AbstractThis project attempts to assist educators in analysing the sentiment of Malay social media
posts. The output from the sentiment can be used to enhance their teaching and learning
activities. In this project, training and testing data was acquired from Husein in 2018, the
Malay Stopwords List that used in data preprocessing stage was based on the research of
Fatimah Ahmad (1995). All datasets need to be prepared using preprocessing, including
tokenization, stop word removal, lower casing, removing numbers, and removing
punctuations. Then the TF-IDF vectorization method was used. In this project, we
implemented Support Vector Machine (SVM). The performance of trained models were
evaluated using Confusion Matrix and Evaluation Matrix. From the experiment this project
tends to produce 93% accuracy, 92% for prediction and 92% for recall...