Optimasi K-Means dengan Algoritma Genetika untuk Target Pemanfaat Air Bersih Provinsi Riau

Taslim, Taslim and Toresa, Dafwen and Jollyta, Deny and Suryani, Des and Sabna, Eka (2021) Optimasi K-Means dengan Algoritma Genetika untuk Target Pemanfaat Air Bersih Provinsi Riau. Indonesian Journal of Computer Science. ISSN 2302-4364

[img] Text
4. document.pdf - Published Version

Download (545kB)

Abstract

Clean water is an important thing in human life. Several actions have been taken by the government to meet the clean water needs of the Riau province. One of them is the Community Based Drinking Water and Sanitation Provision program. Before carrying out activities related to the provision of clean water to the community, the targets to be achieved for the provision of clean water in the future will be determined. This study aims to klaster clean water beneficiary targets using the k-means algorithm with an optimization of the centroid value using a genetic algorithm. Average silhouette number is used to get the optimal number of klasters, which is two klasters. The results of klaster validity were measured using the Davies Bouldin Index (DBI) method where klasterization without optimization resulted in a DBI of 2.164763 and the results of klasterization by carrying out genetic optimization on the centroid value resulted in a DBI value of 2.06894.

Item Type: Article
Uncontrolled Keywords: klasterization;k-means; optimization;genetics; validity
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Divisions: > Teknik Informatika
Depositing User: Mohamad Habib Junaidi
Date Deposited: 19 Sep 2023 08:02
Last Modified: 19 Sep 2023 08:02
URI: http://repository.uir.ac.id/id/eprint/22410

Actions (login required)

View Item View Item