This study aims to investigate the pattern of dynamic relationships between energy consumption, economic growth, and poverty in panel data set of 12 provinces of Eastern Indonesia during the period 2009-2019. PVECM and    FM-OLS were applied to analyze the dynamic link of the variables both in the short and long term. All secondary data used were collected from BPS and the Ministry of Energy and Mineral Resources. The results of this empirical study in the short term corroborate the neutrality hypothesis, which reveals that there is no short-term relationship in the case of energy-growth nexus, energy-poverty nexus, and poverty-growth nexus. In the long term, empirical evidence corroborates the feedback hypothesis in the case of the energy-growth nexus and poverty-growth nexus. Concerning the long-run energy-growth nexus, the increase in energy consumption has a positive effect on the acceleration of economic growth, and also the increase in economic growth requires the fulfillment of adequate energy consumption. Furthermore, a feedback relationship is found in the poverty-growth nexus case which explains that the progress of poverty reduction is significantly determined by sustainable economic growth that supports several previous studies and the trickle-down economics argument or pro-growth-poverty. On the other hand, widespread poverty has a negative impact on the achievement of economic growth.

This study aims to analyze Income Disparities between Regions in the Western Region of Indonesia and the Eastern Region of Indonesia. The type of research used in this study is quantitative research. The variables in this study are Economic Growth. Based on the analysis, the results of this study are the provinces in the Western and Eastern regions of Indonesia are divided into four existing classifications. A total of 2 provinces, namely Jakarta and North Kalimantan Provinces, are among the fast-growing developed regions. A total of 5 provinces, namely Riau Province, Kepulauan Riau, West Papua, Banten and East Kalimantan are among the developed but depressed provinces. A total of 15 provinces namely Central Java, Southeast Sulawesi, Yogyakarta, Central Kalimantan, Jambi, North Sulawesi, Bengkulu, Central Sulawesi, South Sumatra, Maluku, West Sulawesi, North Maluku, South Sulawesi, and Gorontalo Including fast-growing provinces and as 12 provinces, namely West Sumatra, East Java, Bali, South Kalimantan, Lampung, West Kalimantan, West Java, North Sumatra, Aceh, Papua, Kepulauan Bangka Belitung and West Nusa Tenggara are among the many relatively lagging provinces.

Poverty alleviation in Indonesia is strongly influenced by other economic variables. The three main factors used to measure its effect on poverty are economic growth, unemployment and inflation. This study aims to examine and analyze the relationship between theoretical and empirical balance between economic growth, unemployment rate and inflation rate with poverty in Indonesia both in the short and long term. The estimation method used is a dynamic econometric model with the cointegration approach and the Error Correction Model (ECM). The results of this study indicate that the equation model used has cointegration relationships and long-term balance between variables. The estimation results show that there is a short-term effect of economic growth, the unemployment rate and inflation on poverty, while in the long term economic growth and the unemployment rate have a significant effect, while inflation is not significant.

The first purpose of this paper is to develop or construct a new human development composite index and applied to measure the performance of human development in the village / district of West Seram Regency. The second, to develop the priority scale of human development planning. This paper applies quantitative analysis method that is principal component regression (PCR) and clustering analysis (CA). Data is sourced from the Regional Development Planning Agency (Bappeda) of West Seram Regency of year 2016. Application of principal component regression and clustering analysis method, aims to improve the aggregation method of human development composite index developed by UNDP. Composite index compositions resulting from principal component regression and IPM-UNDP largely result in different ranking information but in some villages have the same rank. Based on K-means clustering analysis, there were 3 main clusters, namely high, medium and low cluster. The number of villages in the high cluster is 6 villages, the medium cluster is 13 villages and low cluster is 14 villages.

This study aims to determine the effect of foreign direct investment (FDI) on economic growth and employment. Method, for this purpose, secondary data was collected in the form of annual data from the Central Bureau of Statistics and the Investment and One-Stop Integrated Service (PTSP) Office of Maluku Province. The data were analyzed using simple linear regression. The analysis model used adopts the Cobb Douglas function, namely Q = f (A Kα Lβ) with the assumption that Q is economic growth, K is capital and L is labor and A is technological progress. In the case of this study, it is assumed that economic growth is a function of capital, namely foreign investment (FDI) so that by modifying the Cobb-Douglas production function. The results showed that foreign investment (FDI) has a positive and significant effect on economic growth and employment. The effect of foreign investment (FDI) has a positive and significant effect on economic growth in Maluku Province. Policies that make it difficult for investors need to be reduced. Investment also has an influence on employment. Realized investment can expand production capacity and that will require additional labor.