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Silvia Ningsih
ITB Ahmad Dahlan Jakarta
Computer Science & IT Decision Sciences, Operations Research & Management

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Implementasi Algoritma Backpropagation Untuk Memprediksi Harga Jual Rumah Berdasarkan Harga Bahan Baku Silvia Ningsih; Vany Terisia
Jurnal Sistem Informasi (JUSIN) Vol 1 No 1 (2020): JUSIN
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v1i1.856

Abstract

Housing developers often find it difficult to determine the selling price of the house. One of the main factors to determine the selling price of the house. One of the main factors to determine the selling price of the homes is information regarding the use of raw material prices. Companies need information in prices of row material price fluctuations, air, causing the company is difficult to predict the selling price of the house next period. Forecasting methods used in this system is backpropagation neural network method that refers to a component of time series data forecasting random or random variance with the initial process for determining autocorrelation input variables. This propagation method is proven to predict the selling price of the house.
Co-Authors Vany Terisia