ROBUST GEOGRAPHICALLY WEIGHTED REGRESSION WITH LEAST ABSOLUTE DEVIATION (LAD) ESTIMATION AND M-ESTIMATION ON GRDP OF WEST JAVA PROVINCE

Spatial regression analysis is a form of regression model that considers spatial effects. Geographically weighted regression (GWR) is the spatial regression methods that can be used to deal with the problem of spatial diversity. This method generates local model parameter estimates for each observation location. The application of spatial statistics can be done in all areas such as the problem of poverty. Poverty can be influenced by factors of proximity between regions, so that in determining the poverty factor, the proximity factor of the region cannot be ignored. West Java Province is a province with the largest population, so this study aims to model the poverty data in West Java Province by incorporating spatial effects. The weighting function used for the GWR model is the function of the fixed and adaptive kernels. The analysis results show that the fixed exponential kernel function has the smallest cross validation (CV) value, so the weighting matrix used in the model is determined by the exponential kernel function. The largest value and the smallest AIC value are owned by the GWR model with an exponential kernel function. Based on the results obtained by the the ANOVA table to test GWR's global goodness, the GWR model is more effective than global regression. Therefore, the GWR model is the best model when it used in West Java’s poverty cases. The effect of each explanatory variable on the percentage of poverty varies in each district/city in West Java Province.

Gross Regional Domestic Product (GDP) is one of the economic indicators according to various economic instruments in which clearly visible macro-economic conditions of a region. Infrastructure is the most primary public infrastructure in supporting a country's economic activities, and the availability of infrastructure greatly determines the level of efficiency and effectiveness of economic activities. This study aims to analyze how much electricity, road, and health infrastructure affects gross regional domestic product in Sidoarjo Regency. This research covers the area of Sidoarjo Regency. This study uses secondary data obtained from the Central Statistics Agency with a period of 15 years from 2005-2019. The analysis technique used is Multiple Linear Regression Analysis with Ordinary Least Square (OLS) model using computer tools SPSS program (Statistic Program For Social Science) Version 13.0 that shows the influence between free variables and bound variables. The end result is that electricity infrastructure variables have a positive and significant influence on gross regional domestic product in Sidoarjo Regency. Variable road infrastructure and health infrastructure have a positive but insignificant influence on gross regional domestic product in Sidoarjo Regency.

This study intends to examine the implications of stagflation risk on capital utilization in the East Java from a macroeconomic perspective. Non-random, saturated sampling was used in the sampling procedure. The quantitative nature of this study approach allows for the testing of ideas from unbiased perspectives. Using time series secondary data 2014 to 2022 with capital utilization from the One-Stop Investment and Integrated Services Office (DPMPTSP), inflation and open employment rate from the Bank of Indonesia, and Gross Regional Domestic Product (GRDP) from the Central Statistics Agency (BPS). Data analysis techniques using multiple linear regression processed using ordinary least squares (OLS) by EViews12. The findings were as follows: 1). Capital utilization is positively and significantly impacted by the stagflation trap of gross regional domestic product (GRDP). 2). Capital utilization positive effects from the Stagflation trap of inflation, although the effect is insignificant. 3). The open unemployment rate's Stagflation trap has a positive and significant effect on capital utilization. 4). The macroeconomic stagflation trap, which is represented by the gross regional domestic product (GRDP), inflation rate, and open unemployment rate, has a substantial impact on capital utilization simultaneously. This study's findings are statistically in line with previous findings and theoretical literature.

This research is an observational case study with 9 Economic Sectors in North Sumatra Province, with a period of 5 years (2003-2014). The research object consists of 3 variables, namely: Domestic Investment, Foreign Investment and Labor. Hypothesis, it is expected that three variables collectively influence Gross Regional Domestic Product (GRDP) in North Sumatra. Secondary data was obtained from the publication of survey results related to Indonesian Statistics (BPS) with the 2003-2014 time series, thus forming balance sheet data collected, because data variables across time and in various areas were available with a total of 108 cross-sections of data. Data analysis used log linear regression with the help of statistical tests of the E-views 6.0 application program using the selected Fixed Effect Model regression method. The results of this research show that three variables are thought to influence Gross Regional Domestic Product (GRDP) in North Sumatra, assuming ceteris paribus conditions that: Investment, Labor have a positive influence on Gross Regional Domestic Product (GRDP) in North Sumatra. The percentage of Domestic Investment, Foreign Investment and Labor has a positive effect on Gross Regional Domestic Product (GRDP) in North Sumatra.

