Implementasi Data Mining Dengan Metode Regresi Linier Untuk Memprediksi Laju Pertumbuhan Penduduk Kota Binjai

Abstract

The Central Statistics Agency (BPS) is a ministerial institution tasked with conducting statistical data collection and is directly responsible to the president. One of BPS's duties and functions is to collect statistical data on the population. The BPS conducts routine data collection every few years. However, BPS Binjai City has difficulty estimating the annual population growth rate due to several constraints. Data mining techniques using linear regression methods can be used to estimate the growth rate. The data mining process begins with data selection from source data to target data, followed by preprocessing to improve data quality, transformation, data mining, and interpretation and evaluation. This process produces new knowledge that is expected to contribute to a better understanding. This method was chosen because it can generate predictions using population growth data, thus establishing useful relationship patterns. Linear regression analysis is a widely used statistical method in social research, particularly economic research. Linear regression is a data mining technique frequently used to determine the level of relationship between dependent variables and the effects of forecasting through independent variables or individual causes. Data processing was performed using Google's Collab Research software, using a dataset from 2019 to 2024, covering the male and female population of Binjai City. Data mining results using a linear regression model on BPS population data from 2019 to 2024 indicate that the population growth rate will increase by 3.01% in 2025.