KEMIRIPAN WILAYAH DALAM MENGHASILKAN PRODUKSI BEBERAPA KOMODITAS PANGAN STRATEGIS

Similarity of regions (provinces in Indonesia) in producing the strategic food production were analyzed based on seven serial data sets and each one consists of nine food commodities weighted by number of population. The food data sets were compiled from Food Security Agency, The Ministry of Agriculture, while the population data was collected from The Statistics Indonesia of the Republic of Indonesia. Main sources of variability on each data set were identified on loading values basis extracted using biplot (Gower and 1996). The similarity of the food production patterns to the overall data sets were evaluated using generalized Procrustes rotation (gPr). Results of this research showed there are two groups of production system pattern. In the first group, there are five commodities dominating the first two components, i.e., paddy, maize, soybean, peanut, and cassava−, while in the second group, there are six commodities dominating the first two components, i.e., paddy, maize, chicken eggs, beef, peanuts, and cassava. Hence, the gPr was applied in both groups separately. Applied the gPr to the first group showed there are seven commodities dominating the first two consensus axis −paddy, maize, soybean, peanut, cassava, chicken egg, and sweet potatoes. This means the chicken eggs and sweet potatoes are considered as common variances. Applied the gPr to the second group indicated that the commodities dominating the two consensus axis are same with ones dominating the first two components. But, if the third consensus axis is assumed important then soybean seem as common source of variability in the second group. Consequently, the similarities of the data sets in each group was established based upon identified sources of variability

A SIMULTANEOUS STUDY OF POVERTY RATE , CHILD LABOR AND DROPOUT RATE IN INDONESIA

Poverty is a major cause of child labor and dropout case. Poor families usually encourage their children to work looking for additional income as a way to survive. Based on previous research there is a causal relationship of poverty rate, number of child labor and dropout rate. Characteristics of poverty rate, child labor and dropout rate can be assessed from the demographic characteristics and socioeconomic characteristics are interrelated. This study aims to model the interdependent relationship of poverty rate, child labor and dropout rate in Indonesia and factors that influence them. One appropriate method is used to model the interdependent relationship of these three variables is the simultaneous equation models. From the results of the identification of the model equations were used the method Three Stage Least Square (3SLS) with 3 equations. The number of variables is 11 pieces consist of 3 endogenous variables and 8 predetermined variables. The result showed that child labor in Indonesia is influenced significantly by poverty rate, dropout rate, and percentage of household heads who worked in agriculture. Poverty rate in Indonesia is influenced significantly number of child labor, dropout rate, and percentage of household heads who worked in agriculture. While dropout rate is influenced significantly by number of child labor, percentage of household with members more than six, percentage of household heads who did not complete primary school and percentage of household head who completed basic education. R-square of system is about 66.28%, meaning that total diversity of poverty rate, number of child labor and dropout rate in Indonesia in 2013 which can be explained by the explanatory variables in the system about 66.28%. Keywords: 3 bhaSLS, simultaneous equation models, poverty, child labor, dropout

PRICE OF SUGAR MODELING AND FORECASTING BASED ON STIMA MODEL AND GSTIMA MODEL

STIMA