ANALISIS SENTIMEN ULASAN APLIKASI DEEPL PADA GOOGLE PLAY DENGAN METODE SUPPORT VECTOR MACHINE (SVM)

ANALISIS SENTIMEN ULASAN APLIKASI DEEPL PADA GOOGLE PLAY DENGAN METODE SUPPORT VECTOR MACHINE (SVM)

Sentiment Analysis, DeepL, SVM,Python

n the era of globalization and technological advances, the growth in the use of mobile applications is experiencing rapid development. Understanding the level of user satisfactionand dissatisfaction with mobile applications is very important. One of the very popular online translator applications on the Google Play Store is DeepL which uses artificial intelligence technology to translate languages. DeepL has become a very useful tool for individuals and organizations in overcoming language barriers. This research aims to conduct sentiment analysis on user reviews of the DeepL application on the Google Play Store platform, using the Support Vector Machine classification method. The Support Vector Machine (SVM) classification method is one of the classification approaches in the realm of guided learning in data mining. The advantage of SVM lies in its ability to handle nonlinear and high-dimensional input data by utilizing kernel functions. Data collection was carried out using Web Scraping techniques using Python. The results of this research show an accuracy rate of 91%, which reflects how well the Support Vector Machine (SVM) model is at classifying data. In this research, it is known that the model has a high level of precision, especially in the 'Positive' category of 94%, which shows the model's ability to accurately recognize data that is included in positive sentiment

Septi Putri Azzahra1(*), Yohanes Agung Apriyanto2, Andri Wijaya3

https://ojs.itb-ad.ac.id/index.php/JUSIN/article/view/2368/468

Universitas Katolik Musi Charitas,Palembang

2023

Fajar bagus W

PDF

Indonesia

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