Sentiment Analysis of Students on the Use of ChatGPT in Learning Using SVM
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Abstract
The development of artificial intelligence (AI) has transformed the way students learn, one of which is through the utilization of ChatGPT as a digital learning assistant. This study explores students' perceptions and sentiments regarding the use of ChatGPT in learning activities by implementing the Support Vector Machine (SVM) algorithm. Data was collected from 41 respondents via a Google Form questionnaire containing a Likert scale (1-5) and open-ended questions about their experience using ChatGPT. After undergoing text pre-processing, the data was classified into three sentiment categories: positive, neutral, and negative. The analysis results show that the SVM model achieved an accuracy of 72.88%, indicating the model's capability in recognizing language patterns that represent student opinions. The majority of respondents showed positive sentiment towards ChatGPT as it was considered helpful for understanding learning materials, although some expressed concerns about the potential for over-reliance on AI technology.
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