Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Ekonomi dan Pembangunan Jurnal Litbang Sukowati : Media Penelitian dan Pengembangan
Aida Meimela
Badan Pusat Statistik Provinsi Sumatera Utara
Humanities Economics, Econometrics & Finance Education Environmental Science Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
MODELING OF THE NUMBER OF TUBERCULOSIS CASES IN INDONESIA Aida Meimela
Jurnal Litbang Sukowati : Media Penelitian dan Pengembangan Vol 4 No 2 (2021): Vol. 4 No. 2, Mei 2021
Publisher : Badan Perencanaan Pembangunan Daerah, Penelitian dan Pengembangan Kabupaten Sragen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32630/sukowati.v4i2.204

Abstract

One of the health issues listed in the Sustainable Development Goals (SDGs) is to end the tuberculosis epidemic in 2030. Indonesia is the country with the third-highest number of tuberculosis cases in the world after India and China in 2018. Aims of this study to model the number of tuberculosis cases in each province in Indonesia, depending on the characteristics of each region. Geographically Weighted Lasso (GWL) is a method used to overcome the local multicollinearity that appears in the Geographically Weighted Regression (GWR) model. By using this method, each region will have a different regression model according to its respective characteristics. There is local multicollinearity (VIF> 10) in each explanatory variable used. Banten, West Java, South Kalimantan, East Kalimantan, East Nusa Tenggara and Papua Province are provinces where all research variables affect the number of tuberculosis cases. The variable that has the most significant effect on the number of tuberculosis cases in each region in Indonesia is the number of health centers. Therefore, to end the number of tuberculosis cases, the government should increase the number of health centers and improve the health service.
MODEL HUBUNGAN JUMLAH PENGANGGURAN DAN INDEKS KEDALAMAN KEMISKINAN DI PULAU SUMATERA TAHUN 2019 MENGGUNAKAN REGRESI NONPARAMETRIK SPLINES Aida Meimela
Jurnal Ilmu Ekonomi dan Pembangunan Vol 20, No 2 (2020): Jurnal Ilmu Ekonomi dan Pembangunan
Publisher : Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jiep.v20i2.41701

Abstract

Poverty does not only focus on decreasing the number of poor people. There is an important thing that must also be considered, namely the Poverty Gap Index (P1). From year to year, the poverty gap index for all regencies/cities in Sumatra tends to stagnate. While the island of Sumatra is the second island with the largest population in Indonesia. This should be a serious concern for the government. One of the factors that influence the poverty gap index is unemployment. The more people who are unemployed can increase the poverty gap index. Therefore we need to model the relationship between the number of unemployment and poverty gap index. The approach used is nonparametric regression modeling where the residual value is not normally distributed. The model is smoothing splines regression and quantile splines regression (median, τ = 0, 5). Meanwhile, to see the best model performance by looking at the RMSE values of both models. From the results of the study, it was found that the quantile regression smoothing splines model was better because the RMSE value was lower than the regression smoothing splines.Keywords: poverty gap, unemployment, quantile regressionJEL Classification: I32, J64, C21
MODEL PENGARUH TINGKAT SETENGAH PENGANGGURAN, PEKERJA INFORMAL DAN PENGELUARAN PERKAPITA DISESUAIKAN TERHADAP KEMISKINAN DI INDONESIA TAHUN 2015-2017 Aida Meimela
Jurnal Ilmu Ekonomi dan Pembangunan Vol 19, No 1 (2019): Jurnal Ilmu Ekonomi dan Pembangunan
Publisher : Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jiep.v19i1.25518

Abstract

Indonesia's poverty rate in the last five years has always decreased annually to 10,64 percent (2017). However, this pattern is not followed by all provinces in Indonesia. Some provinces experience fluctuations every year. Even in 2017, poverty has risen in some provinces. This condition is influenced by some factors of both labor and economy. From the existing literature, there is little research on the effects of underemployment rate, informal workers and adjusted per capita spending on poverty in Indonesia. Therefore, this research is very important to do. This study aims to model the underemployment rate, informal workers and per capita expenditure on poverty using the panel data regression analysis of the 2015-2017 period. The result of the research shows that the best model is Random Effect Model (REM). The rate of underemployment has a positive and significant impact on poverty (level of confident 90 percent). In addition, per capita expenditures have negative and significant impact on poverty. The results of the study show that the government is expected to pay more attention to the indicator of the underemployment rate, because this variable has a largest influence(o,04 percent) on poverty compared to all variables.Keywords : labor, panel regression, underemployment, poverty, random effect model
Co-Authors