Implementation of Artificial Neural Networks to Predict Monthly Target Receiving Section in Pt. Indako Trading Coy using Backpropagation Method

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Published Dec 30, 2020
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Vol. 14 No. 2 (2020): Login : Jurnal Teknologi Komputer, Edition December 2020

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Agus Firmansyah
Informatics Engineering Study Program, STMIK Pelita Nusantara, Medan
Jonson Manurung
Informatics Engineering Study Program, STMIK Pelita Nusantara, Medan

Abstract

PT. Indako Indako Trading Coy is a company engaged in the sale of motorbikes and their spare parts with 1000 employees who are given work targets every month. Through the given target, it can be predicted whether the employees will be rewarded or not. Prediction is an important tool in determining everything to be effective and efficient. During this time, many forecasting is done intuitively using statistical methods. The choice of this method depends on various aspects that affect, namely the aspect of time, data patterns, the type of system model observed, the level of forecast accuracy or the desired prediction and so on. The forecasting method used is using artificial neural networks (ANN) with the Backpropagation method, namely the algorithm. learning to reduce the error rate by adjusting the weight based on the difference in output and the desired target.

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How to Cite
Firmansyah, A., & Jonson Manurung. (2020). Implementation of Artificial Neural Networks to Predict Monthly Target Receiving Section in Pt. Indako Trading Coy using Backpropagation Method. Login : Jurnal Teknologi Komputer, 14(2), 335-339. Retrieved from http://login.seaninstitute.org/index.php/Login/article/view/66

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