The results indicate that the Random Forest algorithm performs well in automatically classifying user sentiment in mobile banking application reviews and can be effectively utilized as a tool to support user satisfaction analysis.
The analysis of feature importance shows that positive sentiment is dominated by words related to delivery speed and price, while negative sentiment is dominated by complaints about system errors, sellers, and refund processes, which can be used by application managers to prioritize service improvements.
Sopi Sapriadi, Rahmatia Wulan Dari, Y. Eirlangga· Jurnal Teknologi Dan Sistem...· 0 citations
Overall, the study confirms that Bi-LSTM is a suitable deep learning approach for sentiment classification of application reviews and offers meaningful insights that can support Duolingo developers in evaluating user opinions and enhancing application quality.
Muhammad Nasrullah, Abdul Azis, Intan Mila Hakim· JURNAL ILMIAH SAINS TEKNOLOG...· 0 citations
The rapid development of digital technology has driven the increasing use of mobile applications in the retail sector, one of which is the Alfagift application developed by PT Sumber Alfaria Trijaya Tbk. User reviews on Google Play Store contain valuable information regarding user satisfaction and complaints, yet their...
Nazwa Asyifa, S. Susanto· Jurnal Teknologi Informasi d...· 0 citations
Abstract: The Digital Population Identity (IKD) application allows citizens to access population documents electronically. Service evaluations can be found in user reviews on the Google Play Store, but manual analysis is challenging due to their large and unstructured volume. This study analyzes the sentiment of IKD us...
Atiqa Auliana Fitri, Y. Yuhandri, Rini Sovia· Journal of Science and Socia...· 0 citations
Investigation of user sentiment toward the Threads app through review classification indicates that the method used is capable of identifying user opinions and can be used as a basis for evaluating improvements in app service quality.
Consumer reviews on digital platforms can be used to identify customer perceptions of food quality, service, price, and restaurant comfort. This study used 1,006 reviews from 18 restaurants in Mataram City collected through web scraping from TripAdvisor. After data cleaning and selection, 780 reviews were used as the f...
Ameylan Verina Tabun, Hairani Hairani, Dadang Priyanto· Jurnal Ilmu Komputer dan Tek...· 0 citations
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