Application of Backpropagation Algorithm for Prediction of Sales Results of Basic Foodstuffs at Artha Water Store
DOI:
https://doi.org/10.55123/jomlai.v4i1.5764Keywords:
Artificial Neural Network , Backpropagation , Sales , Artha Water StoreAbstract
Companies need to implement sales growth forecasting strategies to create a balance between inventory and sales needs. Without this effort, an imbalance between inventory and sales can cause losses for the company, both in terms of finance and customer satisfaction. As a business entity engaged in the sale of basic necessities, Artha Water is committed to managing its business seriously in order to achieve profits and meet customer needs optimally. However, the development of consumer consumption patterns and sales growth lines at Artha Water which are fluctuating (up and down) make it quite difficult for the cooperative to balance inventory with demand for goods from consumers. By utilizing science in Artificial Neural Networks, we can predict future income using the Backpropagation Algorithm. From the previous description, the author concludes that from the results of the study with the best architecture experiments, namely 12-10-1 to predict sales growth at the Artha Water Store in 2024, it shows an accuracy result of 92%, MSE training of 0.06031588, that there is a significant difference, in other words, sales growth at the Artha Water Store will increase in 2024. With a total sales result of basic necessities at the Artha Water Store for 2024 of IDR 336,930,000.
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