Optimizing Industrial Policy: Predicting Population Growth in Kediri Regency Using Mathematical Equations

Authors

  • Agus Miftakus Surur Institut Agama Islam Negeri Kediri, Indonesia http://orcid.org/0000-0001-7180-2965
  • Dinda Fatikhatut Diana Institut Agama Islam Negeri Kediri, Indonesia
  • Farisa Aina Fahma Institut Agama Islam Negeri Kediri, Indonesia
  • Eva Alvi Nur Laili Institut Agama Islam Negeri Kediri, Indonesia
  • Atika Anggraini Institut Agama Islam Negeri Kediri, Indonesia
  • Syamsul Arifin UIN K.H. Abdurrahman Wahid Pekalongan, Indonesia
  • Ector Geovanny Pupiales Chuquin Institusi Nacional de Loja University, Ecuador

Keywords:

population growth, Kediri Regency, differential equations, government policy, industrial fields

Abstract

The purpose of this study is to predict the population of Kediri Regency in the year 2030. Kediri Regency was selected because the region hosts an industry with national and international scale. The research method employed in this study is a literature-based approach utilizing population data obtained from the official website of the Government of Kediri Regency. The modeling approach applied is based on differential equations, specifically the Bernoulli growth model. The result of this study shows that the predicted population of Kediri Regency in 2030 is 1,590,753 people. When compared to the population in 2020, this result indicates a decrease of 44,541 people. Nevertheless, the predicted population remains relatively high, so when linked to government policy, several adjustments are required, similar to those implemented during the period from 2010 to 2020. The results of this study are important for the regency government as a basis for formulating policies, particularly in the industrial sector. Regions that develop as industrial areas require data-based planning, so the results of mathematical equation calculations can be used as objective references. Through appropriate policies, it is expected that local communities, especially local residents, can work and build their careers within their own region. Thus, the potential of local human resources can be maintained and utilized optimally. In addition, this study can also be applied by researchers or local governments in other regions to predict population size and adjust policies according to the conditions of their communities.

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Published

2025-04-30

Issue

Vol. 7 No. 1 (2025)

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