Analisis Sentimen Terhadap Review Google Maps Jogja City Mall Menggunakan Algoritma Support Vector Machine
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Putri Marceliana Aryanto
*
Universitas Teknologi Yogyakarta, Sleman,
Indonesia
- Rodhiyah Mardhiyyah Universitas Teknologi Yogyakarta, Sleman, Indonesia (*) Corresponding Author
Abstract
Sentiment analysis works with calculating the total of reviews based on given labels. Reviews that had specific labels would be classified with other reviews that had same labels. This study used Support Vector Machine (SVM) method for analysing of reviews of Google Maps users who had visited Jogja City Mall in Sleman, Special Region of Yogyakarta. In previous studies, SVM was proved several times superior in accuracy score and the accuracy of sentiment classification. SVM model for sentiment analysis in this study was successfully created with accuracy score was 84% and 85% in K-Folds testing. With the total of testing data was 20% out of 1694 data, the total amount of positive label was so much more than the total amount of negatif label. This means the rate of 4.6 stars for Jogja City Mall is relevant with the reviews that were given. The analysis of imbalance review data and the correlation between the stars rating and sentiment that were extracted may contribute to a deeper understanding of consumer behavior in the mall, providing practical implications for mall management in improving customer experience.
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