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Andreansyah, Hylmi
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Computer Science & IT Decision Sciences, Operations Research & Management

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Klasifikasi Sentimen Positif dan Negatif pada Ulasan Aplikasi Gojek Menggunakan Metode Support Vector Machine (SVM) Andreansyah, Hylmi; Sunardi, S
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.739

Abstract

Gojek is an Indonesian decadent company seeing tremendous growth. Given the growing user base of the Gojek application, it is imperative for the firm to consistently maintain and enhance its services. Sentiment analysis is an efficient method for quickly collecting valuable textual information from a vast quantity of data. The objective of this study is to conduct sentiment analysis on comments from users of the Gojek application on the Google Play Store. The study procedure involves many stages: data gathering, data labeling, data preprocessing, feature extraction, and sentiment classification using the Support Vector Machine (SVM) algorithm. The dataset used consists of user comments from the Gojek application on the Google Play Store, collected via Kaggle, spanning from January to March 2023. This research shows that using the Support Vector Machine method to classify Gojek application user sentiment provides quite high accuracy results, with the highest value in the proportion scenario of 80% training data and 20% test data (accuracy 0.676).
Co-Authors S Sunardi