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This study aims to examine the implications of automation and artificial intelligence (AI) on employment law politics in Indonesia, as well as their impact on employment structures and relationships. Along with rapid technological advances, especially in the fields of automation and AI, the world of employment is undergoing significant transformations that affect work models, employment contract arrangements, and worker protection. This study will identify how these technologies affect employment relationships, creating new opportunities, but also threatening the sustainability of jobs in certain sectors. This study uses a qualitative approach with descriptive analysis to understand the dynamics of change resulting from automation and AI, and their legal implications for workers and companies. The main focus of this study is to assess the extent to which employment policies in Indonesia can accommodate the new challenges arising from this technological shift, and how the existing employment law system needs to adapt to remain relevant and effective. The findings of this study are expected to contribute to policymakers, legal practitioners, and academics, by providing recommendations on how employment policies in Indonesia can be updated to anticipate the negative impacts of technology, protect workers' rights, and create social justice in an increasingly digitalized world of work. This research will also provide an overview of the role of technology in shaping future industrial relations and regulations, and propose a legal framework that is adaptive to the development of automation and artificial intelligence in Indonesia.

The increasing adoption of artificial intelligence (AI) in decision-making processes has raised significant concerns regarding algorithmic bias and legal accountability. This study examines the regulatory challenges and enforcement gaps in addressing AI bias, with a particular focus on Indonesia’s legal landscape. Through a comparative analysis of AI governance frameworks in the European Union, the United States, China, and Indonesia, this research identifies key deficiencies in Indonesia’s regulatory approach. Unlike the EU’s AI Act, which incorporates risk-based classification and strict compliance measures, Indonesia lacks a dedicated AI legal framework, leading to limited enforcement mechanisms and unclear liability provisions.The findings highlight that transparency mandates alone are insufficient in mitigating algorithmic discrimination, as weak enforcement structures hinder effective regulatory oversight. Furthermore, the study challenges the notion that global AI regulatory harmonization is universally applicable, emphasizing the need for a context-sensitive hybrid model tailored to Indonesia’s socio-legal environment. The research suggests that Indonesia must adopt a comprehensive AI legal framework, strengthen regulatory institutions, and promote interdisciplinary collaboration between legal experts and AI developers. Future research should focus on empirical case studies, the development of context-specific AI accountability models, and the role of public engagement in AI bias mitigation. These efforts will be essential in shaping effective AI governance strategies that ensure fairness, transparency, and accountability in Indonesia’s digital transformation.

The apparel industry in Chengdu is transforming significantly due to integrating artificial intelligence (AI) technologies. This evolution aims to enhance consumer satisfaction by providing personalized shopping experiences, improving inventory management, and streamlining the supply chain. AI-driven algorithms analyze consumer behavior and preferences, allowing retailers to create tailored recommendations that align with individual tastes. Additionally, AI tools enable efficient inventory management by predicting trends and consumer demand, which helps reduce instances of overstock and stockouts. This optimization improves operational efficiency and ensures customers can find their desired products when visiting stores or online. This study was conducted through an online questionnaire distributed to 376 Chengdu participants to measure their attitudes toward AI improvement in the apparel industry. The findings underscore that innovative technology, perceived information quality, and perceived customization correlate with consumer satisfaction in AI experience improvement.    

This abstract explores the role of artificial intelligence (AI) in enhancing consumer satisfaction in Sichuan's online customer experience and service efficiency. With the rapid growth of e-commerce, understanding consumer preferences and behaviors has become crucial. AI technologies like chatbots, predictive analytics, and personalized recommendations are integrated into online platforms to streamline service delivery and improve user interactions. By leveraging data-driven insights, businesses can tailor their offerings to meet the specific needs of consumers, thereby increasing satisfaction levels. Furthermore, AI facilitates faster response times and more efficient problem resolution, leading to a seamless shopping experience. This study was conducted through an online questionnaire distributed to 380 Sichuan participants to measure their optimization and service efficiency satisfaction. The findings underscore that technical infrastructure, user acceptance and engagement, and service quality positively correlate with consumer satisfaction in AI experience improvement.

The rapid advancement of digital technologies has significantly transformed the shipping logistics and supply chain management sectors. This study explores the impact of digitalization on these industries, focusing on the integration of technologies such as artificial intelligence, blockchain, and the Internet of Things (IoT). The primary objective of this research is to analyze how digital tools enhance operational efficiency, reduce costs, and improve decision-making in logistics and supply chain operations. Through qualitative and quantitative methods, including case studies and surveys, the study identifies key trends and challenges faced by organizations adopting these technologies. Findings reveal that digitalization leads to improved transparency, real-time tracking, and enhanced collaboration across the supply chain. However, challenges such as cybersecurity risks, high implementation costs, and the need for skilled labor remain significant. The implications of these findings suggest that while digital transformation offers considerable benefits, organizations must carefully manage the transition to ensure sustainability and long-term success.

