PENERAPAN ALGORITMA NAÏVE BAYES CLASSIFIER MENGGUNAKAN R-PROGRAMMING UNTUK PENGELOMPOKAN JENIS KELUHAN APLIKASI PLN MOBILE SECARA OTOMATIS GUNA MENINGKATKAN KEPUASAN PELANGGAN

Abstract

The PLN Mobile application was first released on the Google Play Store and App Store in 2016 by the PLN Board of Directors and was relaunched with additional features in 2020. This application was created to realize customer satisfaction from the services provided by PLN. However, in practice there are still complaints from customers and many are written in the comments column on the Google Play Store and App Store platforms. From the many comments, management wants to absorb all aspirations for improvement in increasing customer satisfaction. Management wants to know the statistics on the types of complaints categories reported. Due to the large number of comments, a method is needed to find out the category of disturbance automatically without having to read it one by one. This study offers the Naïve Bayes Classifier algorithm using R programming to provide the required complaint category statistics. Based on the algorithm system that was built, the categorization results obtained are in accordance with the contents of the customer comment messages. With these results, categories of customer comments can be generated automatically, making it easier for management to obtain statistical data related to complaints.