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

Authors

  • Zenitha Amalia Azhar Universitas Sebelas Maret
  • Sri Sulistijowati Handajani Universitas Sebelas Maret
  • Isnandar Slamet Universitas Sebelas Maret

DOI:

https://doi.org/10.58878/sutasoma.v2i2.264

Keywords:

Unemployment Index, Nonparametrik Spline Truncated Regression, Unbiased Risk (UBR), Generalized Cross Validation (GCV)

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.

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Published

2024-06-21

How to Cite

Azhar, Z. A. ., Handajani, S. S. ., & Slamet, I. (2024). Pemodelan Faktor-Faktor Yang Mempengaruhi Tingkat Pengangguran Terbuka (Tpt) Di Provinsi Jawa Tengah Menggunakan Regresi Spline Truncated Multivariabel. Jurnal Sutasoma, 2(2), 66–73. https://doi.org/10.58878/sutasoma.v2i2.264

Issue

Vol. 2 No. 2 (2024): Juni 2024

Section

Ekonomi Pembangunan

License

Copyright (c) 2024 Zenitha Amalia Azhar, Sri Sulistijowati Handajani, Isnandar Slamet

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