Abstract
This study aims to process and classify an opinion (Opinion mining), opinion is a subjective statement that reflects public sentiment or perception of the entity or activity. Most opinions has not been managed well, if The Opinions properly managed will provide important information can be used to make improvements toward better at an activity or program. This study focuses on the processing of opinions that come from public opinion In Lamongan against LGC program which includes cleanliness, green and financial. The study was divided into two phases, namely the training process to produce data (dataset) to perform the classification process and the subjective (datates). Both processes are aimed to extract attributes and object components that have been commented upon in any document and to determine whether positive or negative comments. The results of the subjective test classification using Multinomial Naive Bayes algorithm has a success rate above 80% classification accuracy when it is matched with the manual classification
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