PREDIKSI HARGA RUMAH DI JABODETABEK MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK
Muhammad Abdullah Hafizh, Subairi Subairi, Raditya Dimas Libriawan, Naufal Duta Maulana, Agung Mustika Rizki · KERNEL Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika · 2025
A house is a fundamental need for humans. Determining house prices is a crucial aspect of property transactions, especially in major areas like Jabodetabek, where property prices are consistently rising. Prediction is a suitable tool to assist in decision-making for determining house prices. There are numerous methods that can be applied for prediction; the author employs the Artificial Neural Network (ANN) method. ANN is known as a highly flexible predictive algorithm capable of accommodating various input features. The results of using the ANN method for predicting house prices in the Jabodetabek area show a Mean Absolute Error (MAE) of 0.209, Mean Squared Error (MSE) of 0.159, and Mean Absolute Percentage Error (MAPE) of 4.951.