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- W3199103414 abstract "Student’s perception toward department performance can be crucial, therefore, it can be used to evaluate the department outcome and take an immediate action to improve its management. This study applies sentiment analysis and topic modeling to the student’s reviews of college department at Politeknik Caltex Riau in order to mine student’s perception for seven college departments performance. Sentiment analysis with Support Vector Machine (SVM) is employed to obtain student’s sentiment. There are 3 types of sentiments to be analyzed; positive, negative and neutral. Topic modeling with Latent Dirichlet Allocation (LDA) is also carried out to get some important keywords in the student’s reviews. Our experiments show that Positive is the most prominent sentiment in the student’s reviews while LDA reveals some important topics toward preferences." @default.
- W3199103414 created "2021-09-27" @default.
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- W3199103414 date "2021-08-25" @default.
- W3199103414 modified "2023-09-23" @default.
- W3199103414 title "Mining Student's Reviews to Obtain Their Perception toward College Department Performance" @default.
- W3199103414 hasPublicationYear "2021" @default.
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