Claim Missing Document
Check
Articles

Found 3 Documents
Search

Pengaruh Tingkat Pengangguran, Kebutuhan Pangan, Peningkatan Gizi, Dan Peningkatan Pendapatan Per Kapita Terhadap Kawasan Rumah Pangan Lestari (KRPL) Supardi Supardi; Nurshadrina Kartika Sari
RELASI : JURNAL EKONOMI Vol 14 No 2 (2018)
Publisher : STIE Mandala Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31967/relasi.v14i2.267

Abstract

This study aims to analyze the effect of unemployment rate, food demand, nutrition improvement and income increase per capita after applying Sustainable Food House (KRPL) in Jember Regency. Analysis tool used Multiple Regression Analysis is the number of independent variables used to predict variables depend on more than one. The research design used is associative design, ie to analyze the relationship between one variable with other variables or how a variable affects other variables. The writer uses case study with quantitative approach while the unit of analysis in this research is the influence of Unemployment rate, Food Needs, Nutrition Improvement, and Increase Revenue per Capita to Area Sustainable Food House (KRPL). The sampling method used is the census method, which is a comprehensive sampling of 3 villages with a 3-year study period from 2014 to 2016. Analytical techniques are multiple regression analysis, F test and t test. Keywords: unemployment, food, nutrition, income and krpl.
Quality Reliability Service Towards Student Satisfaction Fajar Isnaeni; Suwignyo Widagdo; Supardi Supardi
International Journal of Social Science and Business Vol. 3 No. 4 (2019): November
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ijssb.v3i4.21401

Abstract

This study aims to examine and analyze the simultaneous effect of service quality on student satisfaction, test and analyze the partial effect of service quality on student satisfaction, test and analyze variables that have a dominant influence on student satisfaction. This research method uses multiple linear regression analysis which is used to determine how much influence the independent (independent) variables, namely Tangible, Reliability, Responsiveness, Assurance, Empathy on the dependent variable is student satisfaction. Research site is at STES Ihya 'Ulumiddin Banyuwangi. The study took a sample of 39 people. While the results of this study can be drawn as follows, the variables Tangible, Reliability, Responsiveness, Assurance and Emphaty simultaneously affect student satisfaction. The partial test of the Reliability variable, Responsiveness, Assurance and Emphaty is positive, but the Tangible variable is negative. Reliability variables are variables that have a dominant and significant influence on student satisfaction.
Pengaruh Tingkat Pengangguran, Kebutuhan Pangan, Peningkatan Gizi, Dan Peningkatan Pendapatan Per Kapita Terhadap Kawasan Rumah Pangan Lestari (KRPL) Supardi Supardi; Nurshadrina Kartika Sari
RELASI : JURNAL EKONOMI Vol 14 No 2 (2018)
Publisher : STIE Mandala Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31967/relasi.v14i2.267

Abstract

This study aims to analyze the effect of unemployment rate, food demand, nutrition improvement and income increase per capita after applying Sustainable Food House (KRPL) in Jember Regency. Analysis tool used Multiple Regression Analysis is the number of independent variables used to predict variables depend on more than one. The research design used is associative design, ie to analyze the relationship between one variable with other variables or how a variable affects other variables. The writer uses case study with quantitative approach while the unit of analysis in this research is the influence of Unemployment rate, Food Needs, Nutrition Improvement, and Increase Revenue per Capita to Area Sustainable Food House (KRPL). The sampling method used is the census method, which is a comprehensive sampling of 3 villages with a 3-year study period from 2014 to 2016. Analytical techniques are multiple regression analysis, F test and t test. Keywords: unemployment, food, nutrition, income and krpl.