Jurnal Informatika Teknologi dan Sains (Jinteks)
Vol 5 No 3 (2023): EDISI 17

ANALISIS PREDIKSI GILINGAN PLASTIK TERLARIS MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR DI CV MENEMBUS BATAS

Amanda Pratiwi (Universitas Pelita Bangsa)
Ananto Tri Sasongko (Universitas Pelita Bangsa)
Dendy K. Pramudito (Universitas Pelita Bangsa)



Article Info

Publish Date
11 Aug 2023

Abstract

The phenomenon of abundant plastic waste is a global problem that has a broad impact, including on the recycling industry such as CV Breaking the Limit. The main challenge facing companies is the difficulty of predicting which products will be most in demand by the market. However, through this research, using historical sales data from the period April 2022 to April 2023, managed to identify ACR Mill products as the best-selling products that are most in demand by consumers. The application of the K-Nearest Neighbor algorithm method in sales prediction helps companies to optimize production, manage stocks, and allocate resources more efficiently. The results showed that the K-Nearest Neighbor algorithm rovides very accurate predictions, with accuracy, recall, and precision values reaching 1.0 in product classification, so it can be relied on in supporting the sustainability of the plastic recycling business amid global challenges related to plastic waste.

Copyrights © 2023






Journal Info

Abbrev

JINTEKS

Publisher

Subject

Computer Science & IT Control & Systems Engineering

Description

Jurnal Informatika Teknologi dan Sains (JINTEKS) merupakan media publikasi yang dikelola oleh Program Studi Informatika, Fakultas Teknik dengan ruang lingkup publikasi terkait dengan tema tema riset sesuai dengan bidang keilmuan Informatika yang meliputi Algoritm, Software Enginering, Network & ...