Komparasi Model Prediksi Kurs Pada Masa Pandemi Covid-19 Menggunakan Neural Network Berbasis Genetic Algorithm dan Particle Swarm Optimization

Ali Nur Ikhsan (Universitas Amikom Purwokerto)
Primandani Arsi (Universitas Amikom Purwokerto)
Jali Suhaman (Universitas Amikom Purwokerto)

Infotekmesin
Vol 13 No 1 (2022): Infotekmesin: Januari, 2022

Data from Bank Indonesia shows that the rupiah exchange rate against dollar weakened at the beginning of the Covid-19 pandemic. This exchange rate volatility is an important problem in the Indonesian economy. Therefore, the prediction model for the exchange rate against the dollar is needed during the Covid-19 pandemic to predict the exchange rate during the Covid-19 Pandemic. This study is proposed to compare the prediction of the rupiah exchange rate against the dollar using the GA-based Neural Network algorithm and the PSO-based Neural Network algorithm. Initially the data was collected in the period 2019 to 2021, then the data is preprocessed. Validation used the k-fold validation technique with a ratio of 70:30, while the evaluation is carried out with the output of RMSE. The results showed that the performance of PSO and GA was the same, namely 0.020 +/- 0.006.