PENERAPAN DATA MINING DENGAN ALGORITMA NAIVE BAYES CLASSIFIER DALAM MEMPREDIKSI PEMBELIAN CAT

Fitriana Harahap; Nidia Enjelita Saragih; Elida Tuti Siregar; Husin Sariangsah

doi:10.33884/jif.v9i01.3702

Authors

Fitriana Harahap Universitas Potensi Utama
Nidia Enjelita Saragih Universitas Potensi Utama
Elida Tuti Siregar Universitas Potensi Utama
Husin Sariangsah Universitas Potensi Utama

DOI:

https://doi.org/10.33884/jif.v9i01.3702

Keywords:

Data mining, Puchase of paint, Naive bayes

Abstract

Companies need several types of communication technology that can predict customer purchase interest, the goal is that the company can properly consider product sales and determine the company's paint product supply. So far, the decision of the Home Smart sales manager has been made by looking at the closeness of the supplier relationship and how many sponsors are funding the company. So that sometimes the product cannot compete with other companies. The Naive Bayes classifier algorithm is one of the algorithms included in the classification technology. The application of the Naive Bayes method is expected to predict paint purchases from suppliers. From 60 paint purchase data tested with the Naive Bayes method, the results reached 80% of the accuracy of the predictions. Of the 60 tested paint purchase data, 48 paint purchase data were successfully classified correctly.

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