Utilization Of Sentiment Analysis Using The Data Science Approach To Improve Customer Satisfaction

atmadji, Ery Setiyawan Jullev and Anita Mukhlisoh, Nanik and Ahmad Sultoni, risqi (2019) Utilization Of Sentiment Analysis Using The Data Science Approach To Improve Customer Satisfaction. In: Proceeding of the 2nd International Conference on Food and Agriculture. P3M Politeknik Negeri Jember. ISBN 978-602-14917-9-9

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Abstract

One of the biggest problem for customer satisfaction is how to understand the user need and the user point of view, to make it visible social media is giving huge impact especially tweeter comment . However, the number of comments submitted is very large and become difficulty to analyse. Besides the comment data on Twitter is an unstructured type of data so that if processing uses a relational database engine the results obtained are not optimal. To deal with these problems, a big data approach is needed in data extraction combined with the comment data processing model. This study uses a combination of big data in data processing and lexicon based to analyse customer comments. Data processing using big data especially with the NoSQL approach is very effective and efficient in conducting searches on unstructured data because the search for big data is based on meta text rather than cardinality between data. While the lexicon based method used depends on the completeness of the dictionary used. The purpose of this study is to analyse comments and share whether they have positive, negative, or neutral sentiments so that they can be used as parameters in decision making in an organization.

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