Sentiment Analysis of Brompit Application Reviews on the Google Play Store Using the Support Vector Machine Algorithm
Analisis Sentimen Ulasan Aplikasi Brompit Di Google Play Store Menggunakan Algoritma Support Vector Machine
DOI:
https://doi.org/10.21070/ups.427Keywords:
Brompit, Google Play Store, Sentiment Analysis, Support Vector MachineAbstract
Sentiment analysis is a technique to classify a document into several sentiments using text analysis methods. This research uses the dataset contained in the brompit application to classify the sentiment of the application reviews. The dataset will be grouped
into two sentiments, namely positive and negative. In this case the researcher uses the Support Vector Machine
algorithm with a dataset consisting of 3359 review data. By using the Support Vector Machine algorithm, the highest
classification result of 87,6% was obtained using the k-fold cross validation method which was obtained from the 8th
fold iteration using a RBF kernel and a ratio of training data and test data of 90:10. This proves that the application
of the Support Vector Machine algorithm in document classification is able to produce high enough accuracy.
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