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All Journal Computatio : Journal of Computer Science and Information Systems
Djoenaedi, Owen
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Computer Science & IT

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Prediksi Jumlah Penduduk Tingkat Kecamatan di Wilayah Bogor Menggunakan Metode Long Short Term Memory Djoenaedi, Owen; Herwindiati, Dyah Erny; Handhayani, Teny
Computatio : Journal of Computer Science and Information Systems Vol. 8 No. 2 (2024): Computatio: Journal of Computer Science and Information Systems
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v8i2.16219

Abstract

Population growth is addition or reduction of the population which is influenced by several factors. In Indonesia, this is something that pays great attention and is monitored by the government, especially on Java Island. Worries of population increase is one of the reasons for this monitoring which can cause problems with the support power and capacity power of the environment. The purpose of this design is to predict the population and calculate population growth rate at sub-district level in the Bogor area for 2021 and 2022 using population data at different annual intervals in each areas. Prediction is done using Long Short Term Memory. The configuration parameters of the model used for training and testing is different for each areas which obtained from the results of the parameter experiment which was repeated 5 times for each configuration to obtain the best Mean Absolute Percentage Error (MAPE) average. All models for LSTM method gain an average MAPE below 10% in each areas so that the models for prediction were stated to be very good.
Co-Authors Dyah Erny Herwindiati Teny Handhayani