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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Recommended Citation
Regla, A. I., Barfeh, D., & Hernandez, A. A. (2019). Clustering of riding in tandem incidents using k-means: A case study in the Philippines. 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 497-500. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/15181
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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