KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika
Vol 5, No 2 (2024)

Prediksi Harga Rumah Di Jabodetabek Menggunakan Metode Artificial Neural Network

Hafizh, Muhammad Abdullah (Unknown)
Subairi, Subairi (Unknown)
Libriawan, Raditya Dimas (Unknown)
Maulana, Naufal Duta (Unknown)
Rizki, Agung Mustika (Unknown)



Article Info

Publish Date
31 Dec 2024

Abstract

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.

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Journal Info

Abbrev

kernel

Publisher

Subject

Computer Science & IT Other

Description

1. Teknologi Informasi 2. Rekayasa Perangkat Lunak: a. Rekayasa Kebutuhan b. Pengembangan Game dan Realitas Virtual c. Management Proyek Perangkat Lunak d. User Interface / User Experience 3. Jaringan Komputer: a. Sekuritas Jaringan b. Internet Of Things c. Wireless Network d. Cloud Computing e. ...