Estimasi Laju Pertumbuhan Penduduk Menggunakan Metode Regresi Linier Berganda Pada BPS Simalungun
DOI:
https://doi.org/10.47065/jimat.v1i2.104Keywords:
Central Statistics Agency; Multiple Linear Regression; Data Mining; Preprocessing; TransformationAbstract
The Central Statistics Agency (CSA) is a non-departmental government agency that reports directly to the president. The use of data collection is for state data collection for the needs of economic strategies, infrastructure, and so on. So that the CSA institution must be able to predict the estimated rate of population growth. Particularly one of the CSA institutions in North Sumatra, CSA Simalungun, has experienced problems in estimating the population growth rate. Multiple linear regression model is the development of a simple linear regression model. If the simple linear regression model consists of only one independent variable and one dependent variable, then in multiple linear regression the number of independent variables is more than one and one dependent variable. The stages carried out in the data mining process begin with data selection from source data to target data, the preprocessing stage to improve data quality, transformation, data mining and interpretation and evaluation stages which produce output in the form of new knowledge which is expected to make a better contribution.
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References
Yuli Mardi, “Jurnal Edik Informatika Data Mining?: Klasifikasi Menggunakan Algoritma C4 . 5 Data mining merupakan bagian dari tahapan proses Knowledge Discovery in Database ( KDD ) . Jurnal Edik Informatika,” JurnalEdikInformatikaPenelitian Bid. Komput. Sains dan Pendidik. Inform., vol. 2, pp. 213–219, 2016.
A. P. Windarto, “Penerapan Data Mining Pada Ekspor Buah-Buahan Menurut Negara Tujuan Menggunakan K-Means Clustering,” Techno.COM, vol. 16, no. 4, pp. 348–357, 2017.
Z. R. S. Elsi et al., “Utilization of Data Mining Techniques in National Food Security during the Covid-19 Pandemic in Indonesia,” J. Phys. Conf. Ser., vol. 1594, no. 1, 2020, doi: 10.1088/1742-6596/1594/1/012007.
Sudirman, A. P. Windarto, and A. Wanto, “Data mining tools | rapidminer: K-means method on clustering of rice crops by province as efforts to stabilize food crops in Indonesia,” IOP Conf. Ser. Mater. Sci. Eng., vol. 420, no. 1, 2018, doi: 10.1088/1757-899X/420/1/012089.
A. Waluyo, H. Jatnika, M. R. S. Permatasari, T. Tuslaela, I. Purnamasari, and A. P. Windarto, “Data Mining Optimization uses C4.5 Classification and Particle Swarm Optimization (PSO) in the location selection of Student Boardinghouses,” IOP Conf. Ser. Mater. Sci. Eng., vol. 874, no. 1, pp. 1–9, 2020, doi: 10.1088/1757-899X/874/1/012024.
A. P. Windarto, U. Indriani, M. R. Raharjo, and L. S. Dewi, “Bagian 1: Kombinasi Metode Klastering dan Klasifikasi (Kasus Pandemi Covid-19 di Indonesia),” J. Media Inform. Budidarma, vol. 4, no. 3, p. 855, 2020, doi: 10.30865/mib.v4i3.2312.
D. Firdaus, “Penggunaan Data Mining dalam Kegiatan Sistem Pembelajaran Berbantuan Komputer,” vol. 6, pp. 91–97, 2017.
D. H. Ningsih S., “Penerapan Metode Suksesif Interval pada Analsis Regresi,” vol. 1, pp. 43–53, 2019.
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