Sentiment Analysis for Curriculum of Independent Learning Based on Naïve Bayes with Laplace Estimator

Curriculum changes have a significant impact on the field of education in Indonesia, especially in universities. This is because the curriculum is used as a means to achieve the goals of educational success as well as guidelines in the implementation of teaching at every level of education. This study aims to determine public sentiment regarding the implementation curriculum of independent learning (MBKM) through Twitter based on Naïve Bayes with Laplace Estimator. Tweet search results use the keywords “kurikulum mbkm” and “mbkm”. The data used in this study amounted to 2500 tweet data which will be divided into 2000 data as training data with details of 1000 positive tweets and 1000 negative tweets and 500 data as testing data. The results showed the performance of Naïve Bayes using Laplace Estimator which resulted in an accuracy value of 80.20%, precision value of 82.00%, and recall value of 79.00%. Meanwhile, the performance of Naïve Bayes without Laplace Estimator resulted in an accuracy value of 77.00%, precision value of 80.00%, and recall value of 74.00%. Naive Bayes with Laplace Estimator reached the highest value in all metrics.