Aiti: Jurnal Teknologi Informasi
Vol 22 No 2 (2025)

Klasifikasi sentimen pada ulasan pengguna aplikasi Cryptocurrency di Google Play Store menggunakan algoritma Decision Tree

Tsuroyya, Kamiliya (Unknown)
Umam, Khothibulu (Unknown)
Yuniarti, Wenty Dwi (Unknown)
Handayani, Maya Rini (Unknown)



Article Info

Publish Date
30 Sep 2025

Abstract

Cryptocurrency has become a trend in digital investment. The Pintu application exemplifies the use of digital technology for trading cryptocurrency assets. Reviews from the Google Play Store serve as an important source of data to understand the opinions of Pintu application users. This study focuses on investigating the sentiment analysis of Pintu application users sourced from the Google Play Store by implementing the Decision Tree and Random Forest algorithms. The approach used involves collecting data from the Google Play Store, which contains user reviews and ratings. The data is then labeled as positive or negative and cleaned, processed, and analyzed using Decision Tree and Random Forest algorithms. The results of the study showed that the accuracy of the Decision Tree reached 0.90, while the Random Forest achieved an accuracy of 0.88. From these results, it can be concluded that the Decision Tree is superior in classifying text mining with high accuracy. The difference between the two methods is insignificant in terms of accuracy, specifically for Decision Tree, with an accuracy of 0.90, Precision of 0.91, and recall of 0.95, and Random Forest, with an accuracy of 0.88, precision of 0.87, and recall of 0.95. User sentiment analysis of the Pintu application provides a positive response to using the Pintu application.

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Journal Info

Abbrev

aiti

Publisher

Subject

Computer Science & IT

Description

AITI: Jurnal Teknologi Informasi is a peer-review journal focusing on information system and technology issues. AITI invites academics and researchers who do original research in information system and technology, including but not limited to: Cryptography Networking Internet of Things Big Data Data ...