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All Journal VARIANSI: Journal of Statistics and Its Application on Teaching and Research
nurismi, Nur ismi
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics

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Penerapan Extreme Learning Machine (ELM) untuk Meramalkan Laju Inflasi di Indonesia Fahmuddin S, Muhammad; Annas, Suwardi; nurismi, Nur ismi
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 03 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm92

Abstract

Inflation is generally the tendency for the prices of goods and services to rise continuously. An artificial neural network (ANN) is an information processing model that closely resembles how an organism's memory system works, such as information transmission processes in the brain. Forecasting is the activity of determining future events based on past data. A time series is a set of observations that occur consecutively in the correct amount of time based on a time index. The data used in this study are Indonesian monthly inflation data. Extreme Learning Machine (ELM) is an artificial neural network approach that uses a single hidden layer feedforward neural network architecture (SLFN). The advantages of ELM over traditional learning algorithms are learning speed, improved generalization performance, and simplified implementation. An error value of RMSE of 0.1992215 was obtained based on the analysis performed using the Extreme Learning Machine (ELM) method.
Co-Authors Fahmuddin S, Muhammad Suwardi Annas