APLIKASI E-COMMERCE DENGAN PERINGKAT OTOMATIS MENGGUNAKAN NAIVE BAYES PADA KAIJIN STORE

G. Christian Happy

Abstract


E-Commerce Applications wtih Automatic RAting Using Naive Bayes On Store Kaijin an E-Commerce website that connects buyers and sellers with its rank is automatic. The system is made using Naive Bayes method to automatically ranked based on the comments. Ranking results are divided into two categories: positive comments and negative comments. Ranking one and two are included in the negative category, while no. three and four are included in the positive category. The test results using the confusion matrix for the evaluation process. Tests using 160 training data nd test data 40 is 40 there are 36 incoming data to the actual ratings and four the data differ from actual ratings so system accuracy of 90%.

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