Application of Feature Engineering Techniques and Machine Learning Algorithms for Property Price Prediction
Bilah Samping Artikel
Diterbitkan:
Jun 30, 2024
Kata Kunci:
property price predictio
Isi Artikel Utama
Abstrak
This research applies feature engineering techniques and machine learning algorithms to predict property prices using a dataset from Kaggle. Three models were implemented: Linear Regression, Decision Tree, and Random Forest. The Random Forest model demonstrated the best performance with an average Mean Absolute Error (MAE) of 16472.76, Mean Squared Error (MSE) of 457407807.78, and R-squared (R²) of 0.83. Key features influencing property prices were identified through feature importance analysis, providing valuable insights for enhancing property appraisals and investment decisions.
Rincian Artikel
##submission.howToCite##
Sihombing, D. J. C. (2024). Application of Feature Engineering Techniques and Machine Learning Algorithms for Property Price Prediction. JITSI : Jurnal Ilmiah Teknologi Sistem Informasi, 5(2), 72 - 76. https://doi.org/10.62527/jitsi.5.2.241
Terbitan
Bagian
Articles
##submission.license.cc.by-sa4.footer##
Referensi
1. V. Gupta and A. Shukla, "Machine Learning Approaches for Predicting Real Estate Prices," Journal of Urban Economics, vol. 56, no. 4, pp. 515-529, 2019.
2. J. Jiao and Y. Zhang, "Real Estate Price Prediction Based on Machine Learning Algorithms," IEEE Access, vol. 9, pp. 163888-163900, 2021.
3. J. Han, J. Pei, and M. Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann, 2011.
4. C. Wang and C. Lee, "Feature Selection and Engineering for Improved Real Estate Price Predictions," Journal of Housing and the Built Environment, vol. 36, no. 4, pp. 1237-1253, 2021.
5. L. Chen and X. Hao, "A Feature Engineering Framework for House Price Prediction," Journal of Real Estate Research, vol. 42, no. 3, pp. 287-304, 2020.
6. D. Zhang and Y. Dong, "Real Estate Price Prediction Based on Feature Engineering and Machine Learning," Journal of Real Estate Research, vol. 42, no. 1, pp. 45-62, 2020.
7. Y. Lu and L. Zhang, "An Empirical Analysis of Feature Engineering in Predicting House Prices," Journal of Applied Statistics, vol. 46, no. 8, pp. 1452-1468, 2019.
8. S. B. Kotsiantis, "Supervised Machine Learning: A Review of Classification Techniques," Informatica, vol. 31, no. 3, pp. 249-268, 2007.
9. T. M. Therneau and E. J. Atkinson, "An Introduction to Recursive Partitioning Using the RPART Routines," Mayo Foundation for Medical Education and Research, 2019.
10. H. Li and J. Zhu, "Real Estate Price Estimation with Machine Learning Algorithms," Journal of Real Estate Finance and Economics, vol. 61, no. 2, pp. 293-307, 2020.
11. Y. Wang and J. Li, "Predicting Housing Prices Using Machine Learning Algorithms: A Comparative Study," Computers, Environment and Urban Systems, vol. 67, pp. 111-118, 2018.
12. K. H. Kim and S. Park, "Residential Real Estate Price Prediction Using a Neural Network Model," Journal of Property Research, vol. 33, no. 2, pp. 175-190, 2016.
13. M. T. Ribeiro, S. Singh, and C. Guestrin, "Why Should I Trust You?: Explaining the Predictions of Any Classifier," Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135-1144, 2016.
14. S. M. Ross, Introduction to Probability and Statistics for Engineers and Scientists, Academic Press, 2014.
15. X. Zheng and W. Chen, "Predicting Real Estate Prices Using Ensemble Learning Techniques," IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 10, pp. 2247-2259, 2017.
16. Y. Huang and P. Wang, "Using Decision Trees for Predicting House Prices," International Journal of Housing Markets and Analysis, vol. 11, no. 2, pp. 348-367, 2018.
17. Kaggle. (n.d.). House Prices: Advanced Regression Techniques. Retrieved from Kaggle
2. J. Jiao and Y. Zhang, "Real Estate Price Prediction Based on Machine Learning Algorithms," IEEE Access, vol. 9, pp. 163888-163900, 2021.
3. J. Han, J. Pei, and M. Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann, 2011.
4. C. Wang and C. Lee, "Feature Selection and Engineering for Improved Real Estate Price Predictions," Journal of Housing and the Built Environment, vol. 36, no. 4, pp. 1237-1253, 2021.
5. L. Chen and X. Hao, "A Feature Engineering Framework for House Price Prediction," Journal of Real Estate Research, vol. 42, no. 3, pp. 287-304, 2020.
6. D. Zhang and Y. Dong, "Real Estate Price Prediction Based on Feature Engineering and Machine Learning," Journal of Real Estate Research, vol. 42, no. 1, pp. 45-62, 2020.
7. Y. Lu and L. Zhang, "An Empirical Analysis of Feature Engineering in Predicting House Prices," Journal of Applied Statistics, vol. 46, no. 8, pp. 1452-1468, 2019.
8. S. B. Kotsiantis, "Supervised Machine Learning: A Review of Classification Techniques," Informatica, vol. 31, no. 3, pp. 249-268, 2007.
9. T. M. Therneau and E. J. Atkinson, "An Introduction to Recursive Partitioning Using the RPART Routines," Mayo Foundation for Medical Education and Research, 2019.
10. H. Li and J. Zhu, "Real Estate Price Estimation with Machine Learning Algorithms," Journal of Real Estate Finance and Economics, vol. 61, no. 2, pp. 293-307, 2020.
11. Y. Wang and J. Li, "Predicting Housing Prices Using Machine Learning Algorithms: A Comparative Study," Computers, Environment and Urban Systems, vol. 67, pp. 111-118, 2018.
12. K. H. Kim and S. Park, "Residential Real Estate Price Prediction Using a Neural Network Model," Journal of Property Research, vol. 33, no. 2, pp. 175-190, 2016.
13. M. T. Ribeiro, S. Singh, and C. Guestrin, "Why Should I Trust You?: Explaining the Predictions of Any Classifier," Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135-1144, 2016.
14. S. M. Ross, Introduction to Probability and Statistics for Engineers and Scientists, Academic Press, 2014.
15. X. Zheng and W. Chen, "Predicting Real Estate Prices Using Ensemble Learning Techniques," IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 10, pp. 2247-2259, 2017.
16. Y. Huang and P. Wang, "Using Decision Trees for Predicting House Prices," International Journal of Housing Markets and Analysis, vol. 11, no. 2, pp. 348-367, 2018.
17. Kaggle. (n.d.). House Prices: Advanced Regression Techniques. Retrieved from Kaggle