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In the dynamic landscape of Human Resource Management (HRM), the emergence of Artificial Intelligence (AI) technologies presents both challenges and opportunities. This research aims to explore strategies for empowering talent amidst AI innovations in HRM. The research adopts a phenomenological approach to delve into the lived experiences of HR professionals and employees within organizations integrating AI technologies. Through purposive sampling, data were collected via in-depth interviews and focus group discussions. Thematic analysis was employed to identify patterns, themes, and insights from the narratives. The findings reveal a nuanced understanding of how AI impacts talent management practices, including recruitment, training, performance evaluation, and career development. Moreover, the research elucidates the importance of human-centric approaches in leveraging AI to augment rather than replace human capabilities. These insights contribute to enhancing organizational strategies for talent empowerment in the era of AI-driven HRM innovations.

This study investigates the utilization of Artificial Intelligence (AI) to promote ethical business practices within the evolving landscape of digital marketing in Indonesia. The research aims to elucidate the current state of AI integration, its impact on ethical considerations, and the challenges and opportunities it presents. The study adopts a qualitative approach, employing semi-structured interviews and focus group discussions with key stakeholders involved in digital marketing and AI development. Sampling techniques include purposive sampling to ensure representation across industries and snowball sampling to access knowledgeable participants. Data analysis follows thematic analysis principles, identifying recurring patterns, themes, and divergences related to ethical concerns and AI implementation. Preliminary findings indicate a nuanced relationship between AI adoption and ethical dilemmas, with emerging strategies to balance innovation with ethical principles. This study contributes to understanding the ethical implications of AI in digital marketing and offers insights for businesses, policymakers, and scholars aiming to navigate this complex terrain responsibly.

This research aims to explore strategies for cultivating exceptional talent in the era of artificial intelligence (AI). The study employs a mixed-method approach, integrating interviews, surveys, and case studies to gather comprehensive data. The sample selection includes individuals from various industries known for fostering talent development, such as technology, education, and business. Through thematic analysis, the collected data are systematically examined to identify recurring patterns, emerging themes, and innovative practices in talent cultivation. Results reveal multifaceted strategies encompassing personalized learning, mentorship programs, continuous feedback mechanisms, and proactive skill development initiatives. Furthermore, the study highlights the significance of human-centric approaches in leveraging AI technologies to enhance talent development efforts. The findings contribute to a deeper understanding of how organizations can harness human potential effectively amidst technological advancements, paving the way for sustainable talent management practices in the AI era.    

In the rapidly evolving landscape of artificial intelligence (AI), optimizing human resources (HR) practices is imperative to foster organizational excellence. This qualitative research aims to explore the intersection of AI and HR practices to enhance organizational performance. The research adopts a qualitative approach utilizing in-depth interviews with HR professionals, AI specialists, and organizational leaders. Sampling techniques include purposive and snowball sampling to ensure diverse perspectives are captured. Data analysis involves thematic analysis, allowing for the identification of patterns and themes within the qualitative data. Preliminary findings indicate that organizations are increasingly leveraging AI to streamline HR processes, enhance talent acquisition, and improve employee engagement. Furthermore, the research reveals the significance of ethical considerations and human oversight in AI-driven HR practices. This study contributes to the growing discourse on AI integration in HR and provides insights for organizations aiming to navigate the AI-driven landscape while fostering excellence in HR practices.  

This research aims to explore strategies for maximizing human capital in the context of advancing artificial intelligence (AI) technologies within the workforce. The study employs a phenomenological approach to understand individuals' experiences and perceptions regarding AI integration in the workplace. Through purposive sampling, data were gathered from a diverse pool of professionals across industries. Semi-structured interviews were conducted to delve into participants' perspectives on the impact of AI on job roles, skill requirements, and organizational dynamics. Thematic analysis was employed to identify recurring patterns and emergent themes within the qualitative data. Preliminary findings suggest a nuanced interplay between AI technologies and human capabilities, highlighting the need for upskilling, retraining, and fostering adaptability among employees. The study contributes to the discourse on optimizing human resources amidst rapid technological advancements, offering insights for organizational strategies to harness the synergy between human expertise and AI innovations in the future workforce.      

