Implementasi Algoritme Extreme Learning Machine (ELM) Untuk Prediksi Harga Emas Bagi Investor - Laila Restu Setiya Wati; Imam Cholissodin; Putra Pandu Adikara (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
There are a variety of investing one is gold. Plain gold made into a long-term investment, since the benefits of investing in gold is easily exchanged, no taxes and investing in gold because it has properties that are resistant to inflation. The nature of the resistance it that make interested investors to invest. Tough investors get information mengenahi changes up and down the gold price with the issue so that investors desperately need information for predictions as a consideration of when to buy and sell gold in order to get the profit in accordance with the perancanaan that have been made. This research uses algorithms Extreme Learning Machine (ELM) for predicting the price of gold. Testing in predicting model algorithms so that the gold price to ELM produce gold price predictions with optimal. Test analysis results by using the best of previous testing variables produce the Mean Absolute Percentage Error (MAPE) of 0.29%, best of MAPE generated less than 10% indicates that Extreme Learning Machine (algorithms ELM) good to be implemented in doing the predictions of the gold price.