Publication Search

Innovation strategy is a crucial approach to enhancing organizational competitiveness, especially in the digital era marked by rapid technological advancement and increasingly complex competition. This study aims to analyze how innovation strategies can be effectively implemented to improve organizational competitiveness, while also identifying key supporting factors such as digital transformation, innovative culture, external collaboration, leadership, and data-driven decision-making. The research method employed is literature review, drawing from various theoretical frameworks and previous studies. The findings indicate that integrated innovation strategies—including digital process transformation, development of digitally competent human resources, and the establishment of an adaptive organizational culture—significantly contribute to overall organizational performance improvement. The application of advanced technologies such as artificial intelligence and big data also enhances the organization's ability to understand stakeholder needs and design targeted solutions. This study emphasizes that innovation is no longer an option, but a fundamental necessity to ensure organizational sustainability, relevance, and competitive advantage in the digital age.

This study investigates the implementation and effectiveness of artificial intelligence-driven adaptive learning platforms in English as a Foreign Language (EFL) classrooms across urban and rural Indonesian educational settings. Through a mixed-methods approach involving 247 students and 12 teachers from eight institutions, this research comparatively analyzes three prominent AI language learning platforms: LinguaLearn AI, AdaptEd English, and AI Tutor Pro. The findings reveal significant differences in learning outcomes, with AI-enhanced platforms demonstrating a 27% improvement in language proficiency compared to traditional methods. However, implementation challenges including digital literacy barriers, internet connectivity issues, and cultural adaptation requirements were identified, particularly in rural contexts. The study proposes a contextually responsive framework for integrating AI language learning technologies in developing EFL environments, contributing to the growing discourse on educational technology in linguistically diverse settings. This research highlights the potential of AI to personalize language acquisition while emphasizing the necessity of culturally and infrastructurally appropriate implementation strategies.

The digital era has fundamentally transformed the educational paradigm. This research examines the transformation of teachers' roles in addressing digital technology developments, particularly artificial intelligence (AI) and social media. The purpose of this study is to analyze the importance of technology literacy and digital ethics for teachers in creating adaptive and relevant learning environments. A literature review methodology is employed to identify key components required for teachers to transform into adaptive educators. The findings indicate that teachers need to develop five core competencies: understanding digital tools, critical information evaluation, interactive learning design, facilitating independent learners, and implementing technology ethics. This research contributes to developing a framework for adaptive teachers capable of utilizing technology as an opportunity rather than a threat in the educational process.

The continuous development of technology compels companies to consistently adapt to advancements across various aspects of life. Digital transformation has become an essential need for many organizations today as a strategy to improve service quality and operational efficiency. Alfamart, one of Indonesia's leading retail companies, is currently adopting digital transformation in its business processes. The acceleration of digital transformation in Indonesia necessitates the application of digital technology as a basic platform to support the Industry 4.0 ecosystem, leveraging technologies such as the Internet of Things (IoT), big data, artificial intelligence (AI), and augmented reality. This research employs a qualitative approach and descriptive analysis method to evaluate the impact of digital transformation on PT. Sumber Alfaria Trijaya, Tbk (Alfamart), specifically at the Nangahure unit located in Sikka Regency. Analysis is conducted through data reduction, data presentation, and conclusion drawing stages. The research results indicate that the management system at Alfamart Nangahure has been applied in a structured manner and in accordance with the policy standards set by the headquarters. The system includes a well-organized organizational structure, efficient operational management, systematic human resource management, as well as regular evaluation and monitoring processes that support the achievement of store operational targets.

In the digital era that increasingly emphasizes human-computer interaction, the existence of an interface system that is not only functional but also able to understand the emotional state of the user is becoming increasingly important. This study aims to explore the effectiveness of empathetic interfaces in chatbot systems designed to respond adaptively to user moods. Empathetic chatbots are defined as artificial intelligence-based conversational agents that are able to recognize and adjust their verbal responses to user emotional expressions through linguistic analysis and non-verbal data such as response time and word choice. This study uses an experimental approach involving 60 participants from among students who interact with two types of chatbots: standard chatbots (non-empathetic) and empathetic chatbots. The analysis methods used include measuring the level of user satisfaction, empathy perception, and emotional comfort through a Likert scale questionnaire and quantitative data processing using a paired T-test.

