Page 34 - Proceeding The 2nd International Seminar of Science and Technology : Accelerating Sustainable Innovation Towards Society 5.0

nd
The 2 International Seminar of Science and Technology
“Accelerating Sustainable innovation towards Society 5.0”
ISST 2022 FST UT 2022
Universitas Terbuka
COMPARISON OF RANDOM FOREST AND SINGLE
EXPONENTIAL SMOOTHING METHODS IN THE
PREDICTION OF GOLD DEMAND FOR INDONESIAN
JEWELRY PERIOD 2010-2021

1
1*
Seni Eriani , Wiwit Pura Nurmayanti , Harista
1
1
1
Almiatus Soleha , Muhammad Gazali , Kertanah , Siti
2
Hadijah Hasanah
1 Department of Statistics, Universitas Hamzanwadi (INDONESIA)
2 Study Program of Statistics, Universitas Terbuka (INDONESIA)
*Corresponding author: wiwit.adiwinata3@gmail.com

Abstract
Forecasting is an activity to predict something that will happen in the
future. In forecasting, there are several methods, including Random
Forest and Single Exponential Smoothing (SES). Random Forest has
the advantage that it does not require assumptions, while SES
requires assumptions as data that must be stationary and used for
short-term forecasting. We can apply Random Forest and SES in
various fields, one of which is economics, which focuses on the
demand for gold jewellery. The importance of analysing data on the
number of requests for gold jewellery is because there are many
enthusiasts from gold itself. This study compares the two methods in
predicting the demand for gold jewellery in Indonesia. Based on the
results of the analysis, we found Random Forest is better than SES,
we can see it from the forecast error value of Random Forest, which
is smaller than SES. The Random Forest method got the best model
with n-tree 50, resulting in an MAPE value of 12.87%. Meanwhile, the
best model for SES with an alpha of 0.4 produces an MAPE value of
20.63%.

Keywords: Forecasting, Random Forest, Single Exponential
Smoothing, gold jewellery, MAPE

ISST 2022 – FST Universitas Terbuka, Indonesia 13
International Seminar of Science and Technology “Accelerating Sustainable
Towards Society 5.0