Analisis Sentimen Tanggapan Pengguna Media Sosial X Terhadap Program Beasiswa KIP-Kuliah dengan Menggunakan Algoritma Support Vector Machine (SVM) - Amelia, Ika; Sugiyono; Sarimole, Frencis Matheos; Tundo (Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh, 2024)
The KIP-Kuliah Scholarship is an Indonesian government program which aims to provide access to higher education for students from underprivileged families. This program has become a hot topic of discussion on social media, including social media. The object of research is comments on X's social media regarding the KIP-College Scholarship. Research methods include crawling data using google collabs, data preprocessing, Support Vector Machine model training, and model evaluation using RapidMiner. The research results show that the Support Vector Machine model is able to classify sentiment with an accuracy of 86.27%, but there is a bias towards negative sentiment. The majority of public responses are negative, often regarding misuse of scholarships. The suggestions given include collecting more balanced data, using dataset balancing techniques, implementing more complex models, and more in-depth evaluation to improve model performance. It is hoped that this research will provide input for the government in improving the KIP-College Scholarship distribution mechanism so that it is more targeted and reduces the potential for abuse.