Klasifikasi Komentar Instagram untuk Identifikasi Keluhan Pelanggan Jasa Pengiriman Barang dengan Metode SVM dan Naïve Bayes Berbasis Teknik Smote

Abstract

Customer satisfaction is one of the things expected by a company when the product produced has been marketed, both in the form of goods and services. How to complain through customer service is very diverse, lately not only by telephone, customers submit their suggestions or complaints. Customers can submit their suggestions or complaints via e-mail or e-mail or forums in the virtual world that are made by product-producing companies to accommodate a variety of complaints, suggestions, and direct criticism from consumers, especially social media, who are free to express their opinions on shipping services. they use. Instagram is a social media that is more inclined to images and on the other hand has text captions and comments, from the above problems trying to make a research for customer complaints of users of goods delivery services on an Instagram account shipping service company. From the background of the problem, the researchers tried to solve the problem for text mining classifiers by using the Support Vector Machine (SVM) and Naïve Bayes methods and using the SMOTE technique with the usual processes for text mining so that they could produce 69.68% accuracy for Support Vector Machine (SVM) and Naïve Bayes with an accuracy of 88.54%, using the Instagram comment text dataset of 776 records that have been done with preprocessing text.