The formulation of Indonesian school operational assistance is a complex issue, as each region has different characteristics. The aim of this research was to find out the mapping of the distribution of school operational assistance budget in Central Java Province, to develop the equalization model of Indonesian school operational assistance of Central Java Province using spatial through three spatial processes namely spatial lag X (SLX), spatial autoregressive (SAR), and spatial error model (SEM). Spatial modeling is expected to be a tool of educational development planning so that the development is more directed to equitable distribution of Indonesian school operational assistance in Central Java. The distribution of funds for the program is one form of government expenditures in the form of subsidies for the education sector as the compensation from reduced subsidies for fuel oil. The research results show that the SEM model is the best model, and the estimation results show that the school development budget, school management and human development index can significantly be a determinant of the distribution of Indonesian school operational assistance.
One of the indicators of the success of social welfare development in Central Java was decreasing the population of people with social welfare problems (PMKS). One exertion that can be done was grouping or clustering the areas in Central Java-based on 26 indicators of PMKS. Fuzzy Geographically Weighted Clustering (FGWC) algorithm is a clustering analysis that observing the effect of the area. However, FGWC has a limitation in the initialization centroid phase that makes it trapped to local optimal. The limitation can be addressed with the Gravitational Search Algorithm (GSA) approach. The purpose of GSA was to optimize the value objective function. This research applied FGWC-GSA on PMKS in Central Java Province contained 26 indicators. Some validity indexes were applied to determine the best cluster. This research clustering the areas of Central Java into two clusters. The first cluster contained 24 districts and cities, and the second cluster contained 11 districts
The Human Development Index (IPM) is a tool to measure development performance, especially human development carried out in a certain area at a certain time or specifically. This study examines HDI and the components of HDI, the data used is data on the values of HDI components for 35 districts/cities in Central Java Province. The variables used in this study were HDI (Y) as the dependent variable, AHH (X1), AMH (X2) and PPP (X3) as independent variables. The research examines the effect of spatial dependencies by using the area approach. Next is given the SEM application to identify how much influence the HDI constituent components can have on the HDI level in Central Java. The results of the study show that the distribution of HDI in Central Java Province has a regional grouping pattern. The results of modeling using SEM show lambda and all significant variables. The SEM model produces an AIC of 43.8540 which is better than the regression OLS method with an AIC of 45.6231.
The issue of the allocation and distribution of the School Operational Aid (BOS) in Central Java Province is a complex problem since each region has different characteristics. The distribution formulation requires a spatial model as the neighbouring regions have dependencies. The variables in this research were BOS value, supervision/building cost, management cost, Human Development Index (HDI) analysed using the Spatial Lag of X (SLX) model with the weighting of Rock Contiguity. It is concluded that all variables have a spatial dependency with the BOS variable influenced by the variables of building and management costs significantly.
HIV / AIDS is a contagious disease that can attack all age groups of the population and is a health challenge in almost all over the world including Indonesia. Therefore, it is necessary to model HIV / AIDS cases for the factors that are suspected to influence them. One suitable method for estimating factors that influence HIV / AIDS is the Generalized Additive Model for Location, Scale, and Shape (GAMLSS). The GAMLSS method is flexible because it includes expansion of a good exponential family distribution to handle overdispersion data, continuous data, and discrete data. This research will apply GAMLSS semiparametric modeling with LOESS smoothing to find out the characteristics and models of HIV / AIDS cases in East Java in 2017. Based on the analysis, it was found that the variables that significantly affected were the number of homeless people, number of victims of drug abuse, population poor, and the number of fertile age couples using condom contraception with AIC value of 437,404, degree = 1 and span = 0.3, and the distribution used is Negative Binomial I.
Human Development Index (HDI) is measuring achievements of human development based on basic components of quality of life. Human development index is low score if HDI is less than 60, moderate HDI between 60 to less than 70, high HDI between 70 to less than 80, and equal to 80 and more than 80 belong to high HDI. Smooth Support Vector Machine (SSVM) is a classification technique that is new. The algorithm used is Newton Armijo with linear kernel, polynomial kernel, and Radial Basis Function (RBF) kernel. The result of classification of human development index with SSVM method with linear kernel shows the prediction accuracy 84.77%, polynomial kernel 61.65%, and RBF kernel 100%. Radial Base Function Kernel (RBF) is the most accurate kernel in predicting human development index.
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