This study aims to analyze the relationship between the number of videos, views, positive comments, negative comments, and neutral comments with the number of new students at higher education institutions during 2021–2024. The data were obtained from three sources: (1) quantitative data on the number of new students from LLDIKTI, (2) data on the number of videos and views from YouTube, and (3) sentiment data from comments classified using the BERT algorithm into positive, negative, and neutral categories. The research employed a quantitative approach using the Random Forest regression model to evaluate the influence of independent variables, namely, the number of videos, views, and sentiment on the dependent variable, which is the number of new students. The analysis results showed a significant positive correlation between the number of views and positive sentiment with the number of new students, while negative sentiment had a negative correlation. However, this relationship is not entirely linear, as indicated by an R² value of 32.1%, suggesting the possibility of other influencing factors. Spearman correlation analysis also confirmed a strong relationship between the number of video, views and positive sentiment with the number of new students, with a correlation value of 0.7-0.8. These findings highlight the importance of digital marketing strategies, such as increasing publications, views and creating content that generates positive sentiment, to attract more new students.
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