APPLICATION OF DATA MINING USING THE NAÏVE BAYES CLASSIFIER METHOD TO ANALYZE THE LEVEL OF CUSTOMER SATISFACTION IN ICE CREAM MIXUE

Anita Anita; Deslin Fitri Y. Lumban Gaol; Meta Doner Septia Sipayung

doi:10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4035

Authors

Anita Anita Universitas Prima Indonesia
Deslin Fitri Y. Lumban Gaol Universitas Prima Indonesia
Meta Doner Septia Sipayung Universitas Prima Indonesia

DOI:

https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4035

Abstract

Ice Cream Mixue is a company engaged in the production of beverages and food. They provide a wide range of ice cream flavors with premium quality and natural ingredients, attracting many customers' attention. This study uses a quantitative method because the data sources are apparent. The research method is a scientific way to obtain data with specific purposes and uses. The technique used is the Naïve Bayes Classifier Algorithm with rapidminer results. 356 customers answered the questionnaire results satisfied, 64 customers who answered the questionnaire results were neutral, and 80 customers responded to the questionnaire results and were not happy. In this case, the Naïve Bayes Classifier Method can predict the level of customer satisfaction for ice cream mixes using the Rapidminer Application with Satisfied Words. This analysis obtained Class Precision satisfaction results of 94.72%, pred. neutral 2.0%, and pred. They are dissatisfied by 4%.

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