Clustering Menggunakan Algoritma K-Means untuk Mengelompokan Data Perjudian Berdasarkan Wilayah di Kota Binjai    (Studi Kasus : Pengadilan Negeri Binjai)

Rindi Asti Ananda; Yani Maulita; Husnul Khair

doi:10.62951/switch.v2i4.226

Authors

Rindi Asti Ananda STMIK Kaputama
Yani Maulita STMIK Kaputama
Husnul Khair STMIK Kaputama

DOI:

https://doi.org/10.62951/switch.v2i4.226

Keywords:

Data Mining, Clustering, K-Means, Gambling

Abstract

The Binjai District Court is a government agency that has the duty and authority to receive, examine and decide every case registered at the Binjai District Court. The Binjai District Court handles many gambling cases, but data management is still not fast and accurate because it still uses manual methods, so the agency needs to implement an application system. To solve this problem, you can use data mining applications, namely by utilizing existing data to dig up new information. One of the techniques in data mining is clustering. Clustering was chosen because it can group data according to the desired characteristics, in this research it means grouping gambling data in the Binjai City area. The clustering algorithm used is K-Means Clustering integrated into a desktop-based programming application. The conclusion obtained is that the system designed has proven successful in grouping gambling data into 3 clusters (groups). The process using MATLAB R2014a obtained results in group 1 which amounted to 276 data with a data centroid center (6.92; 2.41; 4.33) including the category of low levels of gambling, group 2 which amounted to 337 data with a data centroid center (7.56 ; 2.10; 14.48) is included in the category of moderate level of gambling and group 3 which amounts to 387 data with the centroid data (7.56; 2.10; 28.02) is included in the category of high level of gambling.

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