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All Journal Jurnal Informatika Teknologi dan Sains (Jinteks)
Amanda Pratiwi
Universitas Pelita Bangsa
Computer Science & IT Control & Systems Engineering

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ANALISIS PREDIKSI GILINGAN PLASTIK TERLARIS MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR DI CV MENEMBUS BATAS Amanda Pratiwi; Ananto Tri Sasongko; Dendy K. Pramudito
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 5 No 3 (2023): EDISI 17
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v5i3.3323

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.
Co-Authors Ananto Tri Sasongko Dendy K. Pramudito