Poverty remains a persistent challenge in Indonesian urban centers, including Tasikmalaya City in West Java Province. This study investigates the determinants of poverty by employing per capita Gross Regional Domestic Product (GRDP), average years of schooling, and the open unemployment rate as explanatory variables. Using multiple linear regression analysis based on 13 years of data (2012–2024) from the Central Bureau of Statistics (BPS) of Tasikmalaya City, the findings reveal that per capita GRDP significantly reduces poverty, whereas education and unemployment show no significant effects. These results underscore the critical role of economic growth, while education and labor market conditions exhibit only limited short-term influence on poverty alleviation, particularly in urban economies with large informal sectors. The study provides policy recommendations for local governments to design more effective poverty alleviation strategies aligned with the SDGs and regional development agendas.

The study aims to analyse whether the unemployment, poverty and education factors affect gross Regional domestic product (GDP) in Merauke Regency in 2010-2018. The data used in this study is secondary data. The method of collecting data using secondary data from the official data is issued by the Department of Statistics Central of Merauke District. For data processing is done using SPSS 21 program.
 The results of this study showed the variables of unemployment, poverty and education for the four districts studied; The slope district, Kurik District, Naukenjerai District and Sota district are simultaneously affecting the value of the gross Regional domestic product (GDP) of Merauke Regency. Result coefficient of determination (R²) 91.7% indicates that the variables of unemployment, poverty, and education have a significant influence on the improvement of the gross Regional domestic product (GDP). From the results of this research can also be concluded that the unemployment variables that affect the change in the value of gross Regional domestic product (GDP) in Merauke District lower education impact on the gross Regional domestic product value ( GDP) is because awareness of the importance of education in this district is still minimal especially in four districts that are carefully

Businesses quality in the agricultural sector that are involved in the livestock industry are particularly susceptible to negative economic or social effects. Breeders and farmers, particularly those who raise beef cattle will be affected by continues and incidentally price changes or currency exchange rates because these factors have a significant impact on the beef cattle farming industry. The Gross Regional Domestic Product (GRDP) of a region changes as a result of population expansion. This study's goal was to examine how population growth and economic development affect the welfare of beef cattle breeders in West Java Province, with a particular emphasis on four (four) districts that are important hubs for small-scale livestock production: Subang Regency, Purwakarta Regency, Bogor Regency, and Sukabumi Regency. The quantitative methodology of this study analyzes numerical data modified by statistical techniques and literature review. The macroeconomic variables of population and breeder welfare are the focus of the literature review. The West Java Central Bureau of Statistics, the Office responsible for Animal Husbandry and Health Functions for Subang, Purwakarta, Bogor, and Sukabumi Regencies, as well as data from relevant journals and articles, are all sources of secondary data. Data analysis was conducted applying multiple regression analysis techniques. The study's findings concluded that the wellbeing of breeders in Indonesia's West Java Province was significantly impacted by population expansion and economic development. Keywords: Animal farming economy, beef cattle breeders, welfare, economic growth

This study aims to examine and analyze the direct and indirect effects of investment in the agricultural sector, regional capital expenditures for the agricultural sector, the Provincial Minimum Wage (UMP) on the absorption of labor in the agricultural sector in South Sulawesi Province through the Gross Regional Domestic Product (GRDP) ) the agricultural sector and the Human Development Index (IPM). The data used in this study is secondary data from the Central Bureau of Statistics (BPS) in the form of a time series from 1999 to 2019. In this study using the structural equation regression analysis method using SPSS software . The analysis technique used in this study is Path Analysis. The results of the study show that investment in the agricultural sector has an effect both directly and indirectly on the employment of the agricultural sector in South Sulawesi Province through the agricultural sector's Gross Regional Domestic Product (GRDP). Regional capital expenditures for the agricultural sector influence both directly and indirectly the absorption of labor in the agricultural sector in South Sulawesi Province through the agricultural sector's Gross Regional Domestic Product (GRDP) and the Human Development Index (IPM). The Provincial Minimum Wage (UMP) has no direct or indirect effect on employment in the agricultural sector in South Sulawesi Province through the agricultural sector's Gross Regional Domestic Product (GRDP) and the Human Development Index (IPM).

