IMPLEMENTASI METODE K-NEAREST NEIGHBOR DAN REGRESI LINEAR DALAM PREDIKSI HARGA EMAS

Utomo, Prabowo Budi ( Universitas AMIKOM Yogyakarta)
Utami, Ema ( Universitas AMIKOM Yogyakarta)
Raharjo, Suwanto ( Institut Sains & Teknologi AKPRIND Yogyakarta)

Informasi Interaktif
Vol 4, No 3 (2019): Jurnal Informasi Interaktif

ABSTRACT Gold has become one of the inventions that people are interested in. The high resale value makes many people save it as a substitute for savings. But the price of gold is influenced by several things such as economic conditions, the level of demand and supply or the existence of goods, this has encouraged some parties to make predictions of gold prices to avoid unexpected losses going forward. Based on these problems the researchers tried to predict gold prices using the K-Nearest Neighbor (K-NN) method and Linear Regression. The K-NN method is used to classify the data that is owned to then make predictions using Linear Regression. From the test with the number of training data as many as 4305 data and test data as many as 402 data, the root mean square error value of 5.807% was obtained. Keywords: gold investment, gold price prediction, K-Nearest Neighbor, Linear Regression