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Big Data Analytics has gained significant popularity in recent years, with many companies integrating it into their information technology roadmaps to enhance business performance. However, surveys indicate that Big Data Analytics demands substantial resources, including technology, costs, and talent, which often leads to failures in the initial stages of implementation. This study proposes a VGG6 architecture approach, intended to provide a framework for the initial implementation of Big Data Analytics. The study's outcomes include the implementation of the VGG6 architecture for processing images of aromatic plants using Python. Furthermore, this approach enabled the development of a Minimum Viable Product (MVP) solution that adheres to general Big Data principles, such as the 3Vs (Volume, Velocity, and Variety), and encompasses key technological components: 1) Data Storage and Analysis, 2) Knowledge Discovery and Computational Complexity, 3) Scalability and Data Visualization, and 4) Information Security.

This research discusses the application of User Interface (UI) and User Experience (UX) principles in the development of hospital information systems to improve the quality of health services. The research method used involved qualitative and quantitative approaches with data collection through observation, interviews, and surveys. The results showed significant improvements in user experience, measured through access speed, satisfaction levels, and reduced user error rates. Operational efficiency was also shown to improve, especially in terms of scheduling, patient monitoring, and staff information exchange. This study concludes that implementing UI/UX can have a positive impact on user experience and operational efficiency in the context of hospital systems. Therefore, hospital system developers are advised to consider UI/UX principles as an integral strategy in the development of health information systems, in order to improve the overall quality of healthcare services

The presence of artificial intelligence (AI) technology has revolutionized efforts to protect data in offices. The challenges organizations face in maintaining information security are becoming increasingly complex as technology advances, but the benefits of AI provide an effective solution to optimize information security. In this summary, we discuss the challenges and benefits of AI in office data protection, focusing on enhancing information security.The first challenge is the increasing complexity of cyber attacks. Attackers are constantly looking for new vulnerabilities and using more sophisticated attack techniques to breach security systems. Adequate data protection is needed to address this challenge and prevent unauthorized access to critical company information. Additionally, a lack of knowledge about managing and monitoring security systems is a major challenge for many businesses.However, the use of AI to protect office data offers several advantages. First, AI's ability to quickly and accurately detect security threats aids in early detection of cyber attacks. Predictive analysis supported by AI can also detect dangerous patterns and prevent attacks before they occur. Furthermore, using AI to automate security processes can optimize operational efficiency and accountability for events that occur. AI-based security can significantly reduce the risk of data breaches and cyber attacks.The use of AI technology in office data protection is not only a supportive tool but also an innovative and efficient solution to address increasingly complex challenges in information security. We hope this overview provides a deeper understanding of the challenges and benefits of AI in protecting office data, as well as efforts to optimize information security in this digital era.