Pengembangan Sistem Prediksi Harga dan Rekomendasi Mobil Bekas Berbasis Machine Learning
DOI:
https://doi.org/10.37802/joti.v7i1.987Keywords:
Used Car Price Prediction, Machine Learning, Web-Based Application, Rule-Based Recommendation SystemAbstract
The used car sales business in Indonesia has been experiencing rapid growth, driven by increasing market demand. However, determining the price of used cars remains a challenge due to various influencing factors such as the year of production, mileage, and vehicle specifications. This research develops a web-based used car price prediction system using the XGBoost Regressor algorithm. The data used undergoes preprocessing and hyperparameter tuning to produce a high-performance model (R²: 97.79% on training data and 89.90% on testing data, MSE: 2.3129, RMSE: 1.5208). Additionally, the system provides a car recommendation feature using a Rule-Based Method, allowing users to filter vehicles based on specific criteria. The results demonstrate that this system effectively assists both buyers and sellers in making more informed, efficient, and transparent decisions in used car transactions.
Downloads
References
Y. M. Geasela, J. Isabel, S. Pereisia, A. F. N. Runkat, and F. Assahara, “Pengembangan Aplikasi Penyewaan Lapangan 'Connsfield' Berbasis Website,” Journal of Technology and Informatics (JoTI), Vol.4, No. 2, pp 69-76, 2023, doi: 10.37802/joti.v4i2.320
P. A. Azhar and M. A. Pratama, “Prediksi Harga Mobil Audi Bekas Menggunakan Model Regresi Linear Dengan Framework Streamlit,” Journal of Technology and Informatics (JoTI), Vol. 6, No. 1, pp 22-28, 2024. doi: 10.37802/joti.v6i1.763
B. Kriswantara and R. Sadikin, “Used Car Price Prediction with Random Forest Regressor Model,” Journal of Information Systems, Informatics and Computing, Vol. 6, No. 1, pp 40-49, 2022. doi: 10.52362/jisicom.v6i1.752
E. Hasibuan and A. Karim, “Implementasi Machine Learning untuk Prediksi Harga Mobil Bekas dengan Algoritma Regresi Linear berbasis Web”, Jurnal Ilmiah KOMPUTASI, Vol. 21, No 4, pp 595-602, 2022. doi: 10.32409/jikstik.21.4.3327
M. A. A. Syukur and M. Faisal, “Penerapan Model Regresi Linear Untuk Estimasi Mobil Bekas Menggunakan Bahasa Python,” EULER: Jurnal Ilmiah Matematika, Sains dan Teknologi, vol. 11, no. 2, pp. 182–191, 2023. doi: 10.37905/euler.v11i2.20698.
A. Amalia, M. R. Radhi, D. R. H. Sitompul, S. H. Sinurat, and E. Indra, “Prediksi Harga Mobil Menggunakan Algoritma Regresi dengan Hyper-Parameter Tuning,” JUSIKOM PRIMA (Jurnal Sistem Informasi dan Ilmu Komputer Prima), Vol. 4 No. 2, pp 28-32, 2021.
P. Simamora, S. A. Pasaribu, dan V. Wijaya, “Peningkatan dan Optimalisasi Prediksi Harga Emas Menggunakan Metode Combine Machine Learning Random Forest dan Gradient Boosting,” Jurnal Mahkota Informatika, vol. 1, no. 1, pp. 42–52, 2024. [Online]. Tersedia: https://mojs.mtu.ac.id/index.php/mi.
T. A. Pratami, Tursina, and R. Septiriana, "Rekomendasi Pemilihan Model Sepeda Menggunakan Rule Based System," JITET (Jurnal Informatika and Teknik Elektro Terapan), vol. 12, no. 2, pp 1350-1361, 2024. doi: 10.23960/jitet.v12i2.4239
Y. M. Widyastuti, T. Oktiarso, and N. K. Putrianto, “Perencanaan dan analisis kebutuhan pengguna dalam pengembangan sistem informasi hubungan pelanggan (studi kasus di perusahaan bidang jasa finansial),” KURAWAL Jurnal Teknologi, Informasi dan Industri, vol. 7, no. 1, 2024.
A. C. Praniffa, A. Syahri, F. Sandes, U. Fariha, Q. A. Giansyah, “Pengujian Black Box dan White Box Sistem Informasi Parkir Berbasis Web”, Jurnal Testing dan Implementasi Sistem Informasi, Vol. 1., No. 1, 2023, pp. 1-16.
Downloads
Issue
Section
License
Copyright (c) 2025 Journal of Technology and Informatics (JoTI)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