Human development cannot run properly without macro and microeconomic factors. The government's role is very important because it can regulate the flow of the economy so that, in the end, it can meet human material and non-material needs and achieve maslahah. This study aims to analyze the influence of the Gross Domestic Regional Product (GDRP), poverty rate, unemployment rate, economic function, health, and education on the Islamic Human Development Index (I-HDI) in several provinces in Indonesia. The methodology used is quantitative, with secondary data from the Central Statistics Agency (BPS) and the Ministry of Finance for 2010–2021. Data analysis method using Panel Data Regression with Random Effect Model (REM). The results of this study indicate that simultaneously the variables Gross Domestic Regional Product (GDRP), poverty rate, unemployment rate, economic, health, and education functions have a significant effect on the Islamic Human Development Index (I-HDI) in all research areas. At the same time, each variable has an influence on I-HDI except for the poverty rate and economic function. Based on these results, we provide alternative proxies to develop I-HDI and urge national and international databases and independent international Muslim organizations to start publishing proposed I-HDI for all Muslim-majority countries every year. As such, it will provide an opportunity to monitor human development across countries over time, and the I-HDI model can be improved over time. Keywords: Maqashid Syariah, Pandemic, Islamic Human Development Index, Human Development JEL: I31, O15, P46

This study discusses the forecasting of the Open Unemployment Rate (OUR) in West Java Province using two time series approaches: Vector Autoregressive with Exogenous variables (VARX) and Support Vector Regression (SVR). The dataset consists of monthly observations from 2018 to 2023, including variables such as OUR, the Labor Force Participation Rate (LFPR), Gross Regional Domestic Product (GRDP), and the Human Development Index (HDI). Based on the optimal lag selection using the AIC, the VARX model produced the best lag configuration of (5,2), consisting of five lags for endogenous variables and two for exogenous variables. Meanwhile, the SVR model was developed through Grid Search to find the best parameter combination, resulting in a linear kernel with and . The evaluation results showed that the SVR model performed better than VARX, with MSE, RMSE, and MAPE values of 0.24, 0.49, and 6%, respectively, lower than those of the VARX model, which reached 0.68, 0.82, and 8.4%. SVR was selected as the best model and used to forecast the OUR until the end of 2025. The forecast results indicated a spike in OUR at the beginning of 2024 at 8.52%, followed by a declining trend that continues and stabilizes in the range of 7.96%-8.12% by the end of 2025. In conclusion, SVR outperforms VARX in predictive accuracy, while VARX remains useful for analyzing inter-variable relationships.

This study aims to analyze the influence of Foreign Direct Investment (FDI), Domestic Investment (DI), and Labor Force Participation Rate (LFPR) on the growth of Gross Regional Domestic Product (GRDP) in Bali Province. This research employs a quantitative approach using secondary time series data on an quartal basis from 2015 to 2022, obtained from the Central Statistics Agency (BPS) and other relevant institutions. The analytical method used is multiple linear regression with the assistance of EViews 9 software. The results show that, partially, FDI, DI, and LFPR have a positive and significant effect on GRDP growth in Bali Province. Simultaneously, the three variables also have a significant influence on GRDP. The Adjusted R-Squared value of 0.543 indicates that approximately 54.3% of the variation in GRDP can be explained by FDI, DI, and LFPR, while the remaining variation is influenced by other variables outside the model. However, the regression model experiences autocorrelation, indicating that there are time dynamics not fully captured by the model. This study highlights the importance of investment and the optimization of the labor force in supporting regional economic growth.

This study aims to analyze the influence of capture fisheries and marine aquaculture production on the contribution to the Gross Regional Domestic Product (GRDP) of the fisheries sector in Kepulauan Meranti Regency during the 2019–2024 period. This research is motivated by the importance of the fisheries sector as one of the main pillars of the coastal regional economy, especially in island regions where communities are heavily dependent on fisheries activities. Despite having great potential, the contribution of the capture fisheries and marine aquaculture subsectors to the regional GRDP shows diverse dynamics due to environmental changes, technology, and socio-economic factors of coastal communities. The research method employed is a quantitative method with descriptive and associative approaches. The data used are secondary data obtained from the Central Statistics Agency (BPS) of Riau Province and the Department of Marine Affairs and Fisheries (DKP) of Kepulauan Meranti Regency. Research variables include capture fisheries production, marine aquaculture production, and fisheries GRDP contribution. Data analysis was conducted using a multiple linear regression model to examine the simultaneous and partial effects of both fisheries subsectors on the economic added value of the fisheries sector in the region. The research findings indicate that capture fisheries production has a significant influence on increasing the fisheries sector GRDP, demonstrating that fish capture activities remain the backbone of the coastal community's economy. Meanwhile, marine aquaculture production provides a relatively fluctuating contribution but shows an increasing trend from year to year, indicating the great potential of this subsector to be developed as a new sustainable source of economic growth. Overall, the improved performance of both fisheries subsectors plays an important role in strengthening the regional economy, creating new employment opportunities, and improving the welfare of communities in Kepulauan Meranti Regency.

