Abstract: Background: Subjectivity detection is the process of identifying whether a sentence contains an opinion or not. Subjectivity detection is considered as a prior task before conducting sentiment analysis in which the error rate could be decreased. Education is one of the domains that brought many attentions where the student reviews are being analysed to enhance the learning process. Usually, student reviews contain several objective sentences in which the students are expressing facts about their activities. Therefore, it is necessary to accommodate subjectivity detection before classifying polarity of these reviews. Objective: This study proposes a subjectivity detection method using specific features for identifying opinionated sentences. Methodology: Consequentially, a sentiment classification based on lexicon-based and Support Vector Machine (SVM) classifier is being conducted to classify the polarity. Results: Results showed an outperformance of classifying polarity when the proposed subjectivity detection method is used prior. Conclusion: It concluded that superior performance of sentiment classification when using subjectivity detection as a prior task.