Spatial Analysis of Child Violence in West Java Using a Geographically Weighted Negative Binomial Regression Approach

The number of leper in West Java is an example of the count data case. The analyzes commonly used in count data is Poisson regression. This research will determine the variables that influence the number of leper in West Java. The data used is the number of leper in West Java in 2019. This data has an overdispersion condition and spatial heterogenity. To handle overdispersion, the negative binomial regression model can be employed. While spatial heterogenity is overcome by adding adaptive bisquare kernel weight. This research resulted Geographically Weighted Negative Binomial Regression (GWNBR) with a weighting adaptive bisquare kernel classifies regency/city in West Java into ten groups based on the variables that sigfinicantly influence the number of leper. In general, the variable in the percentage of households with Clean and Healthy Behavior (PHBS) has a significant effect in all regency/city in West Java. Especially for Bogor Regency, Depok City, Bogor City, and Pangandaran Regency, the variable of the percentage of people poverty does not have a significant effect on the number leper.

The realization of "Indonesia Emas 2045" is significantly determined by the current Golden Generation. It is expected that this generation possesses high competence, quality, and innovation. As the most populous province in Indonesia, West Java plays a crucial role in achieving the vision of "Indonesia Emas 2045," particularly in the Human Development pillar through the enhancement of health standards. However, infectious diseases have become a major barrier to realizing this vision, with tuberculosis (TB) being one of the most prevalent. In 2023, there were 204,934 reported TB cases in West Java. Therefore, this study aims to identify the factors influencing the number of TB cases in West Java. The data type for TB cases is count data, thus the approach used in this study is Poisson regression, with Negative Binomial regression as an alternative to address overdispersion. The results indicate that the number of community health centers (X1), the percentage of standard-compliant drinking water facilities (X2), and the Air Quality Index (X4) have a significant impact on the number of TB cases in West Java. This is demonstrated by the p-value of each variable, where variables X1, X2, and X4 all have a p-value of 0.0, except for the percentage of households with adequate sanitation (X3), which has a p-value of 0.063 in the Negative Binomial regression. Based on these factors, it is hoped that the government can optimize related programs and facilities to reduce the number of TB cases in West Java and contribute to realizing one of the pillars of "Indonesia Emas 2045."

Indonesia is focusing on preparing for Indonesia’s Golden 2045 through the Golden Generation. The Golden Generation is expected to be the country's quality and superior human resource. The province of West Java, with the largest population in Indonesia, plays an important role in realizing Indonesia's Golden 2045 ambition. However, the high HIV/AIDS incidence in West Java is a major challenge that could potentially hinder Indonesia’s achievement of the 2045 Gold Plan. The Ministry of Health has launched the Three Zero HIV/AIDS concept to meet one of Indonesia's Golden 2045 pillars. Based on this, the study aims to identify factors that influence the number of HIV/AIDS cases in West Java. The HIV/AIDS case is a data count, so the approach used in this study is Poisson Regression. The results of the study showed that the number of cases of violence (X1), the percentage of use of condom contraceptives among members of the Family Planning (KB) program (X2), population density (X3), the proportion of poor population (X4), and number of health facilities per 100,000 inhabitants (X5) were related to cases of HIV/AIDS in the West Java Province. It is seen from the p-value of each variable X is 0.0 except the population density is worth 0.003. Having identified significant factors influencing cases of HIV/AIDS in West Java, the government is expected to enhance cooperation with relevant agencies in reducing the risk of the number of cases in Western Java. Thus, Three Zero in West Java can be achieved by 2030.

Dengue Hemorrhagic Fever (DHF) is an infectious disease that remains a serious public health problem in Indonesia, particularly in West Java Province. This study aims to model the number of DHF cases using Gaussian, Poisson, and Compound Poisson Tweedie regression methods based on 2024 data sourced from the West Java Central Statistics Agency (BPS) and the West Java Provincial Health Office. The predictor variables used include humidity, rainfall, real per capita expenditure, poverty ratio, population density, percentage of households with clean and healthy lifestyles, health facility ratio, and average altitude above sea level. The analysis results show that Gaussian and Poisson regressions are less suitable because they cannot handle overdispersion in the data. The Compound Poisson Tweedie model provides the best performance with the smallest Akaike Information Criterion (AIC) value. Two variables that significantly influence the number of DHF cases are population density and the ratio of health facilities. The model equation can be expressed as follows: the expected number of DHF cases equals the exponential of (18.380 plus 0.00008 times population density minus 0.285 times health facility ratio).

Coronavirus Disease 2019 (COVID-19) spread quickly and reached epidemic levels worldwide. West Java is Indonesia's most populous province and has a high susceptibility to the transmission of the disease, resulting in a significant number of COVID-19 cases. Therefore, this research aimed to determine the influencing factors as well as the spatial and temporal distribution of COVID-19 in West Java. Data on COVID-19 cases in West Java obtained from PIKOBAR were used. Spatial distribution was described using a choropleth, while the influencing factors were evaluated with regression analysis. To determine whether COVID-19s policies and events affected its temporal distribution, the cases detected were graphed daily or biweekly with information on those two variables. Furthermore, the cumulative incidence was described in the linear regression analysis model as being significantly influenced by vaccinations and greatly elevated by population density. The biweekly chart had a random pattern with sharp decreases or spikes in cumulative incidence changes. Spatial and temporal analysis helps greatly in understanding distribution patterns and their influencing factors, specifically at the beginning of the pandemic. Plans and strategies for control and assessment programs may be supported by this study material.

