Leslie Matrix Method for Predicting the Number of Births in Banten Province, Indonesia

Choirul Basir; Siti Nurasiah; Andi Nur Rahman; Tabah Heri Setiawan

Authors

Choirul Basir Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Pamulang, South Tangerang, 15310, Banten, Indonesia
Siti Nurasiah Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Pamulang, South Tangerang, 15310, Banten, Indonesia
Andi Nur Rahman Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Pamulang, South Tangerang, 15310, Banten, Indonesia
Tabah Heri Setiawan Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Pamulang, South Tangerang, 15310, Banten, Indonesia

Keywords:

Eigenvalues, growth rate, Leslie Matrix, pandemic

Abstract

The Leslie Matrix is a model commonly used to predict the growth rate of the female population. Fertility rates and female survival are internal factors in the Leslie matrix that can influence the size of a population. The aim of this research is to apply the Leslie matrix model to predict birth rates during the pandemic in Banten Province. The research method used is determining the research subject, then analysis the data that has been processed using the Python programming language, and finally drawing conclusions. This research data was obtained from the Central Statistics Agency (BPS) of Banten Province, where the number of female residents was from 2015-2020. The result of this research is a Leslie matrix model for the female population in Banten Province which is divided into ten age intervals which are constructed using fertility rates and life expectancy levels. The conclusion of this research is that the eigenvalue is 0.7632, therefore births during the pandemic in Banten Province tend to decrease by 23.6744% or it could be said that the number of births in Banten Province tends to have a negative value.