Sentiment Analysis Analysis of E-Wallet Sentiments on Google Play Using the Naive Bayes Algorithm Based on Particle Swarm Optimization

Analisis Sentimen E-Wallet Pada Google Play Menggunakan Algoritma Naive Bayes Berbasis Particle Swarm Optimization

  • Suwanda Aditya Aaputra stimik nusa mandiri
  • Didi Rosiyadi Pusat Penelitian Informatika LIPI
  • Windu Gata STMIK Nusa Mandiri
  • Syepry Maulana Husain Universitas Muhammadiyah Tangerang
Keywords: Particle Swarm Optimization, Naive Bayes Classifier, E-Wallet, OVO


Increasingly sophisticated technology brings various conveniences both in transportation, information, education to the convenience of transactions in shopping, such as the development of E-wallet can now be easily done using a smartphone. From a number of e-wallet products, researchers took a case study, which is OVO product, which is currently being discussed by many groups, especially in the capital of Jakarta today. Customers or clients who are not satisfied with the services or products offered by a company will usually write their complaints on social media or reviews on Google play. However, monitoring and organizing opinions from the public is also not easy. For this reason, we need a special method or technique that is able to categorize these reviews automatically, whether positive or negative. The algorithm used in this study is Naive Bayes Classifier (NB), with the optimization of the use of Particle Swarm Optimization Feature Selection (FS). The results of cross validation NB without FS are 82.30% for accuracy and 0.780 for AUC. Whereas for NB with FS is 83.60% for accuracy and 0.801 for AUC. Very significant improvement with the use of Feature Selection (FS) Particle Swarm Optimization.



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How to Cite
Aaputra, S. A., Didi Rosiyadi, Windu Gata, & Syepry Maulana Husain. (2019). Sentiment Analysis Analysis of E-Wallet Sentiments on Google Play Using the Naive Bayes Algorithm Based on Particle Swarm Optimization. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 3(3), 377 - 382.
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