We discuss the problem of estimating the number of nests of different species of seabirds on North East Herald Cay based on the data from a 1996 survey of quadrats along transects and data from similar past surveys. We consider three approaches based on different plausible models, namely a conditional negative binomial model that allows for additional zeroes in the data, a weighting approach (based on a heteroscedastic regression model), and a transform-both-sides regression approach. We find that the conditional negative binomial approach and a linear regression approach work well but that the transform-both-sides approach should not be used. We apply the conditional negative binomial and linear regression approaches with poststratification based on data quality and availability to estimate the number of frigatebird nests on North East Herald Cay.

Purpose: This study assesses the spatial autocorrelation of tuberculosis (TB) with population density, poverty, personal hygiene and environmental sani- tation (perilaku hidup bersih sehat, PHBS), and housing quality to identify critical areas for targeted TB management in West Java. Methods: This ecological study analyzes secondary data from all TB patients across 27 regencies/cities in West Java Province for 2022. Spatial patterns were examined using the Global Moran's Index and Local Indicators of Spatial Association (LISA). Results: The analysis revealed significant clustering of TB prevalence with population density (p-value = 0.001) and PHBS (p-value = 0.047). At the same time, dispersion was noted with poverty (p-value = 0.355) and a non-significant clustering with housing quality (p-value = 0.270). Notably, ten regencies/cities exhibited significant local spatial autocorrelat- ion, indicating priority areas for intervention. Conclusion: TB prevalence in West Java show a positive spatial correlation with population density and PHBS, indicating clustered patterns that necessitate focused policy attention. The absence of a spatial correlation between poverty and housing quality suggests different intervention strategies may be required. TB intervention should be prioritized in areas like Bekasi Regency, Bekasi City, Bogor Regency, Bogor City, Cianjur Regency, and Depok City, where TB prevalence is significantly associated with key spatial factors.

Dengue Hemorrhagic Fever (DHF) is an infectious disease that remains a serious public health problem in Indonesia, particularly in West Java Province. This study aims to model the number of DHF cases using Gaussian, Poisson, and Compound Poisson Tweedie regression methods based on 2024 data sourced from the West Java Central Statistics Agency (BPS) and the West Java Provincial Health Office. The predictor variables used include humidity, rainfall, real per capita expenditure, poverty ratio, population density, percentage of households with clean and healthy lifestyles, health facility ratio, and average altitude above sea level. The analysis results show that Gaussian and Poisson regressions are less suitable because they cannot handle overdispersion in the data. The Compound Poisson Tweedie model provides the best performance with the smallest Akaike Information Criterion (AIC) value. Two variables that significantly influence the number of DHF cases are population density and the ratio of health facilities. The model equation can be expressed as follows: the expected number of DHF cases equals the exponential of (18.380 plus 0.00008 times population density minus 0.285 times health facility ratio).


 The agricultural sector is strategic and the third-largest contributor to the GRDP of West Java Province, but its growth has slowed during the 2016–2019 period. The slow growth rate can be caused by the determinants of the growth of the agricultural sector itself and is very likely to be affected by the spatial interaction between regions in the province. Therefore, this study aims to analyze the spatial effect between regions on the growth of the agricultural sector in West Java and identify the factors that influence the growth of the agricultural sector within the province by using spatial analysis of panel data. The results reveal that the appropriate model is a fixed effect spatial error model, which shows an effect of spatial interaction between regions on the growth of the agricultural sector in West Java Province. The factors that affect the growth of the agricultural sector are agricultural credit, agricultural road infrastructure, and diversification of economic activities.
 
 Keywords: agricultural sector growth, spatial autoregressive, spatial error model, spatial panel data

Abstract. This study aims to model the risk factors for maternal mortality in Southeast Sulawesi Province in 2022 using a negative binomial regression approach. This analysis is used to overcome the overdispersion problem in count data. The data used is secondary data obtained from the Southeast Sulawesi Provincial Health Service. The variables studied included the number of health centers, the percentage of births in health service facilities, the percentage of pregnant women who implemented the K4 program, the percentage of pregnant women who implemented the K1 program, and the number of midwives. The research results showed that the variables percentage of births in health service facilities, percentage of pregnant women implementing the K4 program, and number of midwives significantly affected maternal mortality. The negative binomial regression model illustrates that increasing the percentage of births in health service facilities and implementing the K4 program can reduce maternal mortality. On the other hand, increasing the number of midwives did not have a significant effect on reducing maternal mortality.

