Litcius/Paper detail

Penerapan Metode Naive Bayes Untuk Klasifikasi Pelanggan

Hakam Febtadianrano Putro, Retno Tri Vulandari, Wawan Laksito Yuly Saptomo

2020Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN)63 citationsDOIOpen Access PDF

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

Topics & Concepts

Confusion matrixNaive Bayes classifierConfusionComputer scienceDatabase transactionData miningBayes' theoremValue (mathematics)Artificial intelligenceMachine learningDatabaseSupport vector machineBayesian probabilityPsychologyPsychoanalysisData Mining and Machine Learning ApplicationsEdcuational Technology SystemsMultimedia Learning Systems
Penerapan Metode Naive Bayes Untuk Klasifikasi Pelanggan | Litcius