KLASIFIKASI TINGKAT KEPUASAN PELANGGAN PADA COLD N BREW COFFEE MENGGUNAKAN ALGORITMA NAÏVE BAYES
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Abstract
The system for assessing the level of customer satisfaction in coffee selling cafes is still very rarely implemented so that superiors do not know the advantages or disadvantages felt by customers, both in terms of service, products and facilities. This research aims to apply the Naïve Bayes Classification method, and use the Naïve Bayes algorithm to make calculations easier, after which data processing is carried out using the Confusion Matrix method as a tool to measure algorithm performance and obtain results on assessing the level of customer satisfaction of Cold N Brew coffee, aspects which is assessed based on service quality, product quality, facilities and price. This research uses quantitative research methods and collects data by distributing questionnaires to customers. Based on the results of manual testing carried out with 68 training data, 58 "SATISFIED" results were obtained, and 10 "NOT SATISFIED" results were obtained. Data testing using the Confusion Matrix method on RapidMiner using the Naïve Bayes algorithm produces an accuracy rate of 81.25%. Based on the data processing that has been carried out, the Naïve Bayes method can be recommended for predicting the quality of customer satisfaction at Cold N Brew coffee.
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