dc.contributor.advisor | Suyanto | |
dc.contributor.author | Siagian, Dini Lestari Efendi | |
dc.date.accessioned | 2024-04-24T01:41:28Z | |
dc.date.available | 2024-04-24T01:41:28Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://repositori.usu.ac.id/handle/123456789/93133 | |
dc.description.abstract | The increase in the open jobless rate in North Sumatra Province reached 6.30
percent. Due to the distinct characteristics of each region in North Sumatra Province,
the open unemployment rate problem illustrates the geographical influence of
location and the potential for spatial heterogeneity. Geographically Weighted
Regression is a method that can help in dealing with spatial problems. By modeling
influencing variables, This study intends to learn more about North Sumatra
Province's open unemployment rate in 2021. Local partial GWR testing findings
demonstrate that the variable of residents who work during the week has significant
spatial heterogeneity or is local in nature. However, the factors of the human
development index, labor force participation rate, GRDP rate at constant prices and
participation rate are purely global in nature. One model that has spatial
heterogeneity is Y Kab.Nias = 7,774 − 0,155X1 + 0,245X2 − 1,667X5 − 0,133X7 −
3,26e−5x8 . a fixed gaussian weighting function was used in this investigation for
weighting. According to the criteria for the model's goodness, the findings
demonstrate that the GWR model outperforms multiple linear regression analysis
(OLS), as evidenced by the values for R2, AIC, MSE, and MAPE. | en_US |
dc.language.iso | id | en_US |
dc.publisher | Universitas Sumatera Utara | en_US |
dc.subject | Geographically weighted regression | en_US |
dc.subject | regresi linier berganda | en_US |
dc.subject | tingkat pengangguran terbuka | en_US |
dc.subject | SDGs | en_US |
dc.title | Pemodelan Tingkat Pengangguran Terbuka di Kabupaten /Kota Provinsi Sumatera Utara Menggunakan Metode Geographichally Weigthed Regression | en_US |
dc.title.alternative | Modeling Open Unemployment Rates in Regencies/Cities of Nort Sumatra Province Using The Geographically Weighted Regression Method | en_US |
dc.type | Thesis | en_US |
dc.identifier.nim | NIM190803006 | |
dc.identifier.nidn | NIDN0013085903 | |
dc.identifier.kodeprodi | KODEPRODI44201#Matematika | |
dc.description.pages | 81 Pages | en_US |
dc.description.type | Skripsi Sarjana | en_US |