The development of computer technology helps many aspects of life. One aspect of life that takes advantage of technological developments is the health sector, in order to solve problems including brain tumors. Brain Tumor Disease is the growth of abnormal cells in or around the brain in an unnatural and uncontrolled manner. Patients with brain tumors continue to increase every year, because the initial symptoms are often underestimated. Therefore created a software that can help diagnose brain tumors using the certainty factor method

Technological developments in the Digital Era 5.0 have significantly changed the landscape of the accounting profession. Artificial intelligence (AI), big data, blockchain, and the Internet of Things (IoT) are the main factors influencing the transformation in the world of accounting. Accountants are no longer just playing the role of recorders of financial transactions, but are also required to have in-depth data analysis skills and an understanding of new technologies that support efficiency and accuracy in financial management. The biggest challenge faced is the automation of various tasks that were previously done manually, which can reduce the need for conventional accountants. However, on the other hand, this development also opens up opportunities for accountants to increase their role in financial analysis, business planning, and technology-based risk management. This socialization activity aims to provide an understanding to accounting students and high school students regarding the role and challenges of the accounting profession in the digital era. Through a community service program in the form of a Focus Group Discussion (FGD), participants were given insight into the importance of adapting to technological developments and strategies that can be applied to stay relevant in the world of work. The results of this activity showed that the students involved gained a better understanding of the digital transformation in the accounting profession and the importance of developing technology-based skills. Thus, it is expected that future accountants can improve their competitiveness and be ready to face changes in the increasingly digital and complex business world.

The emergence of Artificial Intelligence presents a challenge in Copyright law in the context of visual artworks, as various Artificial Intelligence systems are currently available to create images. Based on this, the research aims to examine the legal regulations regarding the use of Artistic Image Works in Artificial Intelligence training data according to the Copyright Laws of Indonesia and Singapore, as well as how Copyright regulations can be developed to address these legal issues. This study uses a normative legal research method with a descriptive nature, employing statutory and comparative approaches. The data consists of secondary legal materials, collected through library research and analyzed using a syllogistic method with deductive reasoning. The findings and discussion of this research reveal that there is currently no clear legal basis for the use of Artistic Image Works in Artificial Intelligence training data under Law Number 28 of 2014 on Copyright in Indonesia, whereas the Singapore Copyright Act 2021 has accommodated this issue through provisions on Fair Use and Computational Data Analysis. Therefore, a reformulation of regulations is needed regarding several aspects such as Use, Reproduction, and the role of Collective Management Organizations.

The integration of Artificial Intelligence (AI) in education has opened new possibilities for enhancing teaching and learning, particularly in English for Specific Purposes (ESP) classrooms. This study examines the perceptions and motivations of third-semester management students at Universitas Merdeka Pasuruan regarding AI-assisted writing tools in their ESP courses. Using a qualitative case study design, data were collected through semi-structured interviews with 20 participants. Thematic analysis identified three key themes: perceptions of AI tools' usefulness, motivational factors, and challenges. Participants viewed AI tools as beneficial for improving writing skills, providing personalized feedback, and supporting collaborative learning. Motivational drivers included simplifying complex tasks and promoting independent learning. However, challenges such as technical difficulties and limited proficiency in using AI features were highlighted. The findings emphasize the potential of AI in enhancing ESP instruction, provided challenges are addressed with adequate training and support. Despite its small sample size and focus on a single institution, the study offers insights into the pedagogical implications of AI integration in specialized language education. It also provides practical recommendations for optimizing AI use in ESP classrooms while calling for broader research in diverse educational contexts.

The research addresses the role of artificial intelligence technologies in achieving cost reduction, achieving a sustainable competitive advantage, and improving the operational performance of companies, by analyzing how these technologies reduce costs. The research is based on a basic hypothesis that "artificial intelligence technologies contribute positively to reducing costs for economic units by improving the efficiency of using available resources, reducing waste, and improving technical innovations, which enhances the ability of the economic unit to compete and achieve a sustainable competitive advantage." The research recommends investing in artificial intelligence technologies, training employees to use them effectively, developing a clear strategy, adopting analytical models to measure the impact of artificial intelligence on performance and costs on a regular basis, and supporting research related to developing artificial intelligence applications to improve operational efficiency and enhance cooperation between universities and economic units to develop innovative solutions that achieve a sustainable competitive advantage. This research is an addition to the literature concerned with how economic units adopt artificial intelligence technologies and work to reduce their operating costs, and aims to provide a practical framework for economic units seeking to improve their financial performance by adopting the latest artificial intelligence technologies.

