Analisis Sentimen Ulasan Pengguna Aplikasi Alfagift Menggunakan Random Forest
DOI:
https://doi.org/10.14421/jiska.2025.10.2.158-170Keywords:
Sentiment Analysis, Alfagift, Random Forest, Text Mining, ReviewAbstract
Alfagift is a mobile application developed by Alfamart to support online ordering, featuring promotions, transactions, ordering, and delivery from the nearest point based on the consumer’s address. User feedback on the Google Play Store reveals mixed sentiments, including both positive and negative responses, which developers can use as material to improve the application’s quality. This study focuses on assessing the sentiment of Alfagift app user reviews using the Random Forest algorithm. A total of 4,379 review data points were collected from the Google Play Store and grouped into two categories: positive and negative sentiment. The research steps include data collection, data labeling, data preprocessing, word weighting, dividing the data into training and testing sets, implementing the Random Forest algorithm, and model evaluation. The test results show that the Random Forest algorithm achieves an accuracy of 97.6% and an AUC of 0.98, which falls into the category of excellent classification. This research is expected to contribute to application developers’ understanding of user perceptions, enabling them to improve application quality and increase overall user convenience.
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