharia oracles, decentralized arbitration, digital literacy, and Sharia regulatory sandboxes.

In the era of globalization, university graduates are required to have the ability to implement knowledge in real practice, which is realized through the Field Work program. This study aims to evaluate the compliance of Task Force reporting at PT PLN (Persero) North Sumatra Main Distribution Unit (UID North Sumatra). The method used is a quantitative approach with K-Means Clustering. Compliance reporting data was obtained from internal company documents, which then went through the preprocessing and clustering stages using the K-Means algorithm, with the determination of the optimal cluster number through the Elbow and Silhouette methods. The K-Means clustering analysis results identified two groups of units with different levels of compliance. Cluster 2, consisting of UP3 Binjai and UP3 Sibolga, showed a higher and more consistent level of reporting compliance. In contrast, Cluster 1 (including UP2D, UP3 B. Barisan, UP3 L. Pakam, UP3 Medan, UP3 Medan Utara, UP3 Nias, UP3 P. Sidimpuan, UP3 P. Siantar, and UP3 Prapat) had a tendency for lower compliance. This finding indicates a difference in reporting consistency that affects the effectiveness of work safety supervision. The K-Means method is proven to help PLN management identify units with low compliance, allowing corrective actions to be prioritized appropriately.

The rapid expansion of digital technologies has intensified financial misinformation and disinformation, particularly through illegal online loans and online gambling targeting communities with limited digital and financial literacy. This community engagement program in Dusun Munggur, Girimulyo Village, aimed to strengthen residents’ ability to identify and respond to deceptive digital practices through contextualized education on risk indicators, manipulative design strategies, and verification methods. Using a three-hour interactive socialization combining visuals, discussion, and a short comprehension exercise, the program improved participants’ understanding of how fraudulent financial schemes operate and how personal data, behavioral triggers, and algorithmic amplification are exploited. Participants demonstrated greater awareness of suspicious platforms, increased confidence in evaluating online offers, and requested sustained resources such as booklets and reporting guides for household- and community-level prevention. Although effective in raising immediate awareness, the intervention was limited by the lack of long-term behavioral assessment and the rapidly evolving nature of digital fraud. The program underscores the importance of community-centered, preventive literacy to mitigate digital financial risks in rural Indonesia.

The rapid expansion of digital technologies has intensified financial misinformation and disinformation, particularly through illegal online loans and online gambling targeting communities with limited digital and financial literacy. This community engagement program in Dusun Munggur, Girimulyo Village, aimed to strengthen residents’ ability to identify and respond to deceptive digital practices through contextualized education on risk indicators, manipulative design strategies, and verification methods. Using a three-hour interactive socialization combining visuals, discussion, and a short comprehension exercise, the program improved participants’ understanding of how fraudulent financial schemes operate and how personal data, behavioral triggers, and algorithmic amplification are exploited. Participants demonstrated greater awareness of suspicious platforms, increased confidence in evaluating online offers, and requested sustained resources such as booklets and reporting guides for household- and community-level prevention. Although effective in raising immediate awareness, the intervention was limited by the lack of long-term behavioral assessment and the rapidly evolving nature of digital fraud. The program underscores the importance of community-centered, preventive literacy to mitigate digital financial risks in rural Indonesia.

Mental health has become a major global issue, particularly after the COVID-19 pandemic, which significantly increased the prevalence of psychological disorders. Early detection of stress and other mental health problems remains a major challenge, as traditional methods are generally subjective and unable to provide real-time results. This study aims to design and test a wearable sensor based on Heart Rate Variability (HRV) as a physiological indicator for detecting stress levels. The research employed an experimental approach through the development of a wearable sensor prototype equipped with a stress detection algorithm based on HRV analysis, including both time-domain and frequency-domain parameters. The prototype was tested on 100 respondents with varying stress levels under controlled conditions. Instruments used in this study included the HRV sensor prototype, psychological questionnaires, and standard validation devices. Data were analyzed by comparing the sensor detection results with respondents’ psychological data and calculating prediction accuracy. The findings showed that the wearable sensor was able to predict stress conditions with an accuracy rate of 80%. The distribution of sensor detection results was generally consistent with psychological data, especially in the low-stress category, although slight deviations were observed in moderate and high-stress categories. These results demonstrate that an HRV-based wearable sensor can serve as a practical and non-invasive tool to monitor mental conditions in real time. The implications of this research highlight the potential of wearable technology as an innovative solution for mental health monitoring, both for individual use and as support for healthcare systems. Therefore, this study contributes to the development of adaptive and responsive health technologies in addressing global mental health challenges.

Digital transformation in the Industry 4.0 era has accelerated changes in consumer behavior and intensified competition in online markets. Under heterogeneous and increasingly saturated conditions, mass-marketing approaches become less effective, making niche market strategies more relevant as a path to differentiation. This article aims to formulate a systematic framework for independently building a niche market in the digital era through a synthesis of academic literature and a practical social-media case. The study uses a conceptual literature review integrating niche marketing theory, niche success characteristics, and social media marketing dynamics. The review indicates that effective niche market development follows sequential stages: (1) identifying specific market needs/problems, (2) designing a relevant product/service solution, (3) sharpening the target into a clearly defined niche, (4) formulating a unique selling point (USP) and value proposition, (5) conducting small-scale validation through a portfolio/MVP, (6) executing social media marketing, (7) maintaining consistent content and digital branding, and (8) performing continuous adaptive evaluation. The @foodish_mks case reinforces that content consistency and social-media utilization act as key mechanisms linking digital marketing intensity to niche success. This article contributes a cross-sector niche-building roadmap aligned with algorithmic, community-based digital platforms, and proposes a testable hypothesis model (H1–H6) for future empirical validation.