APLIKASI PENERAPAN METODE NEURAL NETWORK MENGGUNAKAN ALGORITMA BACKPROPAGATION UNTUK MENGETAHUI PEMBELIAN DAN PENJUALAN BAHAN BAKAR INDUSTRI

Dwi Retno Sari

Abstract


PT. Kalianda Golden Bunker is a new company that is concerned in the Agent and Transportir Fuel Industry requires a variety of information about the stock and the proceeds to the analysis report for the leadership for the purposes of report generation, so it requires a data processing program fuel stocks as well as the sale of fuel Industrial oils suitable to be applied there.
Documenting stocks and selling fuel industry is a problem frequently encountered in the PT. Kalianda Golden Bunker, this problem arises because of the difficulty of counting the large data and the lack of checks on the data that already exists, so the frequent errors in the calculation of stock and the sale of such fuel.

The algorithm used in this study is the back propagation algorithm Neural Network. Based on its function, neural networks aims to solve a problem with learning techniques. Neural Network is a computing technology, does not provide a miracle but if used properly will produce a remarkable result, the ability of Neural Network in solving complex problems has been demonstrated in a wide variety of research issues such as data analysis, meteorology, pattern recognition, system control , stock market predictions and so forth (Yani, 2005)

The results of this study are expected method using a Neural Network Backpropagation algorithm can determine the number of purchases and sales of industrial fuel in the company to obtain a more accurate calculation of the data.

Keywords: System purchase and sale of fuel Industry, Backpropagation Neural Network.


Keywords


System purchase and sale of fuel Industry; Backpropagation Neural Network

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DOI: http://dx.doi.org/10.20527/infotek.v16i1.212

DOI (PDF): http://dx.doi.org/10.20527/infotek.v16i1.212.g158

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