Convolutional Neural Network – Long Short Term Memory Untuk Prediksi Harga Emas Indonesia - Susi Handayani; Taslim Malano; Dafwen Toresa (AI Society & STMIK Indonesia, 2022)
In the economic field, gold generally has three main functions, namely the monetary function, investment and industrial functions. In the financial world, prediction of the trend of gold price fluctuations is an important issue. Convolutional neural network algorithm is one of the popular algorithms in the image classification domain. But this algorithm can also be applied to 1-dimensional problems, such as predicting the next value in a sequence, be it a time series or the next word in a sentence. In this study, the Convolutional Neural Network algorithm was optimized with long shot time memory to predict the price of Indonesian gold from 1979 to 2021 with a total of 511 records. The test was carried out with three different epoch values, namely 50, 100 and 150 with a validity test using RMSE. From the test results, the smallest RMSE train value and RMSE validation are generated at epoch 150, which is 0.0138 for RMSE train and 0.0402 for RMSE validation.