Track: Data Analytics

Abstract

The rapid development of Information and Communication Technology (ICT) has made ICT an important part in the daily life of society. In that connection, the Indonesian government also tried to take advantage of ICT to be able to establish two-way communication with the public or commonly known as e-Government. One way is to create a website called LAPOR! (Layanan Aspirasi dan Pengaduan Online Rakyat or National Complaint Handling System). All kind of reports that conveyed by public through LAPOR! could be important inputs for the government to develop and improve public services. The high number of reports makes manual analysis becomes ineffective so that big data analysis becomes important. This study uses Text Mining methods for analyzing textual data in the form of opinions or complaints submitted by the public through LAPOR! by classifying those reports into classes. Then the data set in each class was clustered into specific topics. The results of this study show that the majority of public report is associated with poverty, particularly regarding social assistance, such as KPS (Kartu Perlindungan Sosial or Social Security Card) and BLSM (Bantuan Langsung Sementara Masyarakat or Temporary Direct Cash Assistance), which were not well distributed or not on target.