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Implementasi Algoritma K-Means untuk Pengelompokan Data Penjualan Berdasarkan Pola Penjualan

Implementation of K-Means Algorithm for Clustering Sales Data Based on Sales Patterns
Authors: Arfigo Yahya; Rakhmat Kurniawan;

Implementasi Algoritma K-Means untuk Pengelompokan Data Penjualan Berdasarkan Pola Penjualan

Abstract

Toko Sembako Aceh Mulia memiliki sebuah pusat distribusi. Pusat distribusi ini menyimpan banyak produk berbeda yang akan dijual, melihat pada pusat distribusi toko masih melibatkan pembukuan untuk berbagai informasi transaksi, dan masih mengkaji produk yang akan dibeli untuk memenuhi stok di pusat distribusi, masih belum ada estimasi untuk produk yang umumnya dicari oleh pelanggan, untuk menghasilkan perkembangan produk yang sedang populer dan meminimalisir produk tidak sering dibeli yang menyebabkan kerugian. Dalam permasalahan yang ada menggunakan metode K-means, dengan mengklaster atau mengelompokkan barang-barang yang terjual menjadi 3 bagian yaitu sangat laku, laku dan kurang laku, dengan pembagian seperti ini diharapkan memudahkan Toko Sembako Aceh Mulia dalam menyusun strategi dalam management penyetokan barang dengan pengelompokan barang yang terjual dengan kriteria sangat laku. Hasil clustering dari 30 dataset yang sudah di analisis menunjukan bahwa C1 terdapat 21 jenis produk dimana dapat dikategorikan paling laris dengan nilai 181,23 pada jenis produk kopi kapal api dan C2 terdapat 9 jenis produk dimana dapat dikategorikan paling tidak laris dengan nilai 228,03 pada jenis produk kopi kapal api.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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