Yuliana Yuliana, Yulfrita Adamy, Edward M.Nur, Rita Zahara
{"title":"教育和健康对亚齐省贫困的影响","authors":"Yuliana Yuliana, Yulfrita Adamy, Edward M.Nur, Rita Zahara","doi":"10.30601/HUMANIORA.V4I2.1296","DOIUrl":null,"url":null,"abstract":"This study aims to analyze the effect of education and health on poverty in districts / cities of Aceh Province 2014-2017. The data used are secondary data in the form of time series data from 2015-2017 and cross section data of 23 districts / cities in Aceh Province. The data analysis technique used in this research is panel data regression, which is a combination of cross-section data with time series data. The data is processed using the software eviews 9. The model used in this study is as follows: Y = α + β1 + Pit + β2 Kit + it. The research results obtained from the fixed effect note that all variables are significant in the model, so that the Fixed Effect Model (FEM) estimation is obtained as follows: Y = 4.72 + 0.02Pit - 0.03Kit + 0.68eit where the constant value is 4.72 percent, it means that education and health towards poverty have a positive relationship of 4.72 percent. The value of the coefficient X1 = 0.02, meaning that the effect of education on poverty has a positive relationship of 0.02. It is interpreted that if the education variable has increased by 1%, there will be an increase of 0.02 percent of poverty. The coefficient value of X2 = -0.03, meaning that the health effect on poverty has a negative relationship of 0.03. It is interpreted that if the health variable has decreased by 1%, there will be a decrease of 0.03 percent towards poverty","PeriodicalId":229556,"journal":{"name":"Jurnal Humaniora : Jurnal Ilmu Sosial, Ekonomi dan Hukum","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Pengaruh Pendidikan Dan Kesehatan Terhadap Kemiskinan Di Kabupaten/ Kota Provinsi Aceh Tahun 2014-2017\",\"authors\":\"Yuliana Yuliana, Yulfrita Adamy, Edward M.Nur, Rita Zahara\",\"doi\":\"10.30601/HUMANIORA.V4I2.1296\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to analyze the effect of education and health on poverty in districts / cities of Aceh Province 2014-2017. The data used are secondary data in the form of time series data from 2015-2017 and cross section data of 23 districts / cities in Aceh Province. The data analysis technique used in this research is panel data regression, which is a combination of cross-section data with time series data. The data is processed using the software eviews 9. The model used in this study is as follows: Y = α + β1 + Pit + β2 Kit + it. The research results obtained from the fixed effect note that all variables are significant in the model, so that the Fixed Effect Model (FEM) estimation is obtained as follows: Y = 4.72 + 0.02Pit - 0.03Kit + 0.68eit where the constant value is 4.72 percent, it means that education and health towards poverty have a positive relationship of 4.72 percent. The value of the coefficient X1 = 0.02, meaning that the effect of education on poverty has a positive relationship of 0.02. It is interpreted that if the education variable has increased by 1%, there will be an increase of 0.02 percent of poverty. The coefficient value of X2 = -0.03, meaning that the health effect on poverty has a negative relationship of 0.03. It is interpreted that if the health variable has decreased by 1%, there will be a decrease of 0.03 percent towards poverty\",\"PeriodicalId\":229556,\"journal\":{\"name\":\"Jurnal Humaniora : Jurnal Ilmu Sosial, Ekonomi dan Hukum\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Humaniora : Jurnal Ilmu Sosial, Ekonomi dan Hukum\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30601/HUMANIORA.V4I2.1296\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Humaniora : Jurnal Ilmu Sosial, Ekonomi dan Hukum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30601/HUMANIORA.V4I2.1296","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pengaruh Pendidikan Dan Kesehatan Terhadap Kemiskinan Di Kabupaten/ Kota Provinsi Aceh Tahun 2014-2017
This study aims to analyze the effect of education and health on poverty in districts / cities of Aceh Province 2014-2017. The data used are secondary data in the form of time series data from 2015-2017 and cross section data of 23 districts / cities in Aceh Province. The data analysis technique used in this research is panel data regression, which is a combination of cross-section data with time series data. The data is processed using the software eviews 9. The model used in this study is as follows: Y = α + β1 + Pit + β2 Kit + it. The research results obtained from the fixed effect note that all variables are significant in the model, so that the Fixed Effect Model (FEM) estimation is obtained as follows: Y = 4.72 + 0.02Pit - 0.03Kit + 0.68eit where the constant value is 4.72 percent, it means that education and health towards poverty have a positive relationship of 4.72 percent. The value of the coefficient X1 = 0.02, meaning that the effect of education on poverty has a positive relationship of 0.02. It is interpreted that if the education variable has increased by 1%, there will be an increase of 0.02 percent of poverty. The coefficient value of X2 = -0.03, meaning that the health effect on poverty has a negative relationship of 0.03. It is interpreted that if the health variable has decreased by 1%, there will be a decrease of 0.03 percent towards poverty