{"title":"Pengaruh Kemiskinan Terhadap Indeks Pembangunan Manusia (IPM) Di Provinsi Sumatera Selatan Tahun 2016-2020","authors":"Tahan Upoyo Trisno, Munajat, Yetty Oktarina","doi":"10.53488/jba.v7i02.128","DOIUrl":null,"url":null,"abstract":"This study aims to determine the effect of poverty (x), on the human development index (y) in South Sumatra in 2016-2020. The data used is secondary data from the Central Statistics Agency. The analytical method used is panel data regression. The results of the t test show that poverty (x) has a negative and significant effect on the human development index (y). The results of the coefficient of determination test show that the dependent variable can be explained by the independent variable by 12.03% and the remaining 87.97% is explained by other factors outside this model.","PeriodicalId":164157,"journal":{"name":"Jurnal Bakti Agribisnis","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Bakti Agribisnis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53488/jba.v7i02.128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pengaruh Kemiskinan Terhadap Indeks Pembangunan Manusia (IPM) Di Provinsi Sumatera Selatan Tahun 2016-2020
This study aims to determine the effect of poverty (x), on the human development index (y) in South Sumatra in 2016-2020. The data used is secondary data from the Central Statistics Agency. The analytical method used is panel data regression. The results of the t test show that poverty (x) has a negative and significant effect on the human development index (y). The results of the coefficient of determination test show that the dependent variable can be explained by the independent variable by 12.03% and the remaining 87.97% is explained by other factors outside this model.
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