PREDICTION OF MEDICINE SALES FOR TODDLERS AT SARI MUTIARA INDONESIA UNIVERSITY PHARMACY USING THE BACKPROPAGATION ALGORITHM
Keywords:
algorithm, digital compression, compression ratio, image qualityAbstract
This research predicts sales of medicines for toddlers by applying artificial neural networks. The application uses a backpropagation algorithm where the data is input on the number of sales, income and expenditure of medicines for toddlers from the pharmacy. Basically, backpropagation is an algorithm that can be used to calculate derivatives quickly. The data that will be examined or predicted is data on drug sales for toddlers in the last 2 years or from 2022 to 2023, until 2024 is the target for the results. the prediction. The output that will be obtained from this research is the smallest error approach so that we can obtain predicted results for the availability of medicines for toddlers at the Sari Mutiara University Pharmacy in Indonesia.
The purpose of gradient descent. namely to find the optimal weights in an artificial neural network. Then form an artificial neural network by determining the number of units in each layer. After the network is formed, training is carried out from the data that has been grouped. Experiments are carried out with a network architecture consisting of input units, hidden units, output units and network architecture. Testing was carried out with Matlab software. The result was a prediction of drug availability for toddlers with the training and testing process producing actual output as the target achieved
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Copyright (c) 2024 Yunita Boru Simamora (Author)
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