PENGEMBANGAN MODEL PREDIKSI PENJUALAN MINGGUAN PADA PERUSAHAAN RITEL WALMART BERBASIS ARTIFICIAL NEURAL NETWORK (ANN)

  • Gieska N. Salamena Program Studi Ilmu Komputer Universitas Pattimura
  • Vyarlita I. Fataruba Program Studi Ilmu Komputer Universitas Pattimura
  • Shela Tappa Program Studi Ilmu Komputer Universitas Pattimura
Keywords: Artificial Neural Network, deep learning, MSE, sales prediction, Walmart

Abstract

Sales prediction is a crucial element in the modern retail industry, as it directly influences decision-making in inventory management, marketing strategy planning, and product distribution. This study aims to develop a weekly sales prediction model for Walmart stores using the Artificial Neural Network (ANN) approach. The dataset comprises 5,508 historical records that have been cleaned from outliers and includes several variables such as temperature, fuel price, Consumer Price Index (CPI), unemployment rate, and holiday indicators. The model is designed using a Sequential architecture with hyperparameter optimization involving the number of neurons and learning rate. Model performance is evaluated using the Mean Squared Error (MSE) metric.

Downloads

Download data is not yet available.
Published
2025-05-27
How to Cite
Salamena, G., Fataruba, V., & Tappa, S. (2025). PENGEMBANGAN MODEL PREDIKSI PENJUALAN MINGGUAN PADA PERUSAHAAN RITEL WALMART BERBASIS ARTIFICIAL NEURAL NETWORK (ANN). ALGORHYTHM: Journal of Computer Science and Computational Intelligence, 1(1), 1-8. Retrieved from https://ojs3.unpatti.ac.id/index.php/algorhythm/article/view/19326
Issue
Vol 1 No 1 (2025): May Edition
Section
Articles