Penerapan Model Regresi Linear Untuk Estimasi Mobil Bekas Menggunakan Bahasa Python - Arif, Mohamad; Faisal, Muhammad (Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi, 2023)
Used cars have a significant transaction value in the automotive market. Estimating the price of a used car is important for buyers and sellers to determine the appropriate value. In this study, we apply a linear regression model using the Python programming language to estimate the price of a used car based on relevant attributes such as year of production, mileage, car tax, fuel consumption, and number of engines. We use a used car dataset that contains important information for analysis. In using the linear regression model in this study, it was successful in obtaining an accuracy of 0.76% and the results for estimating car prices were obtained by inputting car year = 2019, car mileage = 5000, car tax = 145, fuel consumption = 30,2, and engine size = 2. Then managed to get an estimated value of 21.208,505 in Pounds and 393.608,6514549 in Rupiah units. So that it can be said that the Linear Regression model has proven successful in the good category for finding used car price estimates based on certain factors using python language.