| dc.description.abstract |
Choosing a college major is an important decision that will determine one's future career.
However, many students find it difficult to choose a major that suits their interests and
talents. This study developed a college major recommendation system called CareerPathAI
that uses machine learning algorithms to help students make the right decision.
The system is built using a Random Forest Classifier approach that analyzes ten key
parameters: logical reasoning, creativity, communication skills, data analysis, interest in
biology, social awareness, interest in technology, design skills, economic understanding,
and interest in the humanities. Each parameter is assessed through an interactive
questionnaire with “yes” or “no” answers, which are then converted into numerical data for
processing by the machine learning model.
The system implementation uses Flask as the backend to handle model predictions and
HTML/CSS/JavaScript for a responsive user interface. The system supports two languages
(Indonesian and English) and provides an engaging user experience with modern design,
SVG animations, and a progress bar showing the questionnaire completion progress.
The model was trained using a dataset covering ten popular majors: Computer Science,
Visual Communication Design, Information Systems, Communication Studies, Industrial
Engineering, Nursing, Medicine, Architecture, Management, and International Relations.
Each major prediction is accompanied by recommendations for the top three universities in
Indonesia for that major.
Test results show that the system is capable of providing accurate major recommendations
based on users' interests and talents. The intuitive and responsive interface allows users to
easily access the system from various devices. The system can be further developed by
adding more parameters, majors, and universities to improve the accuracy and scope of
recommendations.
CareerPathAI provides a practical solution to help students choose a major that aligns with
their characteristics, thereby increasing their chances of academic and career success in the
future. |
en_US |