PENGELOMPOKAN KEBUTUHAN UPGRADE BANDWIDTH PADA PELANGGAN BROADBAND INTERNET MENGGUNAKAN ALGORITMA K-MEANS

NALAPRANA, IBNU and Marieska, Mastura Diana and Saputra, Danny Matthew (2024) PENGELOMPOKAN KEBUTUHAN UPGRADE BANDWIDTH PADA PELANGGAN BROADBAND INTERNET MENGGUNAKAN ALGORITMA K-MEANS. Undergraduate thesis, Sriwijaya University.

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Abstract

Insufficient bandwidth capacity is one of the main factors contributing to the decline in the quality of internet services received by customers. Internet Service Providers (ISPs) need to consider many factors before determining which customers require a bandwidth capacity upgrade. This research aims to cluster potential bandwidth upgrade needs for broadband internet customers by applying the K-Means clustering algorithm with and without data normalization using the MinMax Normalization method. The data for this study comprises active customer data from PT Djaya Sampoerna Net up to December 2023. The clustering process results in four clusters for non-normalized data with a DBI value of 0.4103, and two clusters for normalized data with a DBI value of 0.7742. The results of this study indicate that the quality of data clustering based on the DBI evaluation metric is not very good (not close to zero) and that the data normalization can have a negative impact on the clustering process of broadband internet customers using the K-Means algorithm.

Item Type:	Thesis (Undergraduate)
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.D343 Data mining. Database searching. Big data.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Ibnu Nalaprana
Date Deposited:	15 Aug 2024 05:59
Last Modified:	15 Aug 2024 05:59
URI:	http://repository.unsri.ac.id/id/eprint/155428

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