Implementasi Sistem Untuk Prediksi Harga Emas

Abstract

Gold is one of the investment commodities whose value continues to increase from year to year. The rise in gold prices will encourage investors to choose to invest in gold rather than the capital market. Investment in gold gives better results for the long term and with better purchasing power, so gold investment is an effective solution considering the value of money annually eroded by inflation. Such a state of economic instability is what drives many people, organizations and companies to invest in gold precious metals. Factors influencing the rise or fall of gold price according to Riefiyono (2010) are change of exchange rate (dollar exchange rate to rupiah), world political situation, domestic economic situation, and interest rate.   The method used in this case is K-Nearest Neighbor (KNN) is a method that uses In the training phase, this algorithm only retains feature vectors and sample training data classification. In the classification phase, the same features are calculated for testing data (whose classification is unknown).   The results obtained are successfully made an application for the prediction of gold prices by utilizing the method of Nearest Neighbor Retrieval. This application can help users in knowing the gold price prediction results are expensive or cheap with views in terms of economic situation, interest rates, political situation, and changes in exchange rates.