This study aims to look at the influence of the variables government spending on health and education, poverty and Gross Domestic Product (GDP) of the Human Development Index (HDI) in the province of Aceh. The analytical method used in this research is the analysis of the panel data regression model parameter estimation using a random effects model (REM). The data used is the panel data during the period 2010-2014. The results showed that the variables government spending on education and health sector no significant effect on the human development index, this happens because the district/city governments allocate their spending still more dominant that the type of expenditure that are not directly impact the IPM. While poverty variables significant negative effect on the human development index, then with reduced levels of poverty can enhance human development index. GRDP positive and significant effect on the human development index, which means that the GDP increases, IPM will also increase.Penelitian ini bertujuan untuk melihat pengaruh dari variabel-variabel belanja pemerintah pada sektor kesehatan dan pendidikan, tingkat kemiskinan serta Produk Domestik Regional Bruto (PDRB) terhadap Indeks Pembangunan Manusia (IPM) di Provinsi Aceh. Metode analisis yang digunakan dalam penelitian ini adalah analisis regresi data panel dengan estimasi parameter model menggunakan random effect model (REM). Data yang digunakan adalah data panel selama periode 2010-2014. Hasil penelitian menunjukan bahwa variabel pengeluaran pemerintah di sektor pendidikan dan kesehatan tidak berpengaruh signifikan terhadap indeks pembangunan manusia, hal ini terjadi karena pemerintah kabupaten/kota masih lebih dominan mengalokasikan belanjanya yang pada jenis belanja yang secara tidak lansung memberikan pengaruh terhadap IPM. Sedangkan variabel kemiskinan berpengaruh negatif dan signifikan terhadap indeks pembangunan manusia, maka dengan menurunnya tingkat kemiskinan dapat meningkatkan indeks pembangunan manusia. PDRB berpengaruh positif dan signifikan terhadap indeks pembangunan manusia, yang berarti PDRB meningkat maka IPM juga akan meningkat.

This research aims to analyze the level of exports in Indonesia by using Time Series data from the year 1990 to 2015 against a variable interest rate loands, gross domestic product, and the exchange rate. Methods of analysis used i.e, Auto Regressive Distributed Lagged (ARDL). The results showed that the three variables have no Granger which is caused by the difference of the order on the test stasioner. Based on a test of wald for the short term that gained and the long-term gross domestic product, exchange rates and interest rates significantly influential credit toward export.Keywords:ARDL, export, interest rate loands, gross domestic product, exchange rates.AbstrakPenelitian ini bertujuan untuk menganalisis tingkat ekspor di Indonesia dengan menggunakan data Time Series dari tahun 1990 sampai 2015 terhadap variabel suku bunga kredit, produk domestik bruto, dan nilai tukar. Metode analisis yang digunakan yaitu AutoRegressive Distributed Lagged (ARDL).Hasil penelitian menunjukkan bahwa ketiga variabel tidak memiliki kointegrasi yang disebabkan oleh perbedaan ordo pada uji stasionernya. Berdasarkan uji wald didapat bahwa untuk jangka pendek dan jangka panjang produk domestik bruto, nilai tukar dan suku bunga kredit berpengaruh secara signifikan terhadap ekspor.

This study analyzes the occurrence of economic convergence between districts / cities in Aceh Province and looks at the factors that can accelerate the economic convergence. This study uses panel data from 23 districts / cities in Aceh Province for the period 2008-2018. The results found from this study are that there has been economic convergence, both sigma convergence and beta convergence, in Aceh Province. Factors that significantly influence economic convergence in Aceh Province are the average length of schooling, life expectancy, and the special autonomy fund. The time needed to get to half the convergence process is 4.10 years with the resulting conditional beta convergence rate of 16.89%.

This study aimed to analyze the effect of Macroeconomic variables in the form of Economic Growth, Inflation and interest rate of Bank Indonesia (7-Day Repo rate) on Non Performing Loans (NPL) in Indonesia. This study uses annual time series data from 2000 to 2017 with a total sample of 18 years. The model used is Auto Regressive Distributed Lags (ARDL) using Eviews 9. Software The results show that in the short run Inflation has a negative effect on Non Performing Loans (NPL) and Inflation in the previous year  (Lag-1) has a significant positive effect whereas in the long run Inflation has a negative effect, maintained inflation at a reasonable limit to foster a good climate for entrepreneurs to be a stimulus so that they are able to fulfill their obligations, in the long run Economic growth has a significant negative effect and interest rates have a significant positive effect. It is hoped that the government can be more careful in setting the 7-Day Repo rate, given the positive response shown to Non Performing Loans (NPL). In addition, the government must also be able to maintain sustainable economic growth given its negative relationship to Non Performing Loans (NPL). It is recommended for further researchers to add other variables such as stock index, exchange rate, Capital Adequacy Ratio (CAR) and Charge-off policy (PH) of non-performing loans.

Gross domestic product (GDP) is one indicator for measuring a country's economic growth. However, the increase in GDP and population growth are affecting CO 2 emissions. This study analyses the effects of GDP and population density on CO 2 emissions in Indonesia. To this end, it used the Cobb-Douglas model, and parameter estimation using Ant Colony Optimisation algorithm. The analysis of the results reveals that GDP and population density influence CO 2 emissions in Indonesia significantly, and significantly follows the Cobb-Douglas model with increasing return to scale characteristics. Thus, an increase in GDP and population density will lead to increased CO 2 emissions in Indonesia.