Finding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites

The increasing number of cars that have been released to the market makes it more difficult for buyer to choose the choice of car that fits with their desired criteria such as transmission, number of kilometers, fuel type, and the year the car was made. The method that is suitable in determining the...

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Autores principales:	Mohammad Farid Naufal, Yudistira Rahadian Wibisono
Formato:	article
Lenguaje:	EN ID
Publicado:	P3M Politeknik Negeri Banjarmasin 2021
Materias:	e-commerce euclidean distance k nearest neighbors manhattan distance minkowski distance Electrical engineering. Electronics. Nuclear engineering TK1-9971 Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/5e65eb59d2d149498c785ce289c6a943
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spelling	oai:doaj.org-article:5e65eb59d2d149498c785ce289c6a9432021-12-02T17:39:09ZFinding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites2598-32452598-328810.31961/eltikom.v5i1.221https://doaj.org/article/5e65eb59d2d149498c785ce289c6a9432021-03-01T00:00:00Zhttps://eltikom.poliban.ac.id/index.php/eltikom/article/view/221https://doaj.org/toc/2598-3245https://doaj.org/toc/2598-3288The increasing number of cars that have been released to the market makes it more difficult for buyer to choose the choice of car that fits with their desired criteria such as transmission, number of kilometers, fuel type, and the year the car was made. The method that is suitable in determining the criteria desired by the community is the K-Nearest Neighbors (KNN). This method is used to find the lowest distance from each data in a car with the criteria desired by the buyer. Euclidean, Manhattan, and Minkowski distance are used for measuring the distance. For supporting the selection of cars, we need an automatic data col-lection method by using web crawling in which the system can retrieve car data from several ecommerce websites. With the construction of the car search system, the system can help the buyer in choosing a car and Euclidean distance has the best accuracy of 94.40%.Mohammad Farid NaufalYudistira Rahadian WibisonoP3M Politeknik Negeri Banjarmasinarticlee-commerceeuclidean distancek nearest neighborsmanhattan distanceminkowski distanceElectrical engineering. Electronics. Nuclear engineeringTK1-9971Information technologyT58.5-58.64ENIDJurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer, Vol 5, Iss 1, Pp 25-31 (2021)
institution	DOAJ
collection	DOAJ
language	EN ID
topic	e-commerce euclidean distance k nearest neighbors manhattan distance minkowski distance Electrical engineering. Electronics. Nuclear engineering TK1-9971 Information technology T58.5-58.64
spellingShingle	e-commerce euclidean distance k nearest neighbors manhattan distance minkowski distance Electrical engineering. Electronics. Nuclear engineering TK1-9971 Information technology T58.5-58.64 Mohammad Farid Naufal Yudistira Rahadian Wibisono Finding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites
description	The increasing number of cars that have been released to the market makes it more difficult for buyer to choose the choice of car that fits with their desired criteria such as transmission, number of kilometers, fuel type, and the year the car was made. The method that is suitable in determining the criteria desired by the community is the K-Nearest Neighbors (KNN). This method is used to find the lowest distance from each data in a car with the criteria desired by the buyer. Euclidean, Manhattan, and Minkowski distance are used for measuring the distance. For supporting the selection of cars, we need an automatic data col-lection method by using web crawling in which the system can retrieve car data from several ecommerce websites. With the construction of the car search system, the system can help the buyer in choosing a car and Euclidean distance has the best accuracy of 94.40%.
format	article
author	Mohammad Farid Naufal Yudistira Rahadian Wibisono
author_facet	Mohammad Farid Naufal Yudistira Rahadian Wibisono
author_sort	Mohammad Farid Naufal
title	Finding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites
title_short	Finding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites
title_full	Finding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites
title_fullStr	Finding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites
title_full_unstemmed	Finding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites
title_sort	finding the most desirable car using k-nearest neighbor from e-commerce websites
publisher	P3M Politeknik Negeri Banjarmasin
publishDate	2021
url	https://doaj.org/article/5e65eb59d2d149498c785ce289c6a943
work_keys_str_mv	AT mohammadfaridnaufal findingthemostdesirablecarusingknearestneighborfromecommercewebsites AT yudistirarahadianwibisono findingthemostdesirablecarusingknearestneighborfromecommercewebsites
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Finding The Most Desirable Car Using K-Nearest Neighbor From E-Commerce Websites

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