Abstract

In this paper, I discuss how artificial intelligence has become central to the formulation of ethical policies concerning data privacy. With the advancement of technology, customers’ privacy and information security concerns have come into focus and require stringent measures for the usage of data. This paper aims to analyze how AI improves data protection mechanisms for security risks pertaining to personally identifiable information while advocating for the transparency of handling personal information. Drawing evidence from the current global issues involving data privacy, the practical use of AI in cyber defense, and the social issues arising from AI technologies, this paper establishes that while developing ethical frameworks, there exists the need to continuously assess and update the ethical standards. Finally, the study confirms how AI should be incorporated within the context of data privacy to build confidence and ensure better accountability in the growing data era.

This paper explores the role of fuzzy logic in the assessment of student performance in local high school, Badr, Libya, positing that it offers a more flexible and accurate alternative to traditional categorization methods of academic achievement. Conventional assessment tools, such as standardized test scores and GPAs, often yield a distorted and overly simplistic view of student performance. Utilizing a mixed-methods research design, this study compares the performance, attendance, and self-reported satisfaction of students assessed through fuzzy logic with those evaluated by traditional methods. The results demonstrate that students assessed using fuzzy logic achieved higher average scores and expressed greater satisfaction with the assessment process. Additionally, educators employing fuzzy logic provided more detailed and constructive feedback, enriching the learning experience. Thus, this research indicates that fuzzy logic can effectively mitigate the shortcomings of traditional assessment methods, enhancing the recognition of diverse student abilities. The findings advocate for the integration of fuzzy logic in educational assessment practices to promote inclusivity and improved learning outcomes.

Abstract

Nowadays, the information system methodology is lifeblood of any successful project. The success is based on the quality of information and its technology over the globe. This could rely on the development and operation of computer based systems. To assure that you achieved the goal, there should be a perfect and ideal selection of the methodology, and quite simply it matches your needs. However, there should be some researchers have been written about NIMSAD, SSADM and ETHICS and with no doubt much will be written in the future. The purpose of this paper is to conducting a comparison between two methodologies effectively. Besides, the implementation of NIMSAD framework will take an integral part in this paper. Consequently, the implementation will illustrate the strength and weakness points of both methodologies. Eight principals' steps of NIMSAD will be examined to demonstrate various aspects of EHTICS and SSADM methodologies. This, however, will help to ensure the efficient performance which is the main goal of this work.