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Andi Nikma Sri Handayani
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Energy

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KLASIFIKASI PESAN GANGGUAN PELANGGAN MENGGUNAKAN METODE NAIVE BAYES CLASSIFIER Haryono Haryono; Pritasari Palupiningsih; Yessy Asri; Andi Nikma Sri Handayani
KILAT Vol 7 No 2 (2018): KILAT
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3210.193 KB) | DOI: 10.33322/kilat.v7i2.354

Abstract

The application of customer disturbance message classifiers is made because of the process of reporting the interruption by the customer must be done by selection of data disorders by one by the admin to be able to follow-up from the existing customer reports. Naive Bayes is one of machine learning methods that uses probability calculations where the algorithm takes advantage of probability and statistical methods that predict future probabilities based on past experience. The application of the naive bayes classifier method with text mining as the initial data processor of the disorder messaging application can be concluded that this study yields an accuracy of probability values of 95 percent and proves that the Naive Bayes method can be used to help classify interference messages sent by customers.
Co-Authors Haryono Haryono Palupiningsih, Pritasari Yessy Asri