A performance comparison of euclidean, manhattan and minkowski distances in k-means clustering

Haviluddin Haviluddin and Muhammad Iqbal and Gubtha Mahendra Putra and Novianti Puspitasari and Hario Jati Setyadi and Felix Andika Dwiyanto and Aji Prasetya Wibawa and Rayner Alfred (2021) A performance comparison of euclidean, manhattan and minkowski distances in k-means clustering.

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Official URL: https://ieeexplore.ieee.org/document/9392053

Abstract

The Indonesian police department has a role in maintaining security and law enforcement under the Republic of Indonesia Law Number 2 of 2002. In this study, data on the crime rate in the Bontang City area has been analyzed. It becomes the basis for the Police in anticipating various crimes. The K-Means algorithm is used for data analysis. Based on the test results, there are three levels of crime: high, medium, and low. According to the analysis, the high crime rate in the Bontang City area is special case theft and vehicle theft. Furthermore, it becomes the police program to maintain personal and vehicle safety.

Item Type:	Proceedings
Keyword:	Crime , Clustering , K-means , Euclidian distance , Manhattan Distance , Minkowski distance , SSE
Subjects:	D World History and History Of Europe, Asia, Africa, Australia, New Zealand, Etc. > DS Asia > DS1-937 History of Asia > DS520-560.72 Southeast Asia > DS611-649 Indonesia (Dutch East Indies) Q Science > QA Mathematics > QA1-939 Mathematics > QA1-43 General
Department:	FACULTY > Faculty of Computing and Informatics
Depositing User:	DG MASNIAH AHMAD -
Date Deposited:	18 Mar 2022 13:28
Last Modified:	18 Mar 2022 13:28
URI:	https://eprints.ums.edu.my/id/eprint/31909

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