Penerapan Data Mining Pada Data Pelanggaran Lalu Lintas Menggunakan Metode K-Means Clustering (Studi Kasus : Pengadilan Negeri Dumai)

  • Elisawati Elisawati
  • Deasy Wahyuni Sekolah Tinggi Manajemen Informatika & Komputer (STMIK) Dumai
  • Adi Arianto Sekolah Tinggi Manajemen Informatika & Komputer (STMIK) Dumai
Keywords: Data Mining, Violation, Traffic, Clustering, K-Means

Abstract

Dumai District Court is a place to receive, examine, decide and settle case disputes at the First Level by the applicable laws and regulations. The increase in traffic violations in the city of Dumai is due to the lack of awareness of road users towards the traffic rules, which makes a lot of ticket data received by the Dumai District Court. The algorithm used for the application of data mining is a k-means clustering method that will group some data into clusters, so that data that has the same characteristics are grouped into the same cluster and data which have different characteristics are grouped in different clusters. and is useful for getting information that is useful for policy users in the decision-making process. Samples of data taken from the table of traffic violations in 2017 were 8986 violations. This test uses the RapidMiner 5 application where the variables used to conduct the test are the type of violation and the month. So that it will produce violation data with the most types of violations, few and less.

Published
2019-11-26
Section
Articles