?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=COMPARISON+OF+GEOGRAPHICALLY+WEIGHTED+PANEL%0D%0AREGRESSION+(GWPR)+AND+GEOGRAPHICALLY+TEMPORALLY%0D%0AWEIGHTED+REGRESSION+(GTWR)+METHODS+FOR+SPATIAL+DATA%0D%0A(CASE+STUDY+OF+THE+INFLUENCE+OF+POVERTY+FACTORS+ON+THE%0D%0AAMOUNT+OF+MINIMUM+WAGES+IN+PROVINCES+IN+INDONESIA+IN%0D%0A%0D%0A2020+%E2%80%93+2022)&rft.creator=MONICA%2C++RENTA+APRIANI&rft.subject=500+ilmu+pengetahuan+alam+dan+matematika&rft.subject=510+Matematika&rft.description=This+study+aims+to+compare+the+Geographically+Weighted+Panel+Regression%0D%0A(GWPR)+method+and+the+Geographically+Temporal+Weighted+Regression+(GTWR)%0D%0Amethod+in+describing+the+spatial-temporal+pattern+of+poverty+factors+on+the+amount%0D%0Aof+Provincial+Minimum+Wage+(UMP)+in+Indonesia.+The+GWPR+method+is+a%0D%0Acombination+of+Geographically+Weighted+Regression+(GWR)+with+panel+data%0D%0Aregression+that+will+analyze+the+spatial+variation+of+each+region.+In+contrast%2C+the%0D%0AGTWR+method+handles+data+non-stationarity+both+from+spatial+and+temporal%0D%0Aaspects+simultaneously.+In+this+study%2C+the+GWPR+method+will+select+the+best%0D%0Aregression+model+by+involving+two+tests%2C+namely+the+Chow+Test+and+the+Hausman%0D%0ATest+by+producing+a+Fixed+Effect+Model+(FEM).+Meanwhile%2C+the+GTWR+method%0D%0Auses+multiple+linear+regression+to+determine+the+independent+variables+that+have+a%0D%0Asignificant+effect+on+the+dependent+variable.+In+this+study%2C+the+GWPR+and+GTWR%0D%0Amethods+select+the+optimum+bandwidth+using+Cross-Validation+(CV)+with+the%0D%0Asmallest+value+that+can+be+used.+To+compare+the+GWPR+and+GTWR+methods+that%0D%0Aare+good+to+use%2C+this+study+will+measure+the+best+model+with+the+largest+R2+value%2C%0D%0Athe+smallest+RMSE%2C+and+the+smallest+AIC.+The+results+of+the+study+show+that+both%0D%0Amethods+between+GWPR+and+GTWR+will+produce+significant+variables+in+the%0D%0Ainfluence+of+poverty+on+minimum+wages+in+various+provinces+by+creating+a%0D%0Avisualization+of+the+distribution+map+pattern+with+significant+independent+variables%0D%0Afor+each+province+in+Indonesia.%0D%0A%0D%0AKeywords%3A+GWR%2C+GWPR%2C+GTWR%2C+Poverty%2C+Spatial+temporal.%0D%0A%0D%0A%0D%0A%0D%0APenelitian+ini+bertujuan+untuk+membandingkan+metode+Geographically+Weighted%0D%0APanel+Regression+(GWPR)+dan+metode+Geographically+Temporal+Weighted%0D%0ARegression+(GTWR)+dalam+menggambarkan+pola+spasial-temporal+pada+faktor%0D%0Akemiskinan+terhadap+besaran+Upah+Minimum+Provinsi+(UMP)+di+Indonesia.%0D%0AMetode+GWPR+merupakan+gabungan+Geographically+Weighted+Regression+(GWR)%0D%0Adengan+regresi+data+panel+yang+akan+menganalisis+variasi+spasial+setiap+daerah.%0D%0ASebaliknya%2C+metode+GTWR+untuk+menangani+ketidakstasioneran+data+baik+dari%0D%0Aaspek+spasial+maupun+temporal+secara+bersamaan.+Pada+penelitian+ini%2C+metode%0D%0AGWPR+akan+memilih+model+regresi+terbaik+dengan+melibatkan+dua+uji+yaitu%2C+Uji%0D%0AChow+dan+Uji+Hausman+dengan+menghasilkan+Fixed+Effect+Model+(FEM).%0D%0ASedangkan%2C+metode+GTWR+menggunakan+regresi+linear+berganda+untuk%0D%0Amengetahui+variabel+independen+berpengaruh+signifikan+terhadap+variabel%0D%0Adependen.+Dalam+penelitian+ini%2C+metode+GWPR+dan+GTWR+memilih+bandwidth%0D%0Aoptimum+dengan+menggunakan+Cross-Validation+(CV)+dengan+nilai+terkecil+yang%0D%0Adapat+digunakan.+Untuk+membandingkan+metode+GWPR+dan+GTWR+yang+baik%0D%0Adigunakan%2C+dalam+penelitian+ini+akan+mengukur+model+terbaik+dengan+nilai+R2%0D%0Aterbesar%2C+RMSE+terkecil%2C+dan+AIC+terkecil.+Hasil+penelitian+menunjukkan+kedua%0D%0Ametode+antara+GWPR+dan+GTWR+akan+menghasilkan+variabel-variabel+yang%0D%0Asignifikan+dalam+pengaruh+kemiskinan+terhadap+upah+minimum+di+berbagai%0D%0Aprovinsi+dengan+membuat+visualisasi+pola+peta+persebaran+dengan+variabel%0D%0Aindependen+yang+signifikan+untuk+setiap+provinsi+di+Indonesia.%0D%0A%0D%0AKata+Kunci%3A+GWR%2C+GWPR%2C+GTWR%2C+Kemiskinan%2C+Spasial+temporal.&rft.publisher=FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM&rft.date=2024-08-09&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F82401%2F1%2FABSTRAK%2520-%2520Monica%2520Apriani.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F82401%2F2%2FSKRIPSI%2520FULL%2520-%2520Monica%2520Apriani.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F82401%2F3%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN%2520-%2520Monica%2520Apriani.pdf&rft.identifier=++MONICA%2C+RENTA+APRIANI++(2024)+COMPARISON+OF+GEOGRAPHICALLY+WEIGHTED+PANEL+REGRESSION+(GWPR)+AND+GEOGRAPHICALLY+TEMPORALLY+WEIGHTED+REGRESSION+(GTWR)+METHODS+FOR+SPATIAL+DATA+(CASE+STUDY+OF+THE+INFLUENCE+OF+POVERTY+FACTORS+ON+THE+AMOUNT+OF+MINIMUM+WAGES+IN+PROVINCES+IN+INDONESIA+IN+2020+%E2%80%93+2022).++FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM%2C+UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F82401%2F