Analisis Sentimen pada Ulasan Aplikasi Maxim di Google Play Store dengan K-Nearest Neighbor

 (*)Restu Ramadhan Mail (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)
 M Afdal (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)
 Inggih Permana (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)
 Muhammad Jazman (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)

(*) Corresponding Author

Abstract

Online transportation is an innovation in emerging technology to solve various problems that arise in conventional public transportation such as in the ease of ordering, availability, and digitization of payments. Maxim is an online transportation company that has been operating since 2018 in Indonesia. As the number of users of the maxim application increases, demands for the quality of application service also increase. In the Google Play Store, reviews and information about an app are stored in text form. One of the processes of extracting text mining information in the text category is Sentiment Analysis to see the tendency of a sentiment or opinion whether it is positive, neutral, or negative at the Maxim application user reviews. The sentiment classification process using the K-NN algorithm produces accuracy, precision, and recall of 90.23%; 90.23%; and a recall value of 72.38% with an experiment using 90% training data, 10% test data, and a value of k = 5.

Keywords


Google Play Store; K-Nearest Neighbor; Maxim; Sentiment Analysis; Text Mining

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Copyright (c) 2023 Restu Ramadhan, M Afdal, Inggih Permana, Muhammad Jazman

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