PREDICTION OF POPULATION GROWTH IN KARAWANG CITY USING MULTIPLE LINEAR REGRESSION ALGORITHM METHOD
Abstract
Currently, Indonesia is experiencing population growth. The factors influencing this growth are the rates of births and deaths. Every year, the population in an area keeps growing. This growth can have various negative impacts on the region. That's why taking action and making predictions about population growth is crucial. The objective of this study is to use a regression algorithm to estimate how fast the population will grow in Karawang City. The data used for this research comes from population records collected by the Karawang City Statistics Agency between 2017 and 2022. To clean, transform, and analyze this data, we employ the Knowledge Discovery in Database (KDD) approach to data mining. By applying linear regression methods with assistance from RapidMiner tools, we have successfully generated predictions based on data that reveal patterns and relationships between variables that influence population growth rates. According to our predictions, there will increase of 338,011 people from 2022 to 2027. This research will assist the Karawang City government in developing plans to minimize negative impacts while optimizing resource utilization such as energy, food, water, and services.
Keywords: Multiple Linear Regression, Data Mining, BPS, Rapid Miner
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