CD Skripsi

Penerapan Machine Learning Untuk Mengelompokkan Pelanggan Pln (Persero) Kuala Enok Dalam Penambahan Daya

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The development of technology is currently increasingly widespread, especially in the marketing of entrepreneurs who compete to be superior in business competition. Companies are trying to find new ideas to stay in the competitive world. Clustering customers can be one way for companies to find out customers grouped according to existing characteristics so that companies can target additional power to customers. The data processed in this study are prepaid household tariff customer data with variables of old power (VA), new power (VA), power difference (VA), PEM kWh history, pulse frequency, average hours of operation, and average total rupiah. Grouping is done by applying the K-means algorithm. Clustering is a method that is able to group PLN customer data. Based on the results of the study, there are 554 customers in cluster 1, 627 customers in cluster 2 and 334 customers in cluster 3. Based on the evaluation carried out on the clustering results with a value of the silhouette coefficient = 0.42.

Keywords: Add Power,Cluster, K-Means, CRM (Customer relationship
management).

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

2003125536

Penerbit

Pekanbaru : Universitas Riau FMIPA Sistem Informasi., 2024

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

2003125536

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Mutia

Versi lain/terkait

Lampiran Berkas

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