Metode Support Vector Machine pada Klasifikasi Pengaduan Masyarakat

Abstract

Public complaint service is a very important service in a government agency. Service 112 is a public complaint service that is connected directly to the 112 call center that has been appointed by the local government. The government of the city of Samarinda through the Office of Communication and Informatics also has a call center service 112 which is commonly called by Samarinda City residents, namely the Samarinda Siaga Service 112. Various kinds of complaints from the public make operators have to be more careful in categorizing every complaint that comes in, and not infrequently the community convey it using the regional language which can make it difficult for operators to categorize the complaint. Text mining is one of the methods used in the classification process. In this study, the text mining process was used to classify public complaints using the Support Vector Machine method. The results of the research that has been carried out using as many as 120 public complaint data, which are then divided into 2, namely as training data as much as 96 data and data testing as much as 24 data using the Support Vector Machine method using the RBF kernel get an accuracy result of 79%, a precision of 56%, recall of 100%, f1-score of 71% and support 5.