USED CAR PRICE PREDICTION USING SUPPORT VECTOR REGRESSION METHOD
The presence of various automotive e-commerce in Indonesia brings various benefits. However, automotive e-commerce’s existence is inseparable from various weaknesses. In this Final Project, a mathematical model to predict the price of used cars on automotive e-commerce will be developed. Used cars d...
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| Institution: | Institut Teknologi Bandung |
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id-itb.:500492020-09-22T09:40:24ZUSED CAR PRICE PREDICTION USING SUPPORT VECTOR REGRESSION METHOD Rexanna Tabitha Tanan, Ayla Indonesia Final Project SVR method, kernel method, used car price prediction INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/50049 The presence of various automotive e-commerce in Indonesia brings various benefits. However, automotive e-commerce’s existence is inseparable from various weaknesses. In this Final Project, a mathematical model to predict the price of used cars on automotive e-commerce will be developed. Used cars data on digital platforms is obtained using web scraping technique. Later the data will be modelled using Support Vector Regression (SVR) Method. SVR method is a kernel method which is a development of both Support Vector Machines and Regression Methods. The SVR method aims to form a hyperplane in the form of a regression function which represents the relationship between predictor variables and response variable. There are two types of kernels used in this final project, the 2nd order Polynomial Kernel and the Gaussian Radial Basis Kernel. The best model is obtained using 2nd order Polynomial Kernel and removing the Car Variant predictor variable. text |
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Institut Teknologi Bandung |
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Asia |
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Indonesia Indonesia |
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Institut Teknologi Bandung |
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Indonesia |
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The presence of various automotive e-commerce in Indonesia brings various benefits. However, automotive e-commerce’s existence is inseparable from various weaknesses. In this Final Project, a mathematical model to predict the price of used cars on automotive e-commerce will be developed. Used cars data on digital platforms is obtained using web scraping technique. Later the data will be modelled using Support Vector Regression (SVR) Method.
SVR method is a kernel method which is a development of both Support Vector Machines and Regression Methods. The SVR method aims to form a hyperplane in the form of a regression function which represents the relationship between predictor variables and response variable. There are two types of kernels used in this final project, the 2nd order Polynomial Kernel and the Gaussian Radial Basis Kernel. The best model is obtained using 2nd order Polynomial Kernel and removing the Car Variant predictor variable. |
| format |
Final Project |
| author |
Rexanna Tabitha Tanan, Ayla |
| spellingShingle |
Rexanna Tabitha Tanan, Ayla USED CAR PRICE PREDICTION USING SUPPORT VECTOR REGRESSION METHOD |
| author_facet |
Rexanna Tabitha Tanan, Ayla |
| author_sort |
Rexanna Tabitha Tanan, Ayla |
| title |
USED CAR PRICE PREDICTION USING SUPPORT VECTOR REGRESSION METHOD |
| title_short |
USED CAR PRICE PREDICTION USING SUPPORT VECTOR REGRESSION METHOD |
| title_full |
USED CAR PRICE PREDICTION USING SUPPORT VECTOR REGRESSION METHOD |
| title_fullStr |
USED CAR PRICE PREDICTION USING SUPPORT VECTOR REGRESSION METHOD |
| title_full_unstemmed |
USED CAR PRICE PREDICTION USING SUPPORT VECTOR REGRESSION METHOD |
| title_sort |
used car price prediction using support vector regression method |
| url |
https://digilib.itb.ac.id/gdl/view/50049 |
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1822928347216216064 |