Rancang Bangun Sistem Prediksi Nilai Jual Properti Berbasis Web Menggunakan Regresi Linear

Abstract

This research was conducted to provide a clearer and more accurate depiction of the property value at Ziva Graha Property based on the physical characteristics and location of the houses. The study utilized PHP for data processing and modeling. The data employed included information on land area, building area, year of construction, number of floors, number of bedrooms, number of bathrooms, number of garages, and selling prices. This data was explored and processed using PHP software to assess the efficacy of linear regression methods in predicting house values. The research findings indicate that variables such as land area, building area, and number of bedrooms significantly influence the house's selling price at Ziva Graha Property. Other variables, such as the number of floors, number of bathrooms, distance to the city center, and road width, have a smaller impact. It is expected that the results of this research can provide a useful guide for prospective buyers and sellers in determining fair and realistic prices based on the physical characteristics of the houses.