Journal of Dinda : Data Science, Information Technology, and Data Analytics
Vol 5 No 1 (2025): February

Comparison of Sentiment for Midi Kriing and Alfagift Apps Using SVM with TF-IDF Weighting

Diva Ananda Putra (Universitas Pendidikan Ganesha)
Elma Regina Nababan (Unknown)



Article Info

Publish Date
28 Feb 2025

Abstract

The advancement of information and communication technology has impacted various aspects of life, including shopping. With increasing internet access, online shopping apps have become a primary tool for consumers. Alfa Group, a major player in the retail industry, has launched two online shopping apps, Midi Kriing and Alfagift. This study aims to compare user sentiment for these two apps based on data from Google Play Store.Using the Support Vector Machine method with TF-IDF weighting, this research analyzes 2,000 reviews from each app. The data, collected from Google Play Store, was divided into 80% for training the model and 20% for testing it. The results indicate that Midi Kriing has an overall accuracy of 87%, while Alfagift has an overall accuracy of 85%. Both apps demonstrate strong performance in sentiment detection, but Midi Kriing is slightly superior in overall accuracy. These findings provide insights into user satisfaction with the apps and can help consumers determine the best online shopping app from Alfa Group. Additionally, the results can be used by Alfa Group to enhance the services of both apps in the future.

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Journal Info

Abbrev

dinda

Publisher

Subject

Computer Science & IT

Description

Journal of Dinda : Data Science, Information Technology, and Data Analytics as a publication media for research results in the fields of Data Science, Information Technology, and Data Analytics, but not implicitly limited. Published 2 times a year in February and August. The journal is managed by ...