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All Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURTEKSI
Setiana, Rika
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Computer Science & IT

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Population Prediction Using Multiple Regression and Geometry Models Based on Demographic Data Safii, M; Setiana, Rika
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 24 No 1 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i1.4121

Abstract

Population growth is an important issue because it significantly impacts a country’s growth and development. Large population growth can impact potential resources that drive the pace of the economy and national development. On the other hand, it can also be a problem of poverty, hunger, unemployment, education, health, and others. The government needs to control population growth to balance it with good population quality. Data sourced from the Population and Civil Registration Office of Simalungun Regency, Tanah Java sub-district has a high population and continues to increase every year. The impact of the population increase is that it affects the population’s welfare, most of whom work as laborers and farmers. To overcome this problem, it is necessary to predict the number of people in the future so that the government can make the right decisions and policies in controlling the population. This study aims to make predictions using two models, namely Multiple Linear Regression, to find linear equations and Geometry Models for population growth projections. This study utilizes multiple regression analysis and geometric models using three independent variables, namely birth rate (X1), migration rate (X2), and death rate (X3), as well as one bound variable, population number (Y). This study’s results show that the Tanah Java sub-district population is expected to increase in the next five years (2024-2028). Predictions show that by 2024, the population is expected to reach 61178 people from 59589 in 2023. Based on the results of the study, the conclusion of this study it can be used as a guide for the authorities in planning strategies and resource allocation and making a significant contribution in estimating population development in the Java region so that there will be no population explosion in the future so that it does not have a negative impact.
Population Prediction Using Multiple Regression and Geometry Models Based on Demographic Data Safii, M; Setiana, Rika
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 1 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i1.4121

Abstract

Population growth is an important issue because it significantly impacts a country’s growth and development. Large population growth can impact potential resources that drive the pace of the economy and national development. On the other hand, it can also be a problem of poverty, hunger, unemployment, education, health, and others. The government needs to control population growth to balance it with good population quality. Data sourced from the Population and Civil Registration Office of Simalungun Regency, Tanah Java sub-district has a high population and continues to increase every year. The impact of the population increase is that it affects the population’s welfare, most of whom work as laborers and farmers. To overcome this problem, it is necessary to predict the number of people in the future so that the government can make the right decisions and policies in controlling the population. This study aims to make predictions using two models, namely Multiple Linear Regression, to find linear equations and Geometry Models for population growth projections. This study utilizes multiple regression analysis and geometric models using three independent variables, namely birth rate (X1), migration rate (X2), and death rate (X3), as well as one bound variable, population number (Y). This study’s results show that the Tanah Java sub-district population is expected to increase in the next five years (2024-2028). Predictions show that by 2024, the population is expected to reach 61178 people from 59589 in 2023. Based on the results of the study, the conclusion of this study it can be used as a guide for the authorities in planning strategies and resource allocation and making a significant contribution in estimating population development in the Java region so that there will be no population explosion in the future so that it does not have a negative impact.
BACKPROPAGATION ALGORITHM IN PREDICTING THE AMOUNT OF WEST SIANTAR POPULATION GROWTH Setiana, Rika; Purba, Yuegilion Pranayama; Safii, Muhammad
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 1 (2023): Desember 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i1.2890

Abstract

Abstract: Indonesia is included in the category of developing countries and is a country with a relatively large population. According to data from the Pematang Siantar City Population and Civil Registration Service, West Siantar District is one of the sub-districts in Pematang Siantar City whose population continues to increase and this will lead to an increase in poverty and unemployment rates. To overcome the above problems, a method is needed to analyze the population growth of West Siantar, one of which is using the Backpropagation method. This research will use training data starting from 2017-2021 and test data from 2018-2022. The results carried out using MATLAB R2011a software show the best architecture 4-19-1 with an accuracy of 100 with an MSE number of 0.00010031375 and an epoch value of 124777. Based on the research carried out, the population of West Siantar in the next year is 86067 people. It is concluded that backpropagation can be used as a method that makes it easier to search for predictions and the level of accuracy obtained depends on the architecture used.            Keywords: Birth; Growth; Matlab; Predictions; Resident Abstrak: Indonesia termasuk dalam kategori negara berkembang dan merupakan negara dengan jumlah penduduk yang relatif besar. Menurut data Dinas Kependudukan dan Catatan Sipil Kota Pematang Siantar, Kecamatan Siantar Barat merupakan salah satu kecamatan di Kota Pematang Siantar yang jumlah penduduknya terus meningkat dan hal ini akan berdampak pada peningkatan angka kemiskinan dan pengangguran. Untuk mengatasi permasalahan diatas diperlukan suatu metode untuk menganalisis pertumbuhan penduduk Siantar Barat, salah satunya adalah dengan menggunakan metode Backpropagation. Penelitian ini akan menggunakan data latih mulai tahun 2017-2021 dan data uji 2018-2022. Hasil yang dilakukan dengan menggunakan software MATLAB R2011a menunjukkan arsitektur terbaik 4-19-1 dengan akurasi 100 dengan angka MSE 0.00010031375 dan nilai epoch 124777. Berdasarkan penelitian yang dilakukan, populasi Siantar Barat di tahun berikutnya sebanyak 86067 orang. Disimpulkan bahwa backpropagation dapat digunakan sebagai metode yang memudahkan pencarian prediksi dan tingkat akurasi yang diperoleh tergantung pada arsitektur yang digunakan. Keywords: Kelahiran; Matlab; Pertumbuhan; Penduduk; Prediksi
Co-Authors Muhammad Safii Purba, Yuegilion Pranayama Safii, M