PREDICTING CONDOMINIUM PRICE IN BANGKOK USING WEB MINING TECHNIQUES - สังข์โพธิ์ จิรพล; แรมจันทร์ ศราวุธ (Srinakharinwirot Research and Development Journal of Humanities and Social Sciences, 2021)
In Bangkok, condominium is becoming a first home for many people especially Generation Y who prefer convenience of lifestyle. Price of the condominium is one of the most important factors for buyers’ decision-making. This study aims to formulate a model that predict a selling price per square meter of a condominium in Bangkok. This is to support buyer’s decision-making whether to buy or not by using the price prediction from the model. The training dataset was gathered using web crawling techniques from hipflat.co.th. There were 1,465 condominium projects in Bangkok were extracted with each record contains 15 attributes of information. This model was formulated by using a deep learning method based on the best performed after testing the model with testing dataset. Results show that the price of the condominium in Bangkok highly affected by the number of units in the condominium project, its distance from the BTS metro line, and the year of its construction, with the relative error of 17.53%.