Linear Regression Analysis in Predicting the Amount of Stock of HP Sparepart Goods in GMT

Authors

  • Gilang Aryudha Universitas Muhammadiyah Sumatera Utara
  • Wilda Rina Hasibuan Universitas Muhammadiyah Sumatera Utara

DOI:

https://doi.org/10.59934/jaiea.v4i1.676

Keywords:

Linear Regression, Stock Prediction, Spare Parts Availability, Inventory Management, Operational Efficiency

Abstract

The rapid advancement of the digital era has made smartphones an essential part of daily life, making the availability of high-quality spare parts crucial for their seamless operation. GMT, a store specializing in smartphone spare parts, faces challenges in predicting fluctuating consumer demand, often leading to either stock shortages or excesses. To address this issue, this research develops a stock prediction system based on linear regression, which analyzes sales data to accurately forecast stock needs. The implementation of this method has resulted in improved accuracy in stock management, enabling GMT to optimize inventory, minimize potential losses, and enhance both customer satisfaction and operational efficiency.

 

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References

Dewi Putri, R., & Andri. (2022). “Prediksi Pembelian Produk Elektronik Yang Terlaris Pada CV.Istana Komputer Palembang Menggunakan Algoritma Regresi Linear Sederhana”. Jurnal Mantik, 6(2).

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Harsiti, Muttaqin, Z., & Srihartini, E. (2022). “Penerapan Metode Regresi Linier Sederhana Untuk Prediksi Persediaan Obat Jenis Tablet”. JSil, 9(1), 12–16.

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Montgomery, D. C., Peck, E. A., & Vining, G. G. (2020). Introduction to linear regression analysis. Wiley.

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Published

2024-10-15

How to Cite

Gilang Aryudha, & Hasibuan, W. R. (2024). Linear Regression Analysis in Predicting the Amount of Stock of HP Sparepart Goods in GMT. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 4(1), 550–556. https://doi.org/10.59934/jaiea.v4i1.676