Spline Regression Analysis to Modelling The Open Unemployment Rate in Sulawesi

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Selvia Anggun Wahyuni
R Ratnawati
I Indriyani
Mohammad Fajri


Unemployment is a very complex problem because it affects and is influenced by several factors that interact with each other following a pattern that is not always easy to understand. If unemployment is not immediately addressed, it can cause social vulnerability and potentially lead to poverty. This research will use the spline regression method in modeling the 2018 Sulawesi open unemployment rate. The results obtained are the best spline model obtained from the optimum knots point with a combination of knots 3,3,1,1,3,3. This model has the minimum GCV value 1,97 with R2 77,67%. All variables significantly influence the open unemployment rate.

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