The Use of Machine Learning in the Analysis of Pawnshop Digital Service on Customer Satisfaction
DOI:
https://doi.org/10.55927/modern.v2i4.4612Keywords:
Machine Learning, Satisfaction, Pawnshop, Pawnshop Digital Service, CustomersAbstract
This study uses analytical techniques, machine learning technology, and questionnaire surveys to assess how well Pegadaian Digital Service treats pawnshop customers. The study findings show that the service quality of Pegadaian Digital Service which includes elements such as application, fluency, speed, ease of use, service function, connection, interface/appearance, and ease of use, significantly affects customer satisfaction, although the two analytical methods used in this study are slightly different due to the demographic coverage of the sample. In addition, sentiment stems from the results of machine learning data processing, with 6.8% neutral, 46.4% negative (dissatisfied), and 46.8% positive (appointed). Meanwhile, survey data shows that 80% of clients in the Karanganyar area are satisfied, including 10% very satisfied, 20% satisfied, and 50% quite satisfied
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