Penerapan Metode Naive Bayes Untuk Klasifikasi Pelanggan

Authors

  • Hakam Febtadianrano Putro STMIK Sinar Nusantara Surakarta, Indonesia
  • Retno Tri Vulandari STMIK Sinar Nusantara Surakarta, Indonesia
  • Wawan Laksito Yuly Saptomo STMIK Sinar Nusantara Surakarta, Indonesia

DOI:

https://doi.org/10.30646/tikomsin.v8i2.500

Abstract

Business location plays an important role in sales. The business location in cities makes the seller easier to distribute activities for people. Distribution activities are closely related to sales activities. If there is a sales transaction, a classification of potential and non-potential customers will be required. One method that can be used for classification is mining data. One of the most frequently used data mining for classification is the Naive Bayes method. The attributes used in the customer classification process are purchase amount, time interval, and location. The result of the classification system is 23 true reactions and 2 false reactions. Based on the results are using the confusion matrix method, it shows that the accuracy value reaches 92%, the precision value reaches 100%, the recall value reaches 91%.

Keywords: Trading Business, Customer Classification, Naive Bayes, Confusion Matrix

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Published

2020-10-20

Issue

Vol. 8 No. 2 (2020): Jurnal TIKomSiN, Vol.8, No. 2, 2020

Section

Articles

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