Penerapan Metode K-Nearest Neighbor Untuk Prediksi Penjualan Berbasis Web Pada Toko Sembiring

Muhammad Yusuf Virasdi; Ari Syaripudin

Authors

Muhammad Yusuf Virasdi Universitas Pamulang
Ari Syaripudin Universitas Pamulang

Keywords:

K-Nearest Neighbor, Prediction, Sales

Abstract

Toko Sembiring was founded in 2000 by Mr. Pio Sembiring. This shop sells various necessities such as groceries, snacks, soft drinks, kitchen needs such as cooking spices, then there is also bath soap, laundry soap and sells gas and mineral water in gallons. However, along with the increasing number of competitors, sales figures at the Sembiring Store have decreased, because the system currently running at the Sembiring Store is still manual, that is, there is no system that can find out which products are most in demand by consumers and there is no good method for determining products. the most interested. With so many items sold, Toko Sembiring has difficulty determining what products have met the sales target or not in the last 1 year. An application will be designed to be able to predict sales using the K-Nearest Neighbor Method. The accuracy rate of the prediction system using the K-Nearest Neighbor method is 93.3%. So it is hoped that this application can facilitate the Sembiring Store in predicting future sales in order to create a faster and more efficient work
system.

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