This literature review analyzes the transformative potential of digital learning media in revitalizing Indonesian traditional music, with a particular focus on Gambang Kromong innovation within the framework of Society 5.0. Traditional music, as the foundation of cultural identity, faces significant threats from globalization and modernization, resulting in declining interest, especially among the younger generation. This approach examines how digital technologies can serve as a catalyst for the preservation, learning and dissemination of traditional music, transforming it from a marginalized status to one of contemporary relevance. The report synthesizes existing literature to identify key trends, benefits derived from the use of technologies such as Digital Audio Workstations (DAWs), Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), gamification, and online and social media platforms. In addition, the report discusses inherent challenges, including the digital divide, the need for increased educator competencies, and intellectual property rights issues, while highlighting opportunities for collaboration and global audience reach. The conceptualization of "Gambang Kromong 5.0" is proposed as a holistic model that integrates traditional essence with intelligent technological advancements in a human-centric manner, ensuring cultural survival and artistic relevance in the digital age.

The integration of Artificial Intelligence (AI) in education has introduced a more responsive and personalized learning approach. This study aims to examine the correlation between the intensity of AI usage and students’ learning outcomes. Employing a quantitative approach, the research utilized Pearson Product Moment correlation analysis. A total of 27 students, selected through purposive sampling and known to actively use AI in their learning process, participated in the study. Prior to the correlation analysis, the data underwent validity, reliability, normality, homogeneity, and linearity testing. The results confirmed that the instrument met the criteria for validity and reliability (Cronbach’s Alpha = 0.824), with data distribution being normal and homogeneous, and the relationship between variables being linear. The Pearson correlation coefficient of r = 0.583 with a significance value of p = 0.001 indicates a statistically significant and moderately strong positive relationship. These findings suggest that AI plays a meaningful role in enhancing students’ learning effectiveness. Therefore, it is essential to provide guidance and development efforts to ensure AI is utilized ethically and educationally to optimize its impact in academic settings.

The development of Artificial Intelligence (AI) technology has led to the creation of various works, including images generated without direct human involvement. One of the platforms that facilitates the buying and selling of AI-generated images is Adobe Stock. However, this raises legal issues regarding ownership status and copyright protection of such images, considering that Indonesia's positive law has not explicitly regulated ownership of works produced by non-human entities. This research aims to examine the legality of ownership over images generated by Generative AI in transactions through Adobe Stock and to analyze its compatibility with the Indonesian legal system. This study uses a normative juridical method with statutory, case, comparative, and conceptual approaches, as well as a literature study relevant to the issues discussed. The results show that under the Indonesian legal system, a work must have a creator who is a legal subject. Therefore, images generated by AI cannot automatically be granted copyright status unless there is significant human intervention in the creation process. In transactions through Adobe Stock, the platform's policy serves as the main reference in determining ownership and legal responsibility over AI-generated images. The legality of AI-generated image ownership in Indonesia remains a gray area and requires regulatory updates to accommodate technological developments. Legal clarity is needed to protect parties involved in AI-based digital transactions and to ensure legal certainty in the protection of creative works.

The integration of telemedicine and artificial intelligence (AI) into critical care has emerged as a revolutionary development in the healthcare sector, aiming to enhance patient care and outcomes. This research aims to explore the impact of these technologies on improving the quality of patient care in intensive care units (ICUs). A systematic review of recent studies published between 2018 and 2023 was conducted to analyze the role of telemedicine in improving access to healthcare and the application of AI in enhancing diagnostic accuracy and monitoring patients in real-time. The findings suggest that both telemedicine and AI significantly reduce response times, improve decision-making processes, and increase the accuracy of diagnoses, which ultimately contribute to better patient safety and outcomes. The research also highlights challenges, including infrastructure limitations and the need for specialized training for healthcare professionals. The study’s implications underline the importance of integrating these technologies in critical care units to improve overall healthcare delivery, while addressing barriers to implementation. Future research should focus on overcoming these challenges and exploring long-term outcomes of technology use in critical care environments.

