ANALISIS DAN PENGELOMPOKKAN LAPORAN PENGADUAN MASYARAKAT PADA SISTEM LAPOR.GO.ID DENGAN ALGORITMA K-MEANS PERIODE 2013-2015

Sigit Birowo (Institut Bisnis dan Informatika Kwik Kian Gie)

Jurnal Informatika dan Bisnis
Vol. 10 No. 1 (2021): Edisi Juni 2021

Indonesian people has a lot of access to share information about events that occur in everyday life that so the reports data that can be obtained are very numerous. In this study the authors will carry out the implementation and grouping with applying text mining method on report data from LAPOR.go.id to find and classify complaint topics that is most frequently reported with the k-means algorithm.Within the applications, text mining is an advanced technique to analyze and process the textual data that is part of data mining. The application of text mining is used to process the report data prior to the clustering and cluster modeling based on k-means algorithm. Kata Kunci : Keywords : Reports, Complaints, People, Report, Trending, Grouping, Cluster, Text Mining, Data Mining, K-Means