Raw Material Sales Prediction Using an Artificial Neural Network with the Backpropagation Algorithm: A Case Study of PT. Bintang Toba Lestari
DOI:
https://doi.org/10.22303/it.14.1.2026.141-153Keywords:
Artificial Neural Network, Backpropagation, Prediksi Penjualan, Bahan Baku, Mean Squared Error, Manajemen PersediaanAbstract
Raw material sales prediction is an essential aspect of supporting production planning and inventory management in manufacturing companies. Inaccurate estimation of raw material demand may result in either overstock or stockout conditions, leading to increased operational costs and disruptions in the production process. PT. Bintang Toba Lestari, a manufacturing company specializing in spring bed production, still estimates raw material sales based solely on historical records without utilizing artificial intelligence-based forecasting methods. This study aims to apply an Artificial Neural Network (ANN) with the Backpropagation algorithm to predict raw material sales using the company's historical sales data. The research methodology consists of data collection, data preprocessing using Min-Max normalization, ANN architecture design, model training and testing using the Backpropagation algorithm, and model performance evaluation based on the Mean Squared Error (MSE) metric. Artificial Neural Networks were selected because of their ability to learn complex nonlinear relationships among variables and produce more accurate predictions than conventional forecasting approaches. The results demonstrate that the developed model is capable of learning historical sales patterns and generating predictions that closely match actual sales values while achieving a low prediction error as measured by MSE. The proposed prediction model is expected to assist the company in determining raw material requirements more accurately, improving inventory management efficiency, minimizing the risks of overstock and stockout, and supporting decision-making in production planning. Furthermore, this study contributes to the application of artificial intelligence in inventory management and sales forecasting within the manufacturing industry.
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