Aqila, Annisa Farah (2022) Analisis Dampak Pandemi Covid-19 Pada Pemodelan Tingkat Pengangguran Terbuka (Tpt) Di Jawa Barat Dan Banten Menggunakan Metode Regresi Linier Berganda Ordinary Least Square (Ols) Dan Geographically Weighted Regression (Gwr). Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Akibat dari pandemi, pemerintah Indonesia mengeluarkan kebijakan untuk menekan penularan virus COVID-19, salah satunya dengan membatasi mobilitas masyarakat atau istilah lainnya adalah Pembatasan Sosial Berskala Besar (PSBB). Terdapat 8 provinsi yang memiliki tingkat pengangguran terbuka melebihi tingkat pengangguran terbuka nasional di Indonesia, diantaranya adalah Jawa Barat dan Banten. Geographically Weighted Regression (GWR) merupakan salah satu metode statistika yang digunakan untuk memodelkan variabel respon dengan variabel prediktor yang berbasis wilayah atau area. Faktor-faktor yang diduga mempengaruhi antara lain laju pertumbuhan penduduk, rata-rata lama sekolah, Tingkat Partisipasi Angkatan Kerja (TPAK), laju PDRB, dan UMK. Pemodelan TPT di Provinsi Jawa Barat-Banten dan Jawa Barat didapatkan metode terbaik menggunakan Geographically Weighted Regression (GWR). Dilakukan pengujian beda dua mean dependen pada data aktual Tingkat Pengangguran Terbuka (TPT) di Provinsi Jawa Barat-Banten dan Jawa Barat diperoleh bahwa ada perbedaaan antara dua kelompok, dimana data aktual TPT sebelum pandemi COVID-19 lebih kecil daripada data aktual saat pandemi COVID-19. Dampak pandemi pada pemodelan Tingkat Pengangguran Terbuka (TPT) menggunakan metode Geographically Weighted Regression (GWR) diketahui bahwa variabel COVID-19 berpengaruh signifikan pada model di setiap kabupaten/kota. Hasil evaluasi kebaikan estimasi model Geographically Weighted Regression (GWR) di Provinsi Jawa Barat-Banten dan Jawa Barat menunjukkan bahwa variabel UMK (X5) dan COVID-19 memiliki pengaruh terhadap TPT. Sedangkan hasil evaluasi kebaikan estimasi model regresi linier berganda Ordinary Least Square (OLS) di Provinsi Jawa Barat-Banten dan Jawa Barat menunjukkan bahwa variabel TPAK (X3), laju PDRB (X4), dan UMK (X5) memiliki pengaruh terhadap TPT.
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As a result of the pandemic, the Indonesian government has issued a policy to suppress the transmission of the COVID-19 virus, one of which is by limiting community mobility or another term is Large-Scale Social Restrictions. 8 provinces have an open floor above the national open seat floor in Indonesia, including West Java and Banten. Geographically Weighted Regression (GWR) is one of the statistical methods used to model the response variable with region-based predictor variables. The influencing factors include population growth rate, the average length of schooling, Workforce Participation Rate, GDP rate, and the district/city minimum wage. The Open Unemployment Rate modeling in West Java-Banten and West Java got the best method using Geographically Weighted Regression (GWR). The two-mean difference test depending on the actual data on the Open Unemployment Rate in the Provinces of West Java-Banten and West Java, it was found that there was a difference between the two groups, where the actual TPT data before the COVID-19 pandemic was smaller than the actual data during the COVID-19 pandemic. The impact of the pandemic on the Open Unemployment Rate modeling using the Geographically Weighted Regression (GWR) method is known that COVID-19 has a significant effect on the model in each district/city. The results of the evaluation of the Geographically Weighted Regression (GWR) model estimation in the Provinces of West Java-Anten and West Java show that the district/city minimum wage (X5) and COVID-19 variables influence TPT. The results of the evaluation of the Ordinary Least Square (OLS) multiple linear regression model evaluation in the Provinces of West Java-Banten and West Java showed that Workforce Participation Rate (X3), GDP rate (X4), and the district/city minimum wage (X5) affected TPT.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSSt 519.536 Aqi a-1 2022 |
| Uncontrolled Keywords: | COVID-19, Geographically Weighted Regression (GWR), Regresi Linier Berganda, Tingkat Pengangguran Terbuka (TPT). COVID-19, Geographically Weighted Regression (GWR), Multiple Linear Regression, Open Unemployment Rate (TPT) |
| Subjects: | H Social Sciences > HA Statistics |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Marsudiyana - |
| Date Deposited: | 11 Jun 2026 02:55 |
| Last Modified: | 11 Jun 2026 02:55 |
| URI: | http://repository.its.ac.id/id/eprint/133721 |
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