The COVID-19 pandemic began at the end of 2019 in.Wuhan, China, spreading rapidly to all parts of the world. This virus was detected in Indonesia in February 2020, and then the government began to make social restriction policies in March 2020. All countries in the world experienced a fairly severe economic shock. The limited mobility of people impacts decreasing all forms of activities that require face-to-face contacts, such as tourism, transportation, hospitality, etc. It causes a decrease in economic growth which can be measured by the size of the gross regional domestic product. This analysis uses Gross Regional Domestic Product (GRDP) data as a Y variable, general allocation funds (X1), profit-sharing funds (X2), open unemployment rate (X3), labor force participation rate (X4), and the number of industries (X5). It will be analyzed using spatial regression. There are several spatial regressions such as Spatial Autoregressive (SAR) and Spatial Error Model (SEM), Spatial Durbin Model (SDM) and Spatial Durbin Error Model (SDEM). The SDM and SDEM are special cases of SAR and SEM. SDM involves spatial effects on independent and dependent variables, while SDEM involves spatial effects on dependent variable and error. So, we will analyzed using SDM and SDEM. From the results, SDEM is the best method used for the data, and all variables used are significant. The predicted GRDP values of districts/cities in East Java are classified into five classes. There are eight regencies/cities included in the class with declining GRDP due to the COVID-19 pandemic, namely Ngawi Regency, Bangkalan Regency, Pamekasan Regency, Blitar City, Probolinggo City, Pasuruan City, Mojokerto City, and Batu City.

This study aims to analyze the effect of the Provincial Minimum Wage (UMP), Gross Regional Domestic Product (GRDP), and the Information and Communication Technology Development Index (ICT-Dev Index) on the Human Development Index (HDI) in Eastern Indonesia. This research employs a quantitative approach with panel data regression analysis. The study uses secondary panel data from 13 provinces in Eastern Indonesia for the period 2019–2023, obtained from Statistics Indonesia (BPS) and the Ministry of Manpower of the Republic of Indonesia. The results show that the UMP has a positive and significant effect on HDI, GRDP has a negative and insignificant effect on HDI, while the ICT-Dev Index has a positive and significant impact on HDI. Simultaneously, UMP, GRDP, and the ICT-Dev Index have a positive and significant effect on HDI. The coefficient of determination indicates that 99.01% of the variation in HDI can be explained by UMP, GRDP, and the ICT-Dev Index, while the remaining 0.99% is influenced by other factors not examined in this study.

Tourism plays an important role in regional economic development by contributing to the Gross Regional Domestic Product (GRDP), creating employment opportunities, and improving community welfare. The concept of sustainable tourism emphasizes a balance between economic, socio-cultural, and environmental dimensions so that the benefits of tourism can be sustained in the long term. Banyuwangi Regency, known by its branding “The Sunrise of Java,” is one of Indonesia’s leading destinations that has undergone economic transformation through the development of nature-based, cultural, and ecotourism attractions. This study aims to examine the economic dimension of sustainable tourism by measuring the contribution of the tourism sector to the GRDP of Banyuwangi Regency. The research employs a simple linear regression analysis, with the number of tourist visits as the independent variable and the GRDP value of Banyuwangi Regency as the dependent variable. The data used covers the last five years, representing the dynamic relationship between tourist growth and regional economic performance. The data were obtained from the official publications of Statistics Indonesia (BPS) of Banyuwangi Regency and analyzed using a simple linear regression model. The results show that the number of tourists has a positive and significant effect on GRDP, with a coefficient of determination (R²) of 92.6%, indicating that most of the variation in GRDP can be explained by the growth in tourist arrivals. The findings of this study are expected to contribute to a better understanding of the relationship between tourism and regional economic development, both in Banyuwangi and other regions in Indonesia.