Comparative Analysis of Decision Tree and Random Forest for Indonesian Food Prices
M. Rudyanto Arief, Rias Estriana, Ratna Dwi Praptiwi, Ma'aruf Handika
Food price fluctuations in Indonesia represent a persistent macroeconomic challenge, directly affecting national inflation and purchasing power, thereby necessitating an accurate forecasting system for risk mitigation. This study compares Decision Tree Regression and Random Forest Regression using 36,064 observations from Satu Data …
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Applied Computer Science and Software Engineering