Prediksi Jumlah Migrasi Penduduk dengan Menerapkan Jaringan Syaraf Menggunakan Metode Backpropagation

Indonesia is a country that has the fourth highest population density in the world, the distribution of Indonesia's population is not evenly distributed for each region which finally the government took a policy to carry out a migration program from one region to another, thus affecting the economic development of Indonesia's population. When choosing a place to live, there are various factors that must be considered. If someone is not suitable to settle in an area or there are other driving factors, they can move or commonly known as migration. This research aims to predict the number of migrations by analyzing the results using Artificial Neural Networks with the Backpropagation Method. The Backpropagation method can be utilized by providing a relationship between population data so that it is expected in this study to achieve the right prediction. The best modeling is obtained in the 6-16-2 architecture using an input layer of 6 neurons, a hidden layer of 16 neurons and an output layer of 1 neuron. Architecture 6-16-1 produces an epoch of 8939 iterations, time 01:42, training MSE 0.00190005 and testing MSE 0.05752814 with an accuracy rate of 82%. Keywords – Prediction; Migration; Population; Artificial Neural Network; Backpropagation Method.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-05-01
DOI
https://doi.org/10.34010/0qxqxy82
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Prediksi Jumlah Migrasi Penduduk dengan Menerapkan Jaringan Syaraf Menggunakan Metode Backpropagation

SHILAP Revista de lepidopterología
Data Mining and Machine Learning Applications
article

Prediksi Jumlah Migrasi Penduduk dengan Menerapkan Jaringan Syaraf Menggunakan Metode Backpropagation

article en

Abstract

Indonesia is a country that has the fourth highest population density in the world, the distribution of Indonesia's population is not evenly distributed for each region which finally the government took a policy to carry out a migration program from one region to another, thus affecting the economic development of Indonesia's population. When choosing a place to live, there are various factors that must be considered. If someone is not suitable to settle in an area or there are other driving factors, they can move or commonly known as migration. This research aims to predict the number of migrations by analyzing the results using Artificial Neural Networks with the Backpropagation Method. The Backpropagation method can be utilized by providing a relationship between population data so that it is expected in this study to achieve the right prediction. The best modeling is obtained in the 6-16-2 architecture using an input layer of 6 neurons, a hidden layer of 16 neurons and an output layer of 1 neuron. Architecture 6-16-1 produces an epoch of 8939 iterations, time 01:42, training MSE 0.00190005 and testing MSE 0.05752814 with an accuracy rate of 82%. Keywords – Prediction; Migration; Population; Artificial Neural Network; Backpropagation Method.

SHILAP Revista de lepidopterología
Reduced inequalities
Openalex Percentile: Top 44%
Data Mining and Machine Learning Applications
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