Prediksi Nilai Harga Patokan Batu Bara (HPB) Untuk Merek Dagang Gunung Bayan I dengan Metode Extreme Learning Machine (ELM)

Evilia Nur Harsanti (Fakultas Ilmu Komputer, Universitas Brawijaya)
Muhammad Tanzil Furqon (Fakultas Ilmu Komputer, Universitas Brawijaya)
Putra Pandu Adikara (Fakultas Ilmu Komputer, Universitas Brawijaya)

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 2 No 12 (2018): Desember 2018

Coal is a fossil fuel that is often used by industrial companies as a source of energy and power as a raw material for steelmaking. Coal is obtained by industrial companies through a sale and purchase transactions conducted with coal mining companies. Price is a major factor in the transaction process, because industrial companies need to design an expenditure budget every month before making a transaction. Budget design is done to maximize the company's money to meet all the needs of the company. Therefore, the prediction of coal price will be very beneficial for industrial companies that will buy coal products to know the estimated price in the future. The method used to make the prediction process is the method of Extreme Learning Machine (ELM). ELM has the advantage of fast computing time and small error rate, so ELM does not require a long time in the learning process. Based on the result of research, the best Means Absolute Percentage Error (MAPE) score is 3,926804% for training process and 7,360343% for testing process.