Classification of Community Complaints Against Public Services on Twitter

Muqorobin Muqorobin,Nendy Akbar Rozaq Rais,Siti Rokhmah,Isnawati Muslihah

doi:10.29040/ijcis.v1i1.6

Abstract

Abstract— Information on public services is an important part of increasing community satisfaction with government policies. Complaints and Complaints of the community become mediators to improve public services according to community needs.Twitter is one of the most widely used social media in the community to post activities, experiences, and complaints about public services through the internet easily and realtime.The amount of information on Twitter is mixed between satisfaction and extensibility of public services, making it difficult for the government to make decisions in public policy. The role of Big Data can be a solution to classifying data to predict satisfaction or extensibility of public services with parameters: markets, transportation and hospitals.Data sources taken from Twitter are 700 data texts. The twitter classification of public service complaints is built using the Naïve Bayes Algorithm Method, because the algorithm can classify based on probability values. Text processing is done by filtering text and selecting text to be ordered.The results of this study indicate that the Naïve Bayes Method is able to properly classify public service complaints based on 3 parameters, transportation, markets and hospitals. System testing using 700 data obtained the best results accuracy value: 86%, and precision: 72%, recall 81% and f-measure: 83%.

Highlights

The development of the internet today is very rapid and has a great influence on human life, one of which is the increasingly rapid dissemination of information
Text categorization methods that can be used at this time are quite large, including Bayes classification algorithm, KNearest Neighbor (KNN), Neural Network (NN), Support Vector Machine (SVM), The Decision Tree, K-Means, etc
In this study the author will use the Naïve Bayes method. This method was chosen because Naïve Bayes was able to carry out the classification process, which would be able to predict complaints or not on public services based on the results of posts from Twitter of the Indonesian people

Summary

INTRODUCTION

The development of the internet today is very rapid and has a great influence on human life, one of which is the increasingly rapid dissemination of information. In this study the author will use the Naïve Bayes method This method was chosen because Naïve Bayes was able to carry out the classification process, which would be able to predict complaints or not on public services based on the results of posts from Twitter of the Indonesian people. The main aim of this study to predicting by classifying the public services that include on complaint category or not based on 3 parameters is Transportation, Hospital, and market. This analysis results can be used to predict is it a complaint or not in the future, so it will help the government to decide the general policy by using this information

RESEARCH METHODS

AND DISCUSSION

Findings

CONCLUSION