2019•Journal of Physics Conference SeriesOpen access

Forecasting the Export and Import Volume of Crude Oil, Oil Products and Gas Using ANN

Anjar Wanto, Bambang Herawan Hayadi, Purwo Subekti, Dadang Sudrajat, Rinandita Wikansari, Gita Widi Bhawika, Eko Sumartono, Sara Surya

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Abstract

The purpose of this study is to see the development of the volume (value) of exports and Imports of oil and gas in Indonesia in the form of estimated results for the coming years. Research data was taken from the Central Statistics Agency and the Indonesian Customs Service. Data is divided into 7 variables, namely; In the year, crude oil exports, crude oil Imports, oil exports, oil Imports, gas exports and gas Imports. The application of the method for estimating the volume of Crude Oil, Oil Products and Gas export Imports is the ANN backpropagation algorithm with 4 network architectural models namely; 12-5-1, 12-8-1, 12-10-1 and 12-14-1. The best network architectural model is 12-5-1 with an accuracy of 83% and MSE 0.0281641257. The minimum error used is 0.001-0.05 with a learning rate of 0.01. While the activation function used is bipolar and linear sigmoid with gradient descent training function.

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What this paper is about

The purpose of this study is to see the development of the volume (value) of exports and Imports of oil and gas in Indonesia in the form of estimated results for the coming years. Research data was taken from the Central Statistics Agency and the Indonesian Customs Service. Data is divided into 7 variables, namely; In the year, crude oil exports, crude oil Imports, oil exports, oil Imports, gas exports and gas Imports. The application of the method for estimating the volume of Crude Oil, Oil Products and Gas export Imports is the ANN backpropagation algorithm with 4 network architectural models namely; 12-5-1, 12-8-1, 12-10-1 and 12-14-1. The best network architectural model is 12-5-1 with an accuracy of 83% and MSE 0.0281641257. The minimum error used is 0.001-0.05 with a learning rate of 0.01. While the activation function used is bipolar and linear sigmoid with gradient descent training function.

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Available abstract

The purpose of this study is to see the development of the volume (value) of exports and Imports of oil and gas in Indonesia in the form of estimated results for the coming years. Research data was taken from the Central Statistics Agency and the Indonesian Customs Service. Data is divided into 7 variables, namely; In the year, crude oil exports, crude oil Imports, oil exports, oil Imports, gas exports and gas Imports. The application of the method for estimating the volume of Crude Oil, Oil Products and Gas export Imports is the ANN backpropagation algorithm with 4 network architectural models namely; 12-5-1, 12-8-1, 12-10-1 and 12-14-1. The best network architectural model is 12-5-1 with an accuracy of 83% and MSE 0.0281641257. The minimum error used is 0.001-0.05 with a learning rate of 0.01. While the activation function used is bipolar and linear sigmoid with gradient descent training function.

Key concepts: Crude oil, Fossil fuel, Volume (thermodynamics), Petroleum engineering, Sigmoid function, Backpropagation, Value (mathematics), Environmental science

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