Penerapan Data Mining Untuk Memprediksi Penjualan Buah Dan Sayur Menggunakan Metode K-Nearest Neighbor (Studi Kasus : PT. Central Brastagi Utama)
Keywords:Forecasting, Data Mining, K-Nearest Neighbor.
PT. Central Brastagi Utama is a supermarket that sells many consumer products including fruits and vegetables. There are many types of quality fresh fruit and vegetables that come from within and outside the country. Unfortunately, so far there is no system that regulates predictions or forecasts for fruit and vegetable sales at PT. Central Brastagi Utama. So that there is often an accumulation of goods, damaged and rotten goods, or even a shortage of goods that results in losses for the company. To solve this problem, a forecasting or Forecasting is needed. Then the Data Mining technique is used with the K-Nearest Neighbor method. It is hoped that using this technique can process the last 3 years of data into information that can help the company in providing stock of goods. The results of this research are the prediction of sales of a number of products, and determine which category of product sales are in demand, moderate or little.
Copyright (c) 2021 Ayu Azlina Putri
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).