Analisis Sentimen Terhadap Kualitas Pelayanan Aplikasi In-Drive Menggunakan Metode Naive Bayes Classifier
- Muhammad Sidiq Bagus Prakoso Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta, Indonesia
-
Isa Faqihuddin Hanif
*
Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta,
Indonesia
(*) Corresponding Author
Abstract
This research analyzes user sentiment towards the service quality of the In-Drive application using the Naive Bayes Classifier method. A total of 15,000 reviews from the Google Play Store were collected using web scraping techniques from the results of sentiment analysis of the data, 9,665 negative sentiments and 5,335 positive sentiments were found. The data went through a pre-processing stage including cleaning, case folding, stopword removal, tokenizing, and stemming. Naive Bayes algorithm was used to classify the reviews into positive and negative sentiments. Evaluation using the confusion matrix resulted in 76.56% accuracy, 78.26% precision, 87.69% recall, and 82.71% F1 score. These results indicate that most reviews are negative. This research is expected to help In-Drive app developers understand user experience and improve service quality based on automatically available reviews.
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