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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.

Artificial Intelligence (AI) is quickly becoming a game changer in the way businesses build and manage their strategies. This article explores how AI is helping organizations make faster and smarter decisions, streamline operations, and spark innovation across various industries. With the ability to process massive amounts of data, AI tools can uncover valuable insights about market trends and customer behavior, allowing companies to respond more accurately and stay ahead of the competition. From machine learning and generative AI to natural language processing and digital twins, these technologies are transforming everything from internal workflows to how businesses connect with customers. The article also offers a practical roadmap for adopting AI in a business setting, covering steps like evaluating readiness, running pilot projects, and measuring success through return on investment (ROI). It emphasizes the need for strong data infrastructure, skilled teams, and a culture that supports innovation and data-driven thinking. Challenges such as algorithmic bias, data privacy, and internal resistance to change are also addressed. Real-world examples from banking, retail, and manufacturing show how AI can deliver real impact improving efficiency, increasing customer satisfaction, and driving business growth. Ultimately, embracing AI isn’t just about keeping up with technology it’s about shaping the future of smart, strategic, and ethical business.

Teachers are under increasing pressure to deliver personalized, standards-aligned instruction while managing time constraints and rising workloads. Traditional lesson planning often limits creativity and adaptability due to its complexity and repetitive demands. In response, Artificial Intelligence (AI) has emerged as a promising tool to support instructional planning. This study highlights how AI enhances teacher efficiency, simplifies administrative tasks, and supports differentiated, data-driven instruction. However, these benefits require thoughtful and responsible integration. AI adoption must include safeguards for data privacy, ensure algorithmic transparency so teachers understand the basis of system recommendations, and actively mitigate systemic bias that may disadvantage certain learner groups. Most importantly, teachers should remain actively involved in reviewing and adapting AI-generated content to preserve professional judgment and uphold pedagogical integrity.

Artificial Intelligence (AI) is increasingly used in financial accounting to improve decision-making effectiveness. This research analyzes the role of AI in supporting data-driven decision making and identifies challenges in its implementation. Using a qualitative approach with the Systematic Literature Review (SLR) method, this study reviewed 41 relevant articles from national and international journals. The results showed that 28 studies supported the effectiveness of AI in improving financial decision-making by automating transaction recording, enabling algorithm-based predictive analysis, and detecting financial anomalies. AI enables companies to respond faster to market changes, increase transparency of financial reports, and reduce human errors in accounting processes.However, 13 studies highlighted challenges such as technological complexity, limited transparency in decision-making, algorithmic bias, and organizational readiness. In addition, evolving regulations are an obstacle to ensuring optimal use of AI while minimizing ethical and legal risks. The success of AI in financial decision-making depends on infrastructure readiness, regulatory support, and human resource competencies. Without a well-planned strategy, AI may pose new challenges that hinder its effectiveness. Therefore, this study provides insights into the optimal AI implementation strategy to ensure that this technology improves the accuracy and transparency of decision making while maintaining financial accounting accountability.

In the era of artificial intelligence (AI), technology is growing rapidly and changing the way businesses are run. AI enables automation, big data analysis, and increased operational efficiency. However, this development also raises various ethical issues that companies need to pay attention to so as not to harm consumers, society, and the environment. This study explores the paradigm of artificial intelligence in the context of business ethics, focusing on its impacts, challenges, and potential benefits in the business world. This study uses a systematic literature review approach from various reputable sources. The article criteria include literature published from 2019 to 2024 with the theme of business ethics in the AI era, and other articles relevant to this study. Based on the search, 15 articles were determined that were relevant to the predetermined criteria. The results of the study found that in this study, AI is not only a technical tool to improve operational efficiency, but is also able to redefine business ethics in the modern era. AI offers great potential to overcome traditional ethical challenges and create new paradigms in business decision making. However, this opportunity is also accompanied by significant challenges, such as algorithmic bias, data privacy, and lack of regulation. This discussion will review the role of AI in business ethics, the benefits it brings, the challenges it faces, and the steps that can be taken to optimize the ethical use of AI.