Pemodelan Faktor-Faktor Yang Mempengaruhi Tingkat Pengangguran Terbuka (Tpt) Di Provinsi Jawa Tengah Menggunakan Regresi Spline Truncated Multivariabel

Abstract

Human life depends on work as it brings self-actualization to families, societies, and nations. Increasing the Open Unemployment Rate (OPR) is an employment problem. Statistically speaking, regression analysis is a tool for discovering how one or more variables (the predictors) affect another (the response variables). For this TPT case study in Central Java, researchers looked into the nonpatometric regression model of spline reduced using the UBR and GCV approaches for knot selection. The results demonstrated that the GCV model produced MSE values of 1.381e-01 and R2 of 95.69%, while the UBR model generated MSE value of 1.380e-01, and R2.