The integration of Artificial Intelligence (AI) in education presents both challenges and opportunities for 21st-century learning. This study explores the transformative potential of AI in enhancing personalized learning, adaptive assessments, and intelligent tutoring systems. The research aims to identify the key barriers to AI adoption in educational settings, including ethical concerns, data privacy, and technological infrastructure. Utilizing a qualitative approach, data were collected through literature reviews and expert interviews. The findings indicate that while AI can significantly improve learning outcomes and administrative efficiency, its implementation requires strategic planning, teacher training, and regulatory frameworks. This study highlights the importance of balancing AI-driven innovation with ethical considerations to maximize its benefits in education.

Emerging technologies play a crucial role in transforming education by fostering inclusivity and equity. This study explores how artificial intelligence, virtual reality, and adaptive learning platforms contribute to overcoming traditional barriers to education. The research adopts a qualitative approach, analyzing case studies and recent advancements in educational technology. Findings reveal that these technologies enhance accessibility for students with disabilities, provide personalized learning experiences, and bridge educational gaps in underprivileged regions. The study highlights the importance of policy support and infrastructure development to maximize the benefits of technological integration in education. The implications suggest that adopting emerging technologies can create a more inclusive and equitable learning environment, ensuring education for all.

Smart wearable technologies are becoming essential tools for real-time health monitoring, offering a new dimension of personalized medicine. Wearable devices equipped with biosensors, artificial intelligence, and Internet of Things (IoT) connectivity can continuously track vital signs such as heart rate, blood pressure, oxygen levels, and even detect early symptoms of diseases. This paper explores the latest advancements in wearable health technology, including flexible electronics, energy-efficient data processing, and integration with telemedicine platforms. Additionally, ethical concerns such as data privacy, cybersecurity risks, and user adoption challenges are discussed. The study provides insights into how smart wearables can be effectively utilized for preventive healthcare, chronic disease management, and real-time health diagnostics.

This research endeavours to delve into the potential of Artificial Intelligence (AI) in bolstering Project Resource Management (PRM), discerning the principal challenges inherent in project resource planning, acquisition, and human as well as physical resource management, while also appraising the utilization of AI tools by project team members (PTM) and their efficacy in daily tasks. This research contributes a theoretical basis for what lies ahead studies in PM and unveils the benefits of AI in task monitoring, scheduling, team assignment, cost estimation, and the monitoring of physical project resource availability. This study employs a mixed-method approach, commencing with an initial literature review to identify project challenges. Data collection is facilitated through the administration of questionnaire surveys and interviews with project managers, encompassing both closed-ended and semi-structured questions. The research reveals that PTM readily embraces the utilization of AI for daily tasks and Project Resource Management can be enhanced through AI.

Covid-19 pandemic that hit almost all countries and no exception beloved our country Indonesia, has resulted in destruction and the collapse of the community’s economy. At the same time there is information about the covid-19 virus that still needs to be questioned about the validity of the source. With the development of technology in today’s era, it is easier for us to filter information that has valid sources so that there are no misunderstandings about the information obtained. So on this basis, this study aims to develop a chatbot model regarding Covid-19 in a relevant and fast manner according to the questions and statements entered. Chatbot itself is an Artificial Intelligence-based program or we can call it a digital assistant, which can simulate user conversations or chats like humans through an application either based on Android or the web. By using chatbot technology, users can get valid and relevant answers whose sources are clear so as not to cause anxiety and also make it easier for users to get information about the Covid-19 virus.   Keywords: Covid-19; Technology; Chatbot; Artifical Intelligence

Face recognition is an area that is still being researched and improved for various purposes such as attendance, population data collection, security systems and others. Two methods that are often used for face recognition applications are artificial intelligence methods, especially back-propagation neural networks (ANN) and learning vector quantization. Both of these techniques are directed learning techniques that are widely used to identify distinctive patterns, namely grouping patterns into groups of patterns, making them ideal for use in facial recognition applications. In this application, preprocessing of the input image includes the detection process of scaling, grayscale, edged with the sobel and threshold methods, carried out before the image is processed in ANN. Meanwhile, the ANN approach used to identify faces involves the Backpropagation method and the Learning Vector Quantization method. The findings of this analysis are a comparison of the backpropagation neural network method and quantization of the learning vectors of face recognition used to assess variations, limitations, strengths and optimal results of the two techniques for use in facial recognition systems.