PENGARUH PDRB, IPM, DAN JUMLAH PENDUDUK TERHADAP TINGKAT KEMISKINAN DI JAWA TIMUR
The aimof this study is to analyze the influence of Gross Regional Domestic Product (GRDP), Human Development Index (IPM), and Population on the poverty level in East Java from 2017 to 2020.”This research applies two analytical techniques, namely descriptive analysis and regres...
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| Format: | Article |
| Language: | English |
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Department of Economic Development, Faculty of Business and Economic, Universitas Surabaya
2023-07-01
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| Series: | Ekonomi dan Bisnis |
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| Online Access: | https://doi.org/10.24123/jeb.v27i1.5732 |
| _version_ | 1797431022601633792 |
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| author | Baskoro Herlambang Nilam Septi Ariria Rachmawati |
| author_facet | Baskoro Herlambang Nilam Septi Ariria Rachmawati |
| author_sort | Baskoro Herlambang |
| collection | DOAJ |
| description | The aimof this study is to analyze the influence of Gross Regional Domestic Product (GRDP), Human Development Index (IPM), and Population on the poverty level in East Java from 2017 to 2020.”This research applies two analytical techniques, namely descriptive analysis and regression panel data. Descriptive analysis techniques are applied to describe data in detail through the use of graphs or tables. On the other hand, panel data regression analysis provides an explanation of the relationship between units and time, and is a combination of data from various groups and certain time periods.“The data used in this study is secondary data obtained from the Central Bureau of Statistics.”The“data consists of cross-sectional data covering 38 Regencies/Cities in East Java Province, as well as time-series data covering the period 2017-2020.”In conclusion, from the analysis performed, the most optimal regression model is“the Random Effect Model (REM) or Generalized Least Square”(GLS), by calculating individual effects and time effects. The research results obtained are“GRDP and HDI have a significant negative effect on the poverty level,”then there is a positive“significant effect between population size and poverty level.”Overall, GRDP, HDI, and Population simultaneously influence fluctuations in the poverty rate by 60.90% |
| first_indexed | 2024-03-09T09:35:56Z |
| format | Article |
| id | doaj.art-8f44d185490c4bfdb2db461aa138d9f6 |
| institution | Directory Open Access Journal |
| issn | 1410-9204 2655-8858 |
| language | English |
| last_indexed | 2024-03-09T09:35:56Z |
| publishDate | 2023-07-01 |
| publisher | Department of Economic Development, Faculty of Business and Economic, Universitas Surabaya |
| record_format | Article |
| series | Ekonomi dan Bisnis |
| spelling | doaj.art-8f44d185490c4bfdb2db461aa138d9f62023-12-02T01:53:28ZengDepartment of Economic Development, Faculty of Business and Economic, Universitas SurabayaEkonomi dan Bisnis1410-92042655-88582023-07-012715260https://doi.org/10.24123/jeb.v27i1.5732PENGARUH PDRB, IPM, DAN JUMLAH PENDUDUK TERHADAP TINGKAT KEMISKINAN DI JAWA TIMURBaskoro Herlambang0Nilam Septi Ariria Rachmawati1Universitas Negeri SurabayaUniversitas Negeri SurabayaThe aimof this study is to analyze the influence of Gross Regional Domestic Product (GRDP), Human Development Index (IPM), and Population on the poverty level in East Java from 2017 to 2020.”This research applies two analytical techniques, namely descriptive analysis and regression panel data. Descriptive analysis techniques are applied to describe data in detail through the use of graphs or tables. On the other hand, panel data regression analysis provides an explanation of the relationship between units and time, and is a combination of data from various groups and certain time periods.“The data used in this study is secondary data obtained from the Central Bureau of Statistics.”The“data consists of cross-sectional data covering 38 Regencies/Cities in East Java Province, as well as time-series data covering the period 2017-2020.”In conclusion, from the analysis performed, the most optimal regression model is“the Random Effect Model (REM) or Generalized Least Square”(GLS), by calculating individual effects and time effects. The research results obtained are“GRDP and HDI have a significant negative effect on the poverty level,”then there is a positive“significant effect between population size and poverty level.”Overall, GRDP, HDI, and Population simultaneously influence fluctuations in the poverty rate by 60.90%https://doi.org/10.24123/jeb.v27i1.5732grdphdiovertlyratepanel data regression |
| spellingShingle | Baskoro Herlambang Nilam Septi Ariria Rachmawati PENGARUH PDRB, IPM, DAN JUMLAH PENDUDUK TERHADAP TINGKAT KEMISKINAN DI JAWA TIMUR Ekonomi dan Bisnis grdp hdi overtlyrate panel data regression |
| title | PENGARUH PDRB, IPM, DAN JUMLAH PENDUDUK TERHADAP TINGKAT KEMISKINAN DI JAWA TIMUR |
| title_full | PENGARUH PDRB, IPM, DAN JUMLAH PENDUDUK TERHADAP TINGKAT KEMISKINAN DI JAWA TIMUR |
| title_fullStr | PENGARUH PDRB, IPM, DAN JUMLAH PENDUDUK TERHADAP TINGKAT KEMISKINAN DI JAWA TIMUR |
| title_full_unstemmed | PENGARUH PDRB, IPM, DAN JUMLAH PENDUDUK TERHADAP TINGKAT KEMISKINAN DI JAWA TIMUR |
| title_short | PENGARUH PDRB, IPM, DAN JUMLAH PENDUDUK TERHADAP TINGKAT KEMISKINAN DI JAWA TIMUR |
| title_sort | pengaruh pdrb ipm dan jumlah penduduk terhadap tingkat kemiskinan di jawa timur |
| topic | grdp hdi overtlyrate panel data regression |
| url | https://doi.org/10.24123/jeb.v27i1.5732 |
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