Prediksi Harga Mobil Bekas Berdasarkan Tipe Penjual dan Jenis Kendaraan Menggunakan Regresi Linier

The growing demand for affordable transportation has significantly expanded the used car market. This study aims to develop optimal sales strategies by analyzing seller types and vehicle categories through exploratory data analysis and linear regression techniques. Using a cleaned public dataset of over 150,000 used car listings in Germany, key variables such as registration year, mileage, vehicle type, and seller type were examined. Results indicate that individual sellers dominate the market, although dealers set higher and more stable prices. SUVs and limousines typically hold higher market value. The linear regression model achieved an R-squared value of 0.34, suggesting that registration year and mileage account for 34% of the price variance. These findings offer practical insights for stakeholders in the used car business to tailor pricing strategies based on vehicle attributes and seller classification