Enhancing Sales Prediction for MSMEs: A Comparative Analysis of Neural Network and Linear Regression Algorithms
Meningkatkan Prediksi Penjualan untuk UMKM: Analisis Perbandingan Algoritma Neural Network dan Linear Regression
DOI:
https://doi.org/10.21070/ups.3954Keywords:
Prediction, Sales, Neural Network, Linear RegressionAbstract
The increasingly fierce competition in the MSME (Micro, Small and Medium Enterprises) industry has made business actors predict sales to find out future sales predictions and prepare strategies to deal with market trends that will occur in the future. Therefore, this research aims to predict sales and analyze the error value of sales data forecasting so that it can provide recommendations for strategies to increase sales. Based on the test results, the neural network algorithm is more suitable for forecasting sales than the linear regression algorithm. The test results obtained an RMSE value of 40,070 in the Neural Network method using one hidden layer and an RMSE value of 66,998 derived from the feature selection T-Test and Iterative T-Test with a Min-Tolerance value of 0.05 in the Linear Regression method.
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