Algoritma Backpropagation Neural Network dalam Memprediksi Harga Komoditi Tanaman Karet


Julius Rinaldi Simanungkalit(1); Haviluddin Haviluddin(2*); Herman Santoso Pakpahan(3); Novianti Puspitasari(4); Masna Wati(5);

(1) Universitas Mulawarman
(2) Universitas Mulawarman
(3) Universitas Mulawarman
(4) Universitas Mulawarman
(5) Universitas Mulawarman
(*) Corresponding Author

  

Abstract


Rubber plantation sector is one of the leading commodities in East Kalimantan Province contributing greatly to non-oil and gas exports. Currently, the price of rubber in the world is increasingly competitive. The aim of this research is to predict the rubber prices as a reference for the government and companies in making policies and preparing work plans. Data of 60 months during the period of 2014-2018 taken from Plantation office of East Kalimantan Province has been analyzed using Backpropagation Neural Network (BPNN) algorithm in predicting rubber prices. Based on the testing results, parameters of the BPNN algorithm with ratio of 4: 1, architectural models 5-10-10-10-1, trainlm learning function, learning rate of 0.5, error tolerance of 0.01, and epoch of 1000 have gained good accuracy with a mean square error (MSE) of 0.00015464. The results showed that the BPNN algorithm can be used as an alternative method in forecasting.

Keywords


Commodity; Rubber prices; Prediction; BPNN; MSE

  
  

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doi  https://doi.org/10.33096/ilkom.v12i1.521.32-38 		  

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References


K. Dirjen Kerjasama Industri Internasional, “Perkembangan Kerjasama ASEAN di Sektor Industri (s.d. 2011),” 2012.

D. Perkebunan, “Harga Komoditas Tanaman Karet,” 2019. [Online]. Available: https://disbun.kaltimprov.go.id/kategori-download/harga-tbs-kelapa-sawit-tahun-2011-2017.

S. D. Perkebunan, “Komoditas Karet 2011-2013,” 2012.

M. A. Rofiq, Peramalan Komoditas Strategis Pertanian Cabai Menggunakan Metode Backpropagation Neural Network. 2017.

M. A. Puspa, “Backpropagation Neural Network Berbasis Particle Swarm Optimization ntuk Prediksi Harga Karet Spesifik Teknis,” J. Teknosains, Vol. 10, Nomor 2, Juli-Desember 2016, hlm. 197 – 210, vol. Volume 10, pp. 197–210, 2016.

A. J. P. Triyono, Andri Santoso, “Penerapan Metode Jaringan Syaraf Tiruan Backpropagation Untuk Meramalkan Harga Saham (IHSG),” J. Sist. Dan Inform., vol. Vol 11, No, pp. 165–172, 2016.

A. Bode, “K-Nearest Neigbor dengan Feature Selection menggunakan Backward Elimination untuk Prediksi Harga Komoditi Kopi Arabika,” Ilk. J. Ilm., 2017.

M. E. Lasulika, “Prediksi Harga Komoditi Jagung Menggunakan K-NN dan Particle Swarm Optimization sebagai Fitur Seleksi,” Ilk. J. Ilm., 2017.

I. Santoso, U. Effendi, and C. Fauziya, “Penerapan Jaringan Syaraf Tiruan Untuk Peramalan Permintaan Komoditas Karet di PT Perkebunan Nusantara XII Surabaya,” J. Teknol. Pertan., vol. 8, no. 1, pp. 46–54, 2007.

S. Wolfert, L. Ge, C. Verdouw, and M. J. Bogaardt, “Big Data in Smart Farming – A review,” Agricultural Systems. 2017.

M. I. Jordan and T. M. Mitchell, “Machine learning: Trends, perspectives, and prospects,” Science. 2015.

T. Fischer and C. Krauss, “Deep learning with long short-term memory networks for financial market predictions,” Eur. J. Oper. Res., vol. 270, no. 2, pp. 654–669, 2018.

D. Rajasekar, C. Dhanamani, and S. K. Sandhya, “A Survey on Big Data Concepts and Tools,” Int. J. Emerg. Technol. Adv. Eng., vol. 5, no. 2 February 2015, pp. 80–84, 2015.

C. H. Fajardo-toro, J. Mula, and R. Poler, Engineering Digital Transformation. Springer International Publishing, 2019.

S. Athey, “The Impact of Machine Learning on Economics,” in The Economics of Artificial Intelligence: An Agenda, University of Chicago Press, 2018.

H. Aini and H. Haviluddin, “Crude Palm Oil Prediction Based on Backpropagation Neural Network Approach,” Knowl. Eng. Data Sci., 2019.

M. Lehtokangas, “Modelling with constructive backpropagation,” Neural Networks, 1999.

Mislan, Haviluddin, S. Hardwinarto, Sumaryono, and M. Aipassa, “Rainfall Monthly Prediction Based on Artificial Neural Network: A Case Study in Tenggarong Station, East Kalimantan - Indonesia,” in Procedia Computer Science, 2015.

P. Purnawansyah, H. Haviluddin, H. J. Setyadi, K. Wong, and R. Alfred, “An Inflation Rate Prediction Based on Backpropagation Neural Network Algorithm,” Int. J. Artif. Intell. Res., vol. 3, no. 2, p. 2019, 2019.

R. Rojas, “The Backpropagation Algorithm,” in Neural Networks, 2011.


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