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

Kamiliya Tsuroyya; Khothibulu Umam; Wenty Dwi Yuniarti; Maya Rini Handayani

doi:10.24246/aiti.v22i2.279-293

Authors

Kamiliya Tsuroyya Program Studi Teknologi Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Walisongo Semarang https://orcid.org/0009-0004-8403-8897
Khothibulu Umam Program Studi Teknologi Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Walisongo Semarang https://orcid.org/0000-0002-9403-9461
Wenty Dwi Yuniarti Program Studi Teknologi Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Walisongo Semarang
Maya Rini Handayani Program Studi Teknologi Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Walisongo Semarang

DOI:

https://doi.org/10.24246/aiti.v22i2.279-293

Keywords:

Pintu App, Sentiment Analysis, Decision Tree, Random Forest

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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