Dinamika Sentimen Komunikasi Mahasiswa dan Dosen dengan Pemanfaatan Analisis Pesan Whatsapp Akademis Menggunakan Machine Learning

Abstract

Communication is the process of exchanging information, ideas, thoughts, and feelings between individuals or groups through the use of words, signs, or actions. This process can take place verbally or non-verbally and involves various media and channels, such as face-to-face conversations, writing, gestures, facial expressions, and digital technology. This research was conducted at STMIK Kaputama Binjai, namely the WhatsApp group between lecturers and students. This study uses the Support Vector Machine (SVM) method. SVM is a type of supervised learning machine learning that requires sample data. Support Vector Machine (SVM) is an algorithm developed by Boser, Guyon, and Vapnik in 1992. Support Vector Machine (SVM) has a concept that is combined with previous computational theories. This method can transform training data into higher dimensions using non-linear patterns. The results of the Support Vector Machine method classification with a total of 16 positive sentiments, 40 neutral sentiments and 71 negative sentiments. Accuracy value 67%, margin error 39%. Positive prediction precision 75%, neutral prediction precision 83% and negative prediction precision 88%..