Nadia Roosmalita Sari, Wayan Firdaus Mahmud, Aji Prasetya Wibawa
Forecasting is a method of predicting past and current data, most often by pattern analysis. A Fuzzy Takagi Sugeno Kang (TSK) study can predict Indonesia's inflation rate, yet with too high error. This study proposes an accuracy improvement based on Evolution Strategies (ES), a specific evolutionary algorithm with good performance optimization problems. ES algorithm used to determine the best coefficient values on consequent fuzzy rules. This research uses Bank Indonesia time-series data as in the previous study. ES algorithm uses the popSize test to define the number of initial chromosomes for the best optimal solution production. The increase of popSize creates better fitness value due to the ES's broader search area. The RMSE of ES-TSK is 0.637, which outperforms the baseline approach. This research generally shows that ES may reduce repetitive experiment events due to Fuzzy coefficients' manual setting. The algorithm complexity may cost to the computing time, yet with higher performance. © 2021, Universitas Ahmad Dahlan. All rights reserved.
Faculty of Islamic’s Economic and Business, Institut Agama Islam Negeri Tulungagung, Jl.Mayor Sujadi 46, Tulungagung, 66221, Indonesia; Faculty of Computer Science, Universitas Brawijaya, Jl. Veteran Malang, Malang, 65145, Indonesia; Department of Electrical Engineering, Universitas Negeri Malang, Jl. Semarang 5, Malang, 65145, Indonesia