The skin and hair care industry has experienced rapid growth in recent years. As the digital ecosystem becomes more established, various local products have the opportunity to emerge and exist in the market. Among the local products that have just emerged and found a place in the hearts of consumers is Lavojoy. Research on digital marketing strategies for imported products has been carried out very often, while for local products, especially skin and hair care products, has not been done much. This study aims to analyze Lavojoy's digital marketing strategy in increasing consumer loyalty. The research was conducted using a descriptive qualitative approach. Research data were obtained from the results of digital observations and data searches in various popular site databases related to the research problem. The results of the study show that the digital utilization strategy allows Lavojoy to build a loyal customer community through interactive content, collaboration with influencers, and active engagement through live and polling features. Two-way interactions carried out on Instagram, TikTok, and YouTube have a significant impact on brand awareness and customer emotional attachment to the brand. In addition, e-commerce optimization carried out through exclusive promo strategies, cashback, loyalty programs, and live shopping features has succeeded in increasing customer retention and encouraging repeat purchases. To increase the effectiveness of digital marketing strategies in the future, Lavojoy is advised to increase personalization in digital marketing by utilizing artificial intelligence (AI) and customer data analysis to offer a more personalized shopping experience, as well as developing content and product recommendations tailored to each customer's preferences, both through social media and e-commerce.

Artificial Intelligence (AI) can be a transformational tool in Christian Religious Education in the digital era. Technological advancements bring significant changes to the way we learn and teach, including religious education, which demands innovative methods to remain relevant to the younger generation increasingly connected to technology. AI offers various opportunities to enrich the learning experience and deepen the understanding of Christian values through a more personal and interactive approach. This article discusses several AI applications in Christian religious education, such as virtual assistants for spiritual guidance, in-depth Bible text analysis, and adaptive learning platforms that can tailor materials to the needs of learners. With AI technology, Christian religious education can provide more interactive and responsive modules, allowing learners to delve into religious teachings both individually and in groups. Additionally, the use of AI in analyzing learning behavior allows for more effective curriculum personalization according to the spiritual needs of each individual. This approach can address the challenge of maintaining the relevance of religious values amidst the rapid influx of digital information. This article also examines the potential of AI in aiding faith development, for example through spiritual reflection applications tailored to the user's spiritual growth. This transformation is expected to prepare a generation of Christians who are not only technologically savvy but also spiritually strong, and empowered to face moral and ethical challenges in the future. Thus, AI-based Christian Religious Education can be a pathway to building a relevant and dynamic spiritual future in the digital era.

The development of drone technology and artificial intelligence (AI) has presented great opportunities in various sectors, but at the same time opened up new loopholes for potential terrorist attacks. This article analyzes the shift in terrorism attack strategies from traditional manual methods to the use of drone-based autonomous systems and AI. Through a descriptive qualitative approach and literature review, this study explores how this technology is used to improve the effectiveness, anonymity, and scale of attacks. The study also discusses threats arising from AI-based drone swarm capabilities, potential cyberattacks on drone systems, and global regulatory lags in anticipating these threats. In addition, this article offers policy recommendations to strengthen national defense systems against the increasingly complex and automated evolution of terrorism threats. These findings are expected to be an early contribution to the development of counter-terrorism strategies that are adaptive to technological advances.

The advancement of information and communication technology in the era of the Industrial Revolution 4.0 has given rise to various digital innovations, one of which is deepfake technology that utilizes artificial intelligence and machine learning to manipulate audio-visual content convincingly. Although it has positive potentials in entertainment and education, the misuse of deepfake on social media has caused various legal and ethical issues, such as the spread of hoaxes, defamation, privacy violations, and non-consensual pornography. This study aims to analyze the use of deepfake from the perspective of Indonesian law, particularly through Law Number 11 of 2008 on Electronic Information and Transactions (ITE Law) and its amendments. Using a qualitative descriptive approach and literature study methods, this research examines the technical aspects of deepfake development, the relevance of ITE Law articles in regulating manipulative content, and the challenges of law enforcement amid low digital literacy in society. The findings show that although there are no explicit provisions concerning deepfake in the ITE Law, several articles can serve as a legal basis to prosecute offenders, albeit with interpretative and technical implementation challenges. Therefore, regulatory updates and improvements in digital literacy are necessary to prevent and effectively handle the misuse of deepfake technology.

