penerapan data mining dengan metode K-Nearest Neighbor untuk memprediksi penjualan aksesoris aquarium pada PT.Surya Jaya Aquarium

Chaywin, Charles (2023) penerapan data mining dengan metode K-Nearest Neighbor untuk memprediksi penjualan aksesoris aquarium pada PT.Surya Jaya Aquarium. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

PT. Surya Jaya Aquarium is an industry engaged in the sale of various types of aquarium accessories, such as aquarium machines, filter media, aquarium lights. Currently, PT. Surya Jaya Aquarium often lacks certain items when ordering goods from customers. Meanwhile, there is often an excess of other goods at the same time due to a lack of orders from customers. For this reason, it is necessary to carry out the process of predicting product sales at the company, so that the process of controlling product orders can be carried out. To carry out the prediction process, the K-Nearest Neighbor algorithm can be applied. The purpose of this algorithm is to classify new objects using features and training data samples. The data used in this study is sales data for aquarium accessories products sourced from sales for the last 3 years from 2020, 2021 and 2022 originating from PT. Surya Jaya Aquarium. After that the data is selected and will be used to be processed in predicting sales of aquarium accessories for the next period. The K-Nearest Neighbor technique is used in this study to model data that has been prepared using the Knowledge Discovery in Databases (KDD) stage. From the results of the tests carried out, information was obtained that the error rate (error) from the sales prediction results was 6,196%./ PT. Surya Jaya Aquarium adalah salah satu industri yang bergerak di bidang penjualan berbagai jenis aksesoris aquarium, seperti mesin-mesin aquarium, media filter, lampu aquarium. Saat ini, PT. Surya Jaya Aquarium sering kekurangan barang tertentu pada saat adanya pemesanan barang dari customer. Sementara itu sering kelebihan barang lainnya pada saat yang sama karena kurangnya pemesanan dari customer. Untuk itu, maka perlu dilakukan proses prediksi penjualan produk pada perusahaan, sehingga dapat dilakukan proses pengontrolan pemesanan produk. Untuk melakukan proses prediksi, maka dapat diterapkan algoritma K- Nearest Neighbor. Tujuan algoritma ini adalah untuk mengklasifikasikan objek baru menggunakan ciri dan sampel data training. Data yang digunakan dalam penelitian ini ialah data penjualan produk aksesoris aquarium bersumber pada penjualan 3 tahun terakhir dari tahun 2020, 2021, serta 2022 yang berasal dari PT. Surya Jaya Aquarium. Setelah itu data tersebut dipilih serta akan digunakan untuk diolah dalam memprediksi penjualan aksesoris aquarium untuk periode berikutnya. Teknik K-Nearest Neighbor digunakan dalam penelitian ini untuk memodelkan data yang telah disiapkan menggunakan tahap Knowledge Discovery in Databases (KDD). Dari hasil pengujian yang dilakukan, diperoleh informasi bahwa tingkat kesalahan (error) dari hasil prediksi penjualan adalah sebesar 6.196%.

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