Sentiment Anlysis On Customer Reviews Using Support Vector Machine and Usability Scoring Using System Usability Scale

Authors

  • Novira Azpiranda Brawijaya University, Malang, Indonesia
  • Ahmad Afif Supianto Brawijaya University Malang, National Research and Innovation Agency, Bandung, Indonesia
  • Nanang Yudi Setiawan Brawijaya University, Malang, Indonesia
  • Endang Suryawati National Research and Innovation Agency, Bandung, Indonesia
  • R. Sandra Yuwana National Research and Innovation Agency, Bandung, Indonesia
  • Arafat Febriandirza National Research and Innovation Agency, Bandung, Indonesia

DOI:

https://doi.org/10.25126/jitecs.202163330

Abstract

Al-Ghiff Steak is a restaurant located in Cirebon City that offers quality steaks at affordable prices. For maintaining a competitive Al-Ghiff Steak advantage and reputation, it is important to build a good relationship with customers and have a business strategy that considers customer opinions. However, in its implementation, Al-Ghiff Steak has difficulty when collecting and processing customer review data manually. Therefore, it is necessary to conduct sentiment analysis by utilizing Google Reviews to determine customer perspectives regarding Al-Ghiff Steak products and services. This analysis was conducted on 968 Google Review reviews from 2016 to 2020 using the Support Vector Machine (SVM) and Term Frequency-Inverse Document Frequency (TF-IDF) methods. Classification testing is done with a confusion matrix against four parameters: accuracy, precision, recall, and f1-score. SVM with TF-IDF gets accuracy value 83%, precision 64%, recall 60% and f1-score 59%. The sentiment classification result is then visualized in the form of a dashboard. We utilize the System Usability Scale (SUS) for usability testing, which produces a value of 77.5. This result achieve the Acceptable category and an Excellent rating.

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Published

2021-12-21

How to Cite

Azpiranda, N., Supianto, A. A., Setiawan, N. Y., Suryawati, E., Yuwana, R. S., & Febriandirza, A. (2021). Sentiment Anlysis On Customer Reviews Using Support Vector Machine and Usability Scoring Using System Usability Scale. Journal of Information Technology and Computer Science, 6(3), 236–251. https://doi.org/10.25126/jitecs.202163330

Issue

Vol. 6 No. 3: December 2021

Section

Articles

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