ANALISIS CLUSTER KEPUASAN PENGGUNA TERHADAP LAYANAN SHOPEE MENGGUNAKAN ALGORITMA K-MEANS

Endah Patimah, . (2021) ANALISIS CLUSTER KEPUASAN PENGGUNA TERHADAP LAYANAN SHOPEE MENGGUNAKAN ALGORITMA K-MEANS. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

In the era of technology that is increasingly developing, everyday people doing their daily activities are getting easier, one of which is online shopping. One of the applications engaged in this field is Shopee. Shopee is one of the largest online shopping applications in Indonesia, due to frequent and varied promotions, people are interested in using the Shopee application. For that reason, Shopee must know the satisfaction of its customers. Knowing customer satisfaction is one of the things Shopee should know. Where customer satisfaction can prove the quality that Shopee has. In this research, Shopee’s customer satisfaction will be grouped using the K-Means algorithm. K-Means is one of the clustering algorithms, in which K-Means will generate groups based on their similarities, so this method is suitable for use in this study. The cluster values used are 2,3,4 and 5, where the clusters that have been formed will be evaluated using the Davies Bouldin Index (DBI). Where the cluster that has the smallest DBI value is the most optimal cluster. The results obtained from this study the most optimal cluster is K-Means with k=2 which has a DBI value of 1.587617820812729.

Item Type:	Thesis (Skripsi)
Additional Information:	[No. Panggil : 1710511016] [Pembimbing 1 : Ermatita] [Pembimbing 2 : Nurul Chamidah] [Penguji 1 : Henki Bayu Seta] [Penguji 2 : Artambo B. Pangaribuan]
Uncontrolled Keywords:	K-Means, Shopee, Clustering
Subjects:	T Technology > T Technology (General) Z Bibliography. Library Science. Information Resources > ZA Information resources
Divisions:	Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User:	Endah Patimah
Date Deposited:	21 Dec 2021 07:59
Last Modified:	21 Dec 2021 07:59
URI:	http://repository.upnvj.ac.id/id/eprint/11687

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