| NIM | K1B020053 |
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| Namamhs | ALIA PRAMESTU CAHYANI |
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| Judul Artikel | REGRESI NONPARAMETRIK SPLINE UNTUK PEMODELAN TINGKAT PENGANGGURAN TERBUKA DI JAWA TENGAH |
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| Abstrak (Bhs. Indonesia) | Tingkat Pengangguran Terbuka (TPT) merupakan indikator penting dalam menggambarkan kondisi ketenagakerjaan suatu wilayah. Penelitian ini bertujuan memodelkan faktor-faktor yang memengaruhi TPT di Jawa Tengah periode 2021–2023 menggunakan regresi nonparametrik spline multivariabel serta menentukan model terbaik berdasarkan Generalized Cross Validation (GCV). Variabel dependen adalah TPT dengan variabel independen kepadatan penduduk, laju pertumbuhan ekonomi, tingkat partisipasi angkatan kerja (TPAK), dan angka partisipasi kasar (APK) SMP. Hasil analisis menunjukkan model terbaik menggunakan empat titik knot dengan nilai GCV minimum 3,010905. Variabel kepadatan penduduk dan TPAK berpengaruh signifikan terhadap TPT, sedangkan laju pertumbuhan ekonomi signifikan hanya pada uji serentak dan APK SMP tidak signifikan. Uji normalitas residual terpenuhi dengan p-value 0,6455. Nilai koefisien determinasi yang diperoleh adalah 55,56% dan nilai koefesien determinasi adjusted 52,32% menunjukkan bahwa model mampu menjelaskan lebih dari separuh variasi TPT. |
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| Abtrak (Bhs. Inggris) | The Open Unemployment Rate (OUR) is an important indicator in describing the employment conditions of a region. This study aims to model the factors affecting OUR in Central Java during the period of 2021–2023 by using multivariable nonparametric spline regression and to determine the best model based on the Generalized Cross Validation (GCV) criterion. The dependent variable is OUR, with independent variables including population density, economic growth rate, labor force participation rate (LFPR), and gross enrollment rate at junior secondary school (GER-SMP). The results of the analysis show that the best model was obtained using four knot points with a minimum GCV value of 3.010905. Population density and LFPR were found to have a significant effect on OUR, while economic growth rate was significant only in the simultaneous test, and GER-SMP was not significant. The residual normality assumption was satisfied with a p-value of 0.6455. The coefficient of determination obtained was 55,56% and determination obtained Adjusted was 52,32%, indicates that the model is able to explain more than a half of the variation in OUR. |
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| Kata kunci | Generalized Cross Validation, regresi nonparametrik spline, Tingkat Pengangguran Terbuka, titik knot. |
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| Pembimbing 1 | Indra Herdiana, S.Mat., M.Sc. |
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| Pembimbing 2 | Prof. Dr. Idha Sihwaningrum, M.Sc.St. |
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| Pembimbing 3 | |
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| Tahun | 2025 |
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| Jumlah Halaman | 12 |
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| Tgl. Entri | 2025-11-27 13:42:18.648658 |
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