• Tidak ada hasil yang ditemukan

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

N/A
N/A
Protected

Academic year: 2024

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

Copied!
1
0
0

Teks penuh

(1)

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

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.

Referensi

Dokumen terkait

This project focuses on the Derivative Harmony Search Algorithm (DHSA) based K-means clustering protocol used to optimize the localization of sensor node in terms of energy

Abstrak – Tujuan penelitian ini adalah untuk mencari pengelompokkan yang optimal dari perbandingan dua metode dalam pengelompokkan produksi susu segar menggunakan algoritma

The K-Means clustering algorithm is used to overcome scalability problems, while WP-Rank is used to overcome the sparsity problem by performing an aggregation process so as to produce