TWITTER (X) SENTIMENT ANALYSIS OF KAMPUS MERDEKA PROGRAM USING SUPPORT VECTOR MACHINE ALGORITHM AND SELECTION FEATURE CHI-SQUARE - Sari, Mutiara; Syahrullah, Syahrullah; Lapatta, Nouval Trezandy; Ardiansyah, Rizka (Informatika, Universitas Jenderal Soedirman, 2024)
Ministry of Education, Culture, Research and Technology (Kemendikbudristek) has implemented numerous policies aimed at enhancing the quality of education in the country. One of these policies is Kampus Merdeka program. The program includes various initiatives such as Teaching Campus, the Merdeka Student Exchange program, and Internship and Independent Study programs, which have gained significant popularity among students across Indonesia. However, the Kampus Merdeka program has drawn many pros and cons, with some parties supporting the initiative, but also many criticisms related to its implementation, which is considered not optimal in some educational institutions. Social media is where many of these opinions are voiced, one of the most widely used of which is twitter. In light of these circumstances, this study conducted a sentiment analysis of the independent campus program to assess public sentiment towards it. The dataset used in this research consisted of 500 tweets containing the keyword