PENERAPAN DATA MINING UNTUK PREDIKSI PENGARUH PENGGUNAAN APLIKASI GETCONTACT TERHADAP KEAMANAN PENGGUNA DALAM MENERIMA PANGGILAN DAN PESAN
DOI:
https://doi.org/10.33884/comasiejournal.v11i4.9088Keywords:
Application GetContact; Data Mining; User Security; Naive Bayes;RapidMinerAbstract
The study predicts the impact of the GetContact application on user security by using data mining using Naïve Bayes techniques. By using GetContact as a spam and call information filter, users can find and filter unwanted calls and messages. The app send spam or scam notifications based on the labels on the numbers it calls, with milions of users worldwide. Using RapidMiner software to analyze the data, this study used user data in the Batamindo Dormitory Block Q17 Muka Kuning. There were a total of 91 data used, divided into 61 training data and 30 test data. The result of the prediction of the influence the use of the GetContact application with Naïve Bayes resulted in model performance of 83,33% accuracy, 80% precision, and 90% recall. These result show that Naïve bayes successfully predicted the test data class. Of the 30 test data, 16 have a “Yes” class and 14 have a “No” class. This shows that 16 out of 30 users believe that the GetContact app compromises user security, while 14 out of 30 users feel the opposite.
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