Analisis Jaringan Syaraf Tiruan untuk prediksi volume ekspor dan impor migas di Indonesia
DOI:
https://doi.org/10.26594/register.v4i1.1157Keywords:
ANN, NN, artificial neural network, declaration for, impor export declaration, oil and gas, predictions, ekspor, impor, Jaringan Syaraf Tiruan, migas, prediksi, minyak dan gas, JSTAbstract
Analisis pada penelitian penting dilakukan untuk tujuan mengetahui ketepatan dan keakuratan dari penelitian itu sendiri. Begitu juga dalam prediksi volume ekspor dan impor migas di Indonesia. Dilakukannya penelitian ini untuk mengetahui seberapa besar perkembangan ekspor dan impor Indonesia di bidang migas di masa yang akan datang. Penelitian ini menggunakan Jaringan Syaraf Tiruan (JST) atau Artificial Neural Network (ANN) dengan algoritma Backpropagation. Data penelitian ini bersumber dari dokumen kepabeanan Ditjen Bea dan Cukai yaitu Pemberitahuan Ekspor Barang (PEB) dan Pemberitahuan Impor Barang (PIB). Berdasarkan data ini, variabel yang digunakan ada 7, antara lain: Tahun, ekspor minyak mentah, impor minyak mentah, ekspor hasil minyak, impor hasil minyak, ekspor gas dan impor gas. Ada 5 model arsitektur yang digunakan pada penelitian ini, 12-5-1, 12-7-1, 12-8-1, 12-10-1 dan 12-14-1. Dari ke 5 model yang digunakan, yang terbaik adalah 12-5-1 dengan menghasilkan tingkat akurasi 83%, MSE 0,0281641257 dengan tingkat error yang digunakan 0,001-0,05. Sehingga model ini bagus untuk memprediksi volume ekspor dan impor migas di Indonesia, karena akurasianya antara 80% hingga 90%.
Analysis of the research is Imporant used to know precision and accuracy of the research itself. It is also in the prediction of Volume Exports and Impors of Oil and Gas in Indonesia. This research is conducted to find out how much the development of Indonesia's exports and Impors in the field of oil and gas in the future. This research used Artificial Neural Network with Backpropagation algorithm. The data of this research have as a source from custom documents of the Directorate General of Customs and Excise (Declaration Form/PEB and Impor Export Declaration/PIB). Based on this data, there are 7 variables used, among others: Year, Crude oil exports, Crude oil Impors, Exports of oil products, Impored oil products, Gas exports and Gas Impors. There are 5 architectural models used in this study, 12-5-1, 12-7-1, 12-8-1, 12-10-1 and 12-14-1. Of the 5 models has used, the best models is 12-5-1 with an accuracy 83%, MSE 0.0281641257 with error rate 0.001-0.05. So this model is good to predict the Volume of Exports and Impors of Oil and Gas in Indonesia, because its accuracy between 80% to 90%.
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