Rahmawati Erma Standsyah
@unesa.ac.id
Faculty of Mathematics and Natural Sciences
State University of Surabaya
RESEARCH, TEACHING, or OTHER INTERESTS
Mathematics, Applied Mathematics, Statistics and Probability, Modeling and Simulation
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Suyanto Suyanto, Muhammad Afdha Alif Almughni, Jajuk Suprijati, Rahmawati Erma Standsyah, and Sayekti Suindyah Dwiningwarni
Fundacja Ekonomistow Srodowiska i Zasobow Naturalnych
G20 member countries are forced to reduce carbon dioxide emissions from the global community as well as economic development constraints from domestic resources and the environment. Literature related to institutional quality and government expenditure is still limited, especially in G20 countries. To provide empirical evidence to support the theoretical argument, the study investigated the effects of institutional quality and government expenditure on CO2 emissions using a balanced panel dataset of nineteen countries that were members of the G20 between 1995 and 2015. Empirical results show that institutional quality is able to reduce carbon emissions. A good government can formulate strict environmental regulations and ensure transparency, which allows investment in green technologies and renewable energy. Other findings suggest that government spending can increase carbon emissions. The findings show that government spending in G20 countries still does not consider environmental impacts. Several policy recommendations are suggested.
Suyanto ., Muhammad Afdha Alif Almughni, Rahmawati Erma Standsyah, Amirul Mustofa, Eny Haryati, Dendy Syahru Ramadhan, and Bayu Taufiq Possumah
Creative Publishing House
The aim of this study is to examine the impact of regional government expenditure on regional autonomy, taking into account indices of social, economic, and ecological resilience within the context of impoverished regions. This study employs panel regression and route analysis techniques to analyze data from 62 districts identified as undeveloped regions in Indonesia throughout the period of 2016–2022. The exogenous factors in this study encompass capital investment, operating expenditure, and balancing funds, whereas the endogenous variable is the village development index. The findings show that (1) capital expenditure, operational expenditure, and balancing funds have an indirect influence on IDM through the economy. (2) Capital expenditure has a negative impact on economic growth because underdeveloped areas are increasingly concentrated in the eastern region and cause economic disparities to grow. (3) Operational expenditure and balancing funds have a positive impact on the regional economy, which also impacts village independence.
Rahmawati Erma Standsyah, Bambang Widjanarko Otok, and Agus Suharsono
AIP Publishing
Bambang Widjanarko Otok, Agus Suharsono, Purhadi Purhadi, Rahmawati Erma Standsyah, and Harun Al Azies
The Institute for Research and Community Services (LPPM) ITB
This study attempted to identify underdeveloped areas in regencies/cities on the island of Java, Indonesia, based on a number of infrastructure indicators. An unsupervised learning approach was used to perform partition clustering with the K-Means, K-Medoids, and CLARA methods. In addition to technically obtaining clustering results and conducting a performance comparison of the three unsupervised learning methods, another objective of this research was to map the clustering results to make it easier to recognize the characteristics of the regions indicated as underdeveloped areas, which should be absolute priorities for infrastructure development. It was found that the best clustering method was the CLARA method, with a connectivity coefficient of 7.4794 and a Dunn’s index value of 0.1042. The partition clustering of regencies/cities on Java Island using the CLARA method based on infrastructure indicators resulted in 99 regencies/cities included in the cluster of areas with underdeveloped infrastructure, while 12 regencies/cities were included in the cluster of areas with developing infrastructure, and 8 regencies/cities were included in the cluster of areas with developed infrastructure.
Rahmawati Erma Standsyah, Bambang Widjanarko Otok, and Agus Suharsono
MDPI AG
The fixed effect meta-analytic structural equation modeling (MASEM) model assumes that the population effect is homogeneous across studies. It was first developed analytically using Generalized Least Squares (GLS) and computationally using Weighted Least Square (WLS) methods. The MASEM fixed effect was not estimated analytically using the estimation method based on moment. One of the classic estimation methods based on moment is the Generalized Method of Moments (GMM), whereas GMM can possibly estimate the data whose studies has parameter uncertainty problems, it also has a high accuracy on data heterogeneity. Therefore, this study estimates the fixed effect MASEM model using GMM. The symmetry of this research is based on the proof goodness of the estimator and the performance that it is analytical and numerical. The estimation results were proven to be the goodness of the estimator, unbiased and consistent. To show the performance of the obtained estimator, a comparison was carried out on the same data as the MASEM using GLS. The results show that the estimation of MASEM using GMM yields the SE value in each coefficient is smaller than the estimation of MASEM using GLS. Interactive GMM for the determination of the optimal weight on GMM in this study gave better results and therefore needs to be developed in order to obtain a Random Model MASEM estimator using GMM that is much more reliable and accurate in performance.
Bambang Widjanarko Otok, Agus Suharsono, Purhadi, Rahmawati Erma Standsyah, and Harun Al Azies
AIP Publishing
Underdeveloped areas are regencies whose territories and communities are less developed than other regions at the national level. The regions of Java island are faster-developing areas than other areas outside of Java, but there are still areas in Java that are classified as underdeveloped areas. The backwardness of the area is measured based on six main criteria, namely economy, human resources, infrastructure, regional financial capacity, accessibility, and regional characteristics. This research can be carried out by compiling a model on the influencing factors of underdeveloped areas with the meta-analysis CFA TSSEM approach. The results of this study show that the analysis of the structural model can be accepted to explain the underdevelopment of areas in Java based on the result the Goodness of Fit Indicates, it is the RMSEA < 0.008 so it can be confirmed that the indicators used in infrastructure variables, HR variables, and regional characteristic variables are suitable to be used to measure the underdeveloped areas in Java.
Bambang Widjanarko Otok, Rahmawati Erma Standsyah, Agus Suharsono, and Purhadi
AIP Publishing