Synergizing Aptitude, Interest, and Intelligence: A Systematic Approach to Career Selection Decision-making in Higher Education

The process of making informed career decisions during higher education holds great significance, both for individuals and society at large. Careful evaluation of factors such as aptitude, interests, and intelligence is essential when selecting a suitable career path. The impact of this choice is far-reaching, influencing professional paths and contributing to personal contentment and societal advancement. This study delves into the pivotal roles played by aptitude, interest, and intellect in shaping students' career choices, particularly within the realm of higher education. The primary objective of this paper is to examine existing research on the process of career decision-making within the context of higher education. By establishing connections among aptitude, interest, and intelligence, the study aims to offer insights into an effective framework for supporting career decision-making approaches, thereby guiding students toward careers that align with their aspirations and yielding successful outcomes.To achieve this goal, a fuzzy-based technique is used to aid students in making well-informed career selections subsequent to completing their higher education. The system incorporates interest, intellect, and aptitude as input variables, encompassing a comprehensive array of eleven inputs, including nine specific aptitude dimensions. The ultimate output variable encompasses the chosen career option. The synthesis of scores from diverse aptitude, interest, and intelligence assessments serves as the basis for determining the most suitable career path. Employing the Mamdani technique within a fuzzy logic framework facilitates a thorough analysis of these inputs, offering pragmatic career alternatives congruent with individual skill sets. In order to gauge the system's efficacy, a comparative analysis is conducted between the proposed fuzzy-based approach and the traditional manual methodology employed by career counselors. The system's effectiveness is tested by comparing its results with those of the counselor. A high degree of positive correlation (0.988) is observed between the two results, indicating the system's good efficiency. The results of this correlation reveal that the fuzzy-based approach demonstrates a high degree of similarity to the outcomes generated by human counselors, thus validating its effectiveness as a valuable tool for aiding students in their career decision-making process.