The Comparison of Efficiency on The Analysis of Satisfaction on Teaching Performance using Sentiment Analysis by Ensemble Technique
Keywords:
Sentiment analysis, Text mining, Ensemble techniqueAbstract
Nowadays, the educational institutions emphasize the evaluation of the teaching performance of teachers. In addition to direct assessments, indirect assessments were conducted by surveying the satisfaction of learners using questionnaires. The analysis of closed-ended question data in the questionnaire can be easily done. But open-ended questions can be difficult, complex and may not be accurate due to bias from the data analyst. In this study, the sentiment analysis was used to analyze 1,577 comments classified to satisfaction polarity and compare the efficiency of classification by using ensemble techniques such as Vote, Bagging and Random Forest with standard techniques such as Decision Tree, Naïve Bayes and K-NN. The results showed that the Vote ensemble technique was the most effective.
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