USING THE NAIVE BAYES CLASSIFIER METHOD ON SOCIAL MEDIA SENTIMENT ANALYSIS
Abstract
Social media is one of the many technological developments that greatly affect human communication and socialization systems. Most people voice their opinions through social media, with the aim that they can be heard and seen by the general public. However, the use of social media often backfires for the owners themselves due to their excessive use. In particular, this study discusses the grouping of sentiment data from Prima Indonesia University students where to seek negative and positive opinions from students as a benchmark for online learning methods carried out in the campus environment. The data grouping process uses the nave Bayes algorithm, because this algorithm has been widely used in data processing. The tests carried out in this study resulted in an accuracy of 68% of the dataset selected as the data training process. This results in a classification of new data to find out a sentiment on students belonging to the negative or positive class.
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References
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