Analisis Sentimen Opini Masyarakat terhadap Film Horor Indonesia Menggunakan Metode SVM dan TF-IDF - Br Sinulingga, Jesica Emarapenta; Sitorus, Hizkya Cesar Kayika (Jurnal Manajemen Informatika JAMIKA, 2024)
In the digital era, public opinions regarding Indonesian horror films often receive significant attention on social media platforms. The objective of this study is to assess the perspectives and sentiments expressed by the public concerning Indonesian horror films. The Support Vector Machine (SVM) method along with Term Frequency-Inverse Document Frequency (TF-IDF) is utilized as the primary analytical tool in this research. Issues and public viewpoints regarding horror films are extracted from social media platforms to identify both pros and cons. Employing the SVM method in conjunction with text representation using TF-IDF is expected to provide comprehensive insights into the emotional responses of the public toward specific film genres. The analyzed dataset comprises 2281 entries. Subsequently, the application of the Support Vector Machine (SVM) algorithm is employed for text classification, coupled with word weighting using TF-IDF. The outcomes of this analysis exhibit an accuracy of 82.51%, a precision of 5.28%, a recall of 7.26%, and an F1 Score of 6.12%. This study demonstrates the efficacy of the SVM and TF-IDF methods in classifying public sentiment toward Indonesian horror films and has the potential to provide insights into the social impact and reception of film works within the entertainment industry.