Distribution of elementary schools in Depok, West Java, is not only located in settlement area. This situation influences the pattern of children’s independent mobility, which is one of the aspects in Depok’s Children Friendly City program. This research aimed to discover the spatial behaviour pattern of children’s independent mobility in Depok. Sample in this research consists of 7 elementary schools and the data was gathered by 4th graders’ questionnaire filling, narration writing, and mental map drawing. Furthermore, the data was analyzed using spatial analysis method. The result showed that there is correlation between human activities around the school and children’s chosen transportation mode. Moreover, trip distance also affects the type of transportation mode. The further children’s trip distance, the more limited transportation mode they can use. From the analysis result, it is concluded that school location influences the spatial pattern of children independent movement. The fact that schools are placed in high-crowd area shows that Depok hasn’t taken side yet with children’s independence in doing trip to school as the aspect of Children Friendly City program.

Background: The development of bullion business and its increasing digitalization are widely promoted as instruments for financial inclusion and regional welfare enhancement, yet empirical evidence on their actual welfare effects remains limited and spatially heterogeneous. This study aims to examine whether bullion business development, particularly through digital access, contributes to regional welfare in West Java and to identify the conditions under which such development strengthens resilience without generating new systemic risks. Building on theories of asset-based welfare, financial resilience, and digital finance adoption. Methods: The research employs a mixed quantitative approach combining macro-financial indicators, provincial and municipal welfare data, and household-level survey evidence. The analysis utilizes monthly national gold price data, inflation, interest rates, exchange rates, provincial economic indicators, and a structured survey of respondents representing all 27 regencies and municipalities in West Java, complemented by spatial clustering and scenario-based stress testing. Findings: The findings indicate that gold ownership functions primarily as a risk-mitigation asset rather than a growth driver, with welfare effects becoming more pronounced during inflationary and income-shock periods. Physical gold holders demonstrate higher crisis utilization rates than digital users, reflecting stronger behavioral resilience despite lower liquidity. Digital bullion access improves transaction efficiency and inclusion in regions with high digital readiness but amplifies volatility transmission and welfare reversals under stress scenarios, particularly in urbanized areas. Spatial analysis reveals uneven welfare outcomes, where digitally advanced municipalities benefit during price appreciation phases yet face sharper contractions during crises, while low digital readiness regions display greater stability through reliance on physical bullion. Conclusion: The study concludes that bullion digitalization contributes to regional welfare only under conditional designs incorporating hybrid access, spatial differentiation, and crisis-mode governance. Novelty/Originality of this article: The originality of this article lies in empirically positioning bullion access as a spatial welfare variable and demonstrating that digital efficiency does not automatically translate into systemic resilience.

The emergence and spread of COVID-19 prompted several studies focusing on spatial analysis in this disease's visualization, investigation, and modeling. This study aims to determine the geographical distribution and grouping of COVID-19 cases and identify hotspots. Reports from the COVID-19 task force are used to collect monthly data on reported cases. Moran's I and Anselian local Moran's I global spatial autocorrelation approaches investigated regional groupings. Getis-ord G* was used to examine changes in hotspots and coldspots, followed by mapping using ArcGIS. The hotspots with a 99% confidence level are DKI Jakarta, West Java, Central Java, East Java, Yogyakarta, and Bali. The coldpots with a 90% confidence level are North Maluku and West Papua.

The purpose of research were (1) a conceptual, functional model designed and implementation for spatial airports, (2) a causal, flow diagrams and mathematical equations made for airport activity, (3) obtained information on the conditions of space and activities at airports assessment, (4) the space and activities evaluation at airports based on national and international airport services standards, (5) options provided to improve the spatial and airport activities performance become the international standards airport. Descriptive method is used for the research. Husein Sastranegara Airport in Bandung, West Java, Indonesia was study location. The research was conducted on September 2015 to April 2016. A spatial analysis is used to obtain runway, taxiway and building airport geometric information. A system analysis is used to obtain the relationship between components in airports, dynamic simulation activity at airports and information on the results tables and graphs of dynamic model. Airport national and international standard could not be fulfilled by spatial and activity existing condition of Husein Sastranegara. Idea of re-location program is proposed as problem solving for constructing new airport which could be serving international air transportation.

There is a paucity of studies investigating the spatial pattern and factors associated with the prevalence of tuberculosis (TB) in Java. This study aimed to identify spatial autocorrelation, clusters, and factors associated with TB prevalence in Java using district- or city-level data. This was an ecological study using data from 118 districts or cities across six provinces in Java. Spatial analyses (i.e., Global Moran’s I, Local Indicator Spatial Autocorrelation [LISA], and Geographically Weighted Regression [GWR]) were used. This study found positive spatial autocorrelation of TB prevalence in Java (Global Moran’s I = .45, p = .001). Statistically significant high-high clusters (p < .05) were identified in some districts within the capital city of Jakarta, Banten, and West Java provinces. The GWR model with the Bi-square Kernel weighting function was selected as the best model to predict the prevalence of TB (R2 = 37.50%, AIC = -59.94%). Findings from the GWR model indicate that the average number of years in education, the percentages of households with floor space per capita < 8 m2 and reporting easy access to health care facilities were associated with the prevalence of TB in some districts within West and Central Java provinces. Therefore, considering district differences in factors associated with TB prevalence, locally-focused interventions are worth considering.