CAREER NAVIGATOR: EMPOWERING GRADUATES THROUGH DATA INSIGHTS
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UNIVERSITI MALAYSIA SARAWAK
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Career Navigator: Empowering Graduates Through Data Insights addresses the persistent challenge of unemployment and underemployment among Computer Science (CS) and Information Technology (IT) graduates. These challenges arise from the mismatch between academic training and the rapidly evolving demands of the technology sector. Current career guidance systems often rely on generalized recommendations that fail to consider the unique qualifications, technical skills, and career aspirations of CS and IT students, leading to job mismatches and dissatisfaction. This project develops a web-based recommender system that employs a content-based filtering algorithm with a customizable threshold mechanism to provide tailored job recommendations for CS and IT graduates. User data, including academic background, technical skills, and personality traits, are matched with job postings retrieved from dynamic databases. The system incorporates a personality assessment to enhance job alignment, categorizing users as introvert, extrovert, or ambivert. The methodology involves phases such as data collection, preprocessing, feature extraction, algorithm development, recommendation generation, and iterative refinement through user feedback. The findings demonstrate that integrating academic, technical, and psychological attributes into job recommendation systems significantly enhances their accuracy and relevance. The system empowers graduates to explore personalised career paths, bridging the gap between their qualifications and the demands of the tech industry. By addressing gaps in traditional systems, such as lack of personalization and localization, this project offers a scalable solution for improving the employability of Malaysian CS and IT graduates. This study contributes to the field by providing a data-driven, user-centric approach to career guidance, addressing the unique needs of CS and IT graduates. It highlights the importance of combining academic qualifications, technical expertise, and personality insights to deliver precise and actionable job recommendations. The proposed system represents a significant step toward improving job search experiences and aligning education with employment in the fast-evolving technology landscape.