Learners are continually faced with choosing appropriate courses or making career choices due to increased educational opportunities. The emergence of machine learning-based course and career recommender systems has the potential to address this issue, offering personalized course recommendations tailored to individual learning pathways, preferences, and learning history. The optimization and feature engineering techniques and practical deployment environments have not been collectively examined in the previous research, despite the significant advancements in this area of research. Furthermore, previous research has rarely synthesized how these technical components help students choose appropriate courses and careers. This systematic review was carried out to investigate the current state of machine learning-based course and career recommender systems, focusing on key elements, such as primary data sources, feature engineering methods, algorithms, optimization techniques, evaluation metrics, and the environments where the existing course recommendation models are deployed. The PRISMA method for conducting a systematic review was used to choose studies that met the requirements for inclusion and exclusion. The study findings show significant reliance on interpretable and traditional machine learning algorithms, such as K-Nearest Neighbor and Random Forest, to develop recommender models. Feature engineering remains basic, as most studies rely on normalization, while optimization processes are often underreported. Also, evaluation metrics varied widely, impeding comparability, while most of the recommender models are deployed in an e-learning environment, leaving the traditional learning environment underrepresented. Furthermore, the study findings identified issues including data sparsity and diversity, data security and privacy, and changes in learner preferences that may have an impact on the performance of recommender systems while recommending further studies to make use of standardized optimization methods, and automated domain-informed feature engineering frameworks, benchmark and annotated datasets in developing models the gives priority to learners’ success and educational relevance.

The development of digital technology has driven fundamental changes in management accounting practices, which no longer serve merely as internal recording tools but have transformed into strategic support systems for business decision-making. This article aims to systematically examine the role of technology-based management accounting in supporting decisions at the strategic, operational, and tactical levels. This study employs a Systematic Literature Review (SLR) method on 20 relevant scientific articles published between 2021 and 2025. The findings indicate that the integration of technologies such as ERP, cloud accounting, artificial intelligence (AI), and big data can enhance the accuracy, speed, and efficiency of managerial decision-making. Additionally, it was found that the implementation of technology significantly impacts operational efficiency and a company's competitiveness. However, the success of implementing technology-based management accounting systems heavily depends on organizational readiness, human resource competencies, as well as supportive work structures and cultures. This article also identifies gaps in the literature, particularly in the context of SMEs, which present important opportunities for future research.

Deepfake technology, a product of artificial intelligence, is widely discussed by the public because of its sophistication in replacing the face of the original subject with the face of another subject in the form of a video or photo. This has been misused to create non-consensual pornographic content that has claimed many victims. Over time, this abuse has been facilitated by the spread of the Telegram conversation application. The abused content is then disseminated by the perpetrators on social media and traded. The research method used in this research is normative juridical research which aims to analyse existing regulations, as well as regulations needed to fill the legal vacuum. Moreover, in the case of crimes using AI, there is no specific regulation, so the vacuum has an impact on the lack of security and comfort for victims of deepfake porn. However, the ITE Law describes AI as electronic agents and electronic systems. Criminal law considers that AI is not a legal subject, so the responsibility for AI crimes is imposed on the users of AI technology itself, especially in the crime of deepfake porn.

