<![CDATA[In recent years, there has been little systematic mapping of trends and popular topics in student final projects, particularly in the field of Information Technology at Mercu Buana University. This is important because identifying trends can provide insight into the direction of scientific development and student research interests. This study aims to analyze the dominant trends and topics of the past few years in the final projects of Information Technology students at Mercu Buana University. The research object consists of a collection of titles and abstracts of student final projects from 2019 to 2024, totaling 1677 datasets. The data was collected through internal faculty documentation and compiled into a text-based dataset. The analysis process included the stages of preparation, text pre-processing, feature extraction, and the application of two topic modeling methods with BERTopic and LDA. BERTopic uses transformer-based representation and semantic clustering, while LDA utilizes a probabilistic distribution approach. The evaluation was conducted by comparing topic coherence and prediction accuracy to assess the quality and relevance of the results produced by each method. The results showed that there were 15 main topics. Model evaluation was conducted using a coherence score of 0.4 for LDA with an accuracy rate of 100%, while BERTopic had a coherence score of 0.39 with an accuracy rate of 86.01%.]]>
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