Clustering of riding in tandem incidents using k-means: A case study in the Philippines

College

College of Computer Studies

Department/Unit

Computer Science

Document Type

Conference Proceeding

Source Title

2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)

First Page

497

Last Page

500

Publication Date

12-2019

Abstract

Riding in tandem crimes is increasing every year and have doubled over the past five years in the Philippines. However, scant research on analyzing riding in tandem data is available. This study aims to cluster riding in tandem data in the Philippines using k-means algorithm. This study shows four major crime clusters such as shooting, car- napping, robbery and others. These four major crime was categorized into three such as killed, wounded and unharmed and most reported crime category, which is robbery unharmed having the highest crime rates between 2011 to 2013 in the Philippines. The results also show a decreasing trend of riding in tandem crimes in the Philippines. This contributes by providing an understanding of riding in tandem crime in the Philippines.

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Disciplines

Computer Sciences | Criminology | Physical Sciences and Mathematics

Keywords

Thieves—Philippines—Statistics; Theft—Philippines—Statistics; Crime—Philippines—Statistics; Cluster analysis; Data mining

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