Arfianta, Puput (2021) Pemodelan Tingkat Pengangguran Terbuka Di Provinsi Jawa Timur Menggunakan Geographically Weighted Regression. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
Preview |
Text
06211940005002-Undergraduate_Thesis.pdf - Accepted Version Download (3MB) | Preview |
Abstract
Tingkat pengangguran terbuka merupakan persentase jumlah pengangguran terhadap jumlah angkatan kerja. Menurut data BPS Jawa Timur, tingkat pengangguran terbuka di Jawa Timur pada tahun 2019 belum mencapai target yang telah direncanakan oleh Pemerintah Provinsi Jawa Timur. Berdasarkan fakta, diketahui bahwa tingkat pengangguran terbuka di Jawa Timur dipengaruhi oleh faktor yang
bervariasi di setiap daerah, sehingga digunakan pemodelan menggunakan metode Geographically Weighted Regression (GWR).
GWR merupakan metode statistika yang dapat digunakan untuk menganailisis adanya heterogenitas spasial pada data. Oleh karena itu, maka perlu dilakukan analisis dengan mempertimbangkan aspek
kewilayahan mengenai pemodelan tingkat pengangguran terbuka di Jawa Timur tahun 2019 menggunakan GWR. Data yang digunakan
adalah sekunder yang didapatkan melalui publikasi website BPS Jawa Timur dengan kabupaten/kota sebagai unit pengamatan. Hasil analisis menunjukkan bahwa variabel laju pertumbuhan ekonomi, PMDN, kepadatan penduduk dan UMK berpengaruh signifikan terhadap tingkat pengangguran terbuka pada beberapa kab/kota di Jawa Timur.
Berdasarkan kriteria pemilihan model terbaik bahwa dibandingkan model regresi global, maka model GWR merupakan model yang terbaik.
================================================================================================
The unemployment rate is the percentage of the number of unemployed to the total labor force. According to East Java BPS data, the unemployment rate in East Java in 2019 has not reached the target planned by the East Java Provincial Government. Based on the facts, it is known that the level of unemployment in East Java is influenced by factors that vary in each region, so that modeling is used using the Geographically Weighted Regression (GWR) method. GWR is a statistical method that can be used to analyze the presence of spatial heterogeneity in the data. Therefore, it is necessary to conduct an analysis by considering regional aspects regarding the modeling of the unemployment rate in East Java in 2019 using GWR. The data used is secondary obtained through the publication of the BPS East Java website with the district/city as the unit of observation. The results of the analysis show that the rate of economic growth, PMDN, population density and UMK variable have a significant effect on the unemployment rate in several districts/cities in East Java. Based on the criteria for selecting the best model, the GWR model is the best model
compared to the global regression model.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | geographically weighted regression, heterogenitas spasial, tingkat pengangguran terbuka, spatial heterogeneity, unemployment rate. |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA30.6 Spatial analysis |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Puput Arfianta |
| Date Deposited: | 03 Sep 2021 17:22 |
| Last Modified: | 21 Oct 2024 04:56 |
| URI: | http://repository.its.ac.id/id/eprint/91587 |
Actions (login required)
 |
View Item |