Coffee Stock Prediction Using Backpropagation Algorithm

Harsono, Ivan (2019) Coffee Stock Prediction Using Backpropagation Algorithm. Other thesis, UNIKA SOEGIJAPRANATA SEMARANG.

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Luwak Brand is already known as a famous coffee brand. They also have many types of coffee and coffee packaging. Providing Luwak Coffee stock everyday is difficult for the Luwak Coffee company. This happens because of the uncertain sales order every day making the company hesitant to prepare the amount of stock everyday. To solve this problem, this project makes a program that can predict amount of coffee stock. The method to be used in this project is Backpropagation Algorithm. This algorithm can calculate based on the existing data. Then, the algorithm produce an output that will be compare with the actual output. The RSME calculation is used to calculate the error comparison for getting the optimal result. The result from this program is RMSE value from Backpropagation Algorithm with various number of learning rate and hidden layer. The best result learning rate is 0,9 and the best result number of hidden layer is 7 with precentage 90%. This result had been compared with the other result and considered as the optimal result. Keyword: Backpropagation Algorithm, Neural Network, Luwak Coffee Item Stok, Prediction

Item Type: Thesis (Other)
Subjects: > 640 Home & family management > Food and Drink
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: Mr Lucius Oentoeng
Date Deposited: 10 Jul 2019 08:02
Last Modified: 10 Jul 2019 08:02

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