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Abstract

In October 2022, there were many cases of children suffering from acute kidney failure due to harmful chemical compounds detected in the history of children's cough medicine use. The statement caused controversy and became a conversation on social media, especially Twitter. Exploring this opinion can lead to a decision that can be applied in machine learning and sentiment analysis, namely support vector machines (SVM). The purpose of this research is to find out the sentiment of the community towards drugs that cause acute kidney failure in children and see the performance of the support vector machine algorithm. The data used was 1128. Based on the results of the study, the community responded negatively to this topic, as evidenced by the fact that the negative sentiment obtained was greater than the positive sentiment, and the support vector machine algorithm with a linear kernel performed very well, as evidenced by the excellent accuracy value of 91%.

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Salsabilla, T. R., & Nunik Pratiwi. (2024). Penerapan Support Vector Machine Untuk Analisis Sentimen pada X (Twitter) Mengenai Obat Penyebab Gagal Ginjal Akut pada Anak. Jurnal Teknik Informatika Dan Komputer, 3(2), 67–74. https://doi.org/10.22236/jutikom.v3i2.16892
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