Prediksi Harga Resale Sepatu Adidas Samba OG Menggunakan Metode Random Forest Regression Berdasarkan Variabel E-Commerce Sebagai Referensi Harga Untuk Seller dan Buyer

Abstract

The growth of e-commerce has expanded fashion product trading, including the Adidas Samba OG resale market, where prices vary across listings. This condition may complicate buyers in assessing price reasonableness and sellers in determining selling prices. This study aims to predict Adidas Samba OG resale prices using Random Forest Regression based on Size, Color, e-commerce Platform, and Units Sold. A total of 999 observations were manually collected from Shopee, Tokopedia, and TikTok Shop. The research stages included preprocessing, an 80:20 dataset split, baseline modeling, hyperparameter tuning using GridSearchCV, evaluation, feature importance analysis, visualization, and new-data prediction. The baseline model achieved an MAE of IDR 29,884.25, RMSE of IDR 111,979.93, and R² of 0.8401. After hyperparameter tuning, the best model obtained an MAE of IDR 32,907.91, RMSE of IDR 104,414.54, and R² of 0.8610. Feature importance analysis identified Units Sold as the most influential variable, with an importance of 58.99%. Testing on five new-data scenarios produced estimated resale prices ranging from IDR 2,138,312 to IDR 2,404,340. The results indicate that the model can serve as supporting information for buyers and sellers in considering Adidas Samba OG resale prices.