The Geopolitics 5.0 era has introduced a new paradigm in which artificial intelligence (AI), digital technology, and global power dynamics are reshaping traditional diplomatic practices. As a nation rooted in the Pancasila ideology, Indonesia faces complex challenges in upholding its principles of humanity, unity, and social justice amid increasingly competitive geopolitical shifts. This research aims to analyze the relevance of Pancasila as a strategic framework for Indonesia’s diplomatic efforts in responding to the challenges of Geopolitics 5.0, while formulating policy recommendations aligned with national values. The study employs a qualitative approach, analyzing content related to Indonesia’s foreign policy, government documents, and recent diplomatic case studies. Supporting data is drawn from academic literature, archives of the Ministry of Foreign Affairs, and reports from global think tanks. The findings demonstrate that Pancasila serves as a critical foundation for shaping Indonesia’s adaptive diplomacy, particularly through: (1) soft power strategies rooted in cultural and creative economic assets, (2) digital diplomacy that prioritizes cyber sovereignty and freedom, and (3) leadership in multilateral forums. Pancasila’s values not only remain relevant but also provide Indonesia with a strategic advantage in building principle-driven diplomacy in the Geopolitics 5.0 era. Policy recommendations include strengthening digital human resource capacity, fostering collaborative technology research, and advancing public diplomacy initiatives.

This study examines the pivotal role of artificial intelligence (AI) in talent attraction within the human resources sector, particularly in the context of modern technological advancements. We aim to understand the influence of AI on recruitment processes and identify factors affecting talent attraction in the information age, as well as the associated challenges. The study focuses on how AI impacts recruitment and utilizes statistical methods, including interviews, questionnaires, standard deviation, arithmetic mean, and Spearman's rank correlation, to achieve accurate results. Participants included 100 employees and professors from the Ministry of Higher Education and Scientific Research, with a research community of around 750. Findings suggest that organizations employing AI for recruiting, attracting, training, and guiding individuals tend to succeed. The study recommends the urgent integration of AI into organizational operations, urging a shift from traditional applicant comparison methods to modern assessment techniques while avoiding favoritism. Additionally, organizations should implement contemporary training programs to boost employee performance.

The continuous evolution of technology has significantly transformed the way humans interact with computers, moving beyond traditional keyboard and mouse inputs toward more natural and adaptive interfaces. This literature review examines the current and emerging trends in user interface (UI) development within the context of Human-Computer Interaction (HCI), with a specific focus on future-oriented innovations. Key areas of discussion include voice-user interfaces (VUIs), gesture-based interaction systems, adaptive and context-aware UIs, artificial intelligence (AI) integration, and neuroadaptive technologies. The study employs a qualitative analysis method, drawing upon scholarly publications from 2020 to 2025 and emphasizing the contributions of researchers from Universitas Islam Negeri Sumatera Utara, particularly M. Khalil Gibran. These technologies are assessed for their usability, accessibility, efficiency, and their ability to enhance user satisfaction through personalization and contextual awareness. Results from reviewed studies suggest that adaptive and AI-driven UIs are becoming essential in delivering personalized user experiences

The COVID-19 pandemic has exposed fundamental vulnerabilities in global supply chain systems, such as over-reliance on single suppliers and a lack of operational visibility. This has highlighted the urgent need for a new approach to risk management—one that leverages smart technologies. Artificial Intelligence (AI) has emerged as a promising solution, thanks to its capabilities in predictive analytics and adaptive, data-driven decision-making in real time. This study aims to develop an AI-based predictive system framework to enhance the resilience of global supply chains in the face of post-pandemic disruptions. Using the Design Science Research (DSR) methodology, the research designs and evaluates a system that integrates algorithms such as LSTM, Random Forest, Natural Language Processing (NLP), and Reinforcement Learning. It also applies a federated learning approach to ensure data privacy among supply chain partners. The study analyzes over 12,000 data entries from diverse sources, including IoT devices, weather data, demand trends, and social media. The system's effectiveness is evaluated through a combination of quantitative methods (PLS-SEM analysis on 103 respondents) and qualitative methods (interviews with 12 industry executives). The findings show that AI-driven predictive analytics significantly improve supply chain resilience (β = 0.67; p < 0.001), with demand forecasting accuracy increasing by up to 40% and delivery times reduced by 30%. Conceptually, the study contributes by designing a resilient model that integrates real-time visibility, adaptability, and cross-organizational collaborative learning. Unlike traditional approaches focused solely on automation, this framework offers a more holistic solution, addressing key gaps in the literature. The implication is clear: AI is becoming a strategic asset in building sustainable, resilient supply chains amid ongoing global uncertainty.