The development of digital technology based on Artificial Intelligence (AI) has had a significant impact on society, including the emergence of new crimes such as deepfake pornography. Deepfake pornography is a form of AI misuse that creates fake pornographic content by manipulating a person's face into a video or image without consent. This phenomenon raises complex legal issues within the Indonesian criminal law system. This study aims to examine how Indonesian criminal law regulates AI deviations in the form of deepfake pornography and to assess the effectiveness of these regulations in providing legal protection. This research uses a normative approach with qualitative analysis methods and the theory of legal effectiveness as the analytical tool. The research findings indicate that AI deviations in the form of deepfake pornography are not specifically regulated in Indonesia's positive criminal law. The applicable regulations are still general in nature, scattered across several laws such as the Electronic Information and Transactions Law (ITE Law), Personal Data Protection Law, Pornography Law, Sexual Violence Criminal Act Law, Copyright Law, and the Criminal Code (KUHP), which do not comprehensively address the technological aspects and psychosocial impacts of this crime. Based on Soerjono Soekanto's theory of legal effectiveness, the existing regulations are not yet effective, as seen from the legal substance, law enforcement, legal facilities and infrastructure, community factors, and legal culture. Therefore, a responsive legal reform is needed to keep pace with digital technological developments, along with strengthening the capacity of law enforcement institutions.

The present study reflects upon the initial evaluation of Indonesia's readiness for the ethical adoption of artificial intelligence (AI) per the available evaluation framework, namely, the UNESCO Readiness Assessment Methodology (RAM). The analysis considers key legal, social, scientific, economic, and technical dimensions pertaining to governance of artificial intelligence in Indonesia, with the view to exploring particular gaps and opportunities for improvement. Following a detailed secondary-document analysis, this study underscores the capacity of the country to apply AI within economic, governance, and sustainable development domains while tackling ethical challenges. The study also makes recommendations for legal systems and frameworks, infrastructure, and interdisciplinary collaboration. The limitations of the present assessment are indicated, alongside guidance for future studies to pursue an inclusive and sustainable AI ecosystem in Indonesia.

This research aims to find out the regulations regarding deepfake crimes in Indonesia and to find out the ideal regulations regarding deepfake crimes in the future. This technology, which is increasingly developing rapidly, can essentially make it easier to do anything. Apart from that, technological developments can cause serious problems, one of which is the misuse of deepfakes which are part of artificial intelligence. Deepfakes certainly harm many people, starting from victims whose identities are used by fraudsters, to victims who suffer material losses. The absence of regulations governing deepfakes means that state protection for victims of this crime is still in doubt. This research uses a normative legal research method which uses 3 (three) approaches, namely the statutory approach, the comparative approach and the conceptual approach. This research uses data collection techniques through library research. This research uses descriptive data analysis techniques by presenting data and information as a description of the research subjects and objects which are arranged systematically so that they can be understood. This research also uses a prescriptive analysis method, namely by providing arguments on the research results that have been described. The results of this research show that Indonesia has not yet explicitly regulated deepfake crimes. Indonesia only regulates falsification of personal data in general in the ITE Law which is a derivative of the 1945 Constitution of the Republic of Indonesia.

This study aims to analyze the application of Deep Neural Networks (DNN) as an artificial intelligence approach in processing weather data to support more accurate and stable climate predictions. Increasingly unpredictable and fluctuating weather patterns demand modern analytical methods capable of capturing non-linear relationships among atmospheric variables. DNN is utilized due to its ability to learn complex data structures through multilayer representations that extract deeper features from input variables. Weather data such as temperature, humidity, rainfall, air pressure, and wind speed are processed through several preprocessing stages to ensure optimal model performance. This research employs a descriptive qualitative method based on literature studies to examine the role of DNN in weather prediction systems. The findings indicate that DNN demonstrates strong generalization abilities, robustness to fluctuating data, and more stable predictive outputs compared to conventional statistical approaches. Thus, DNN is considered a promising component for the development of early warning systems and modern data-driven climate analysis, offering improved reliability in understanding and forecasting atmospheric conditions.

The safety and security of toll road users is a very important issue in road infrastructure management. In order to improve monitoring and response to potential dangers, smart CCTV technology can be an effective solution. This research aims to develop a smart CCTV detection system that can detect events that endanger safety, such as accidents or traffic disturbances. This system uses image processing technology and artificial intelligence to analyze CCTV footage in real-time and provide immediate warnings to security officers. Test results show that this system can detect events quickly and accurately, improving response and decision making to improve toll road safety. This system also allows for more efficient monitoring by reducing reliance on manual monitoring.    

This research is a Systematic Literature Review (SLR) aimed at analyzing the application of Artificial Intelligence (AI) technology in the management of information technology (IT) projects. This study focuses on identifying the AI technologies employed, the benefits gained, and the challenges faced in implementing these technologies. The study gathers and analyzes literature from various leading databases, including Scopus, IEEE Xplore, and SpringerLink, within the timeframe of 2015–2025. The findings reveal that AI technologies such as machine learning, predictive analytics, and natural language processing play a significant role in improving efficiency, reducing risks, and supporting decision-making in IT project management. However, challenges such as data quality, organizational resistance, and implementation costs remain major obstacles in adopting this technology. This review provides comprehensive insights into trends, benefits, and barriers associated with AI utilization, along with recommendations for more effective implementation in the future.

Stress and burnout among healthcare workers represent a global crisis with significant implications for psychological and physical health, job performance, and interpersonal skills. These conditions are linked to anxiety, depression, suicidal ideation, substance use, poor quality of life, digestive disorders, and cardiovascular diseases. Burnout is characterized by emotional fatigue, depersonalization, and reduced personal accomplishment, often caused by chronic workplace stress. Factors such as demographics, fatigue, and resilience influence its development and severity. Traditional stress management interventions, such as counselling and leave, often prove insufficient in addressing these challenges. Recent advancements in Artificial Intelligence (AI) provide innovative tools for stress and burnout management, including mobile applications offering mindfulness, meditation, and self-care resources. AI systems like IBM Watson and Google DeepMind are being tested to enhance accessibility and effectiveness in stress management. Additionally, Stress Inoculation Training (SIT), involving methods such as meditation, yoga, cognitive-behavioural therapy, and biofeedback, has been recognized as a proactive approach to mitigating stress. This review explores the factors contributing to stress and burnout in healthcare workers and evaluates interventions aimed at improving well-being and productivity, emphasizing the potential of AI and SIT in preventing and managing these conditions.

This research aims to understand the impact of the integration between artificial intelligence (AI) technologies and cyber security on administrative decisions in three aspects: (1) decision-making speed, (2) decision accuracy, and (3) decision effectiveness. A sample of 150 employees was drawn, and a survey was used to gather the required information. Data analysis was conducted using the statistical program SPSS 25, employing various statistical methods such as mean, standard deviation, correlation coefficient, and simple linear regression. The research concluded with several findings, the most important being: The integration of AI technologies and cyber security leads to improved speed, accuracy, and effectiveness of administrative decisions, The researcher recommended that institutions adopt AI technologies to enhance their cyber security systems, particularly in areas like machine learning and big data analysis.

The Next-Gen Global Health 6.0 initiative offers an integrative model employing genomics, nano-immunotherapies, and artificial intelligence (AI) to address the escalating complexity of global health issues, particularly the convergence of infectious and chronic diseases. This framework advances precision medicine by integrating real-time genomic surveillance with AI algorithms, enabling timely prediction and response to outbreaks, as well as tailored therapeutic approaches. Nano-immunotherapies play a critical role in modulating immune responses with high specificity, especially in chronic infections and diseases resistant to conventional treatments. Through these synergistic technologies, the Next-Gen Global Health 6.0 approach aims to transcend traditional healthcare boundaries, offering scalable, data-driven interventions that are adaptable to varying resource levels worldwide. Emphasizing accessibility and equity, this framework highlights the necessity for innovative health policies and interdisciplinary collaboration to optimize deployment in underserved regions, ultimately contributing to sustainable, resilient healthcare systems prepared for evolving global health challenges.

This study aims to explore the impact of supply chain automation on workers’ well-being in the sustainable industrial sector through a Systematic Literature Review (SLR) approach. The transformation driven by Industry 4.0 technologies such as artificial intelligence (AI), Internet of Things (IoT), and blockchain, has presented significant challenges and opportunities. This study identifies the impacts of automation on workers’ economic, social, and psychological aspects, including changes in skills requirements, reduction of manual employment, and its effects on mental health. In addition, this study also highlights the importance of sustainability in automation implementation, by balancing economic efficiency, environmental preservation, and social welfare. By integrating the results of studies from various literatures, this study provides recommendations for policies that support sustainability and social inclusiveness, as well as strategic guidance for industries in adopting supply chain automation sustainably.