Analisis Sentimen Pengguna X terhadap Chatgpt dengan Algoritme Naive Bayes
DOI:
https://doi.org/10.61769/telematika.v18i2.614Keywords:
X, ChatGPT, Lexicon-based, Naive Bayes, sentiment analysisAbstract
Artificial intelligence has experienced rapid growth in various sectors of modern human life. One example is ChatGPT (chat generative pre-trained transformer), which OpenAI developed. ChatGPT is capable of understanding and generating human-like text. ChatGPT is used to answer questions, create articles, generate code, and scientific journals. However, some concerns are that using ChatGPT in education may not optimally support the development of students' problem-solving and critical-thinking skills. In addition, ChatGPT may also reduce the role of workers in content creation, from writers to programmers. Therefore, analyzing public sentiment towards ChatGPT is important. In this study, sentiment analysis was conducted on users of app X, a social media platform often used to express opinions. Naive Bayes classifier was used as the algorithm to analyze the sentiment of 4,861 data collected, with 2,884 data after preprocessing. The analysis results showed positive (1,543 data), negative (318 data), and neutral (1,023 data) sentiments. The Naive Bayes algorithm provides an accuracy of 87.175043%. This research provides a more in-depth view of the community's response to ChatGPT. Such results are important to support the responsible development of this model by ensuring the validity of the information and avoiding over-reliance. This research provides a foundation for OpenAI to better develop ChatGPT according to the needs and expectations of the community.
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