Artificial intelligence algorithms to predict housing market prices in Surabaya, Indonesia

What is it about?

This research explores the use of Artificial Intelligence (AI) to predict house prices in Surabaya, Indonesia. It addresses challenges like inaccurate pricing caused by traditional methods and limited data. By using web-scraped data from the "Rumah123" property marketplace, the study compares the performance of various prediction models, including Artificial Neural Network (ANN), Support Vector Machine (SVM), and Classification And Regression Tree (CART), along with traditional linear regression. The findings reveal that ANN provides the most accurate price predictions, making it a valuable tool for buyers, sellers, and real estate professionals. The study emphasizes the importance of factors like house size and electricity capacity while suggesting improvements through larger datasets. These results demonstrate the potential of AI to revolutionize property valuation, saving time and enhancing decision-making in real estate markets

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