Prediksi Tingkat Pengangguran Berdasarkan Data Time Series Menggunakan Regresi Linear (Studi Kasus : Kota Salatiga)
DOI:
https://doi.org/10.35870/emt.v6i2.702Keywords:
Unemployment, Salatiga City, Linear RegressionAbstract
Unemployment is a very big problem. Coupled with the outbreak of the COVID-19 virus which resulted in many employees and workers being laid off. The purpose of this study is to predict the unemployment rate based on the number of the workforce. To produce an accurate prediction requires valid data in the long term. This makes it a reference for forecasting the unemployment population in a 5-year time series. For forecasting, a method is needed, namely the Linear Regression method. Linear regression is a statistical method that serves to test how far the relationship between the causal variables and the effect variables is. After forecasting, prediction data is generated in 2022, and the population and unemployment have changed from the previous year. Where the population in 2022 is predicted to be 144189 and the number of unemployed is 4513 people. This result is a prediction, not 100% accurate, therefore it would be better if you use another method to compare the prediction results and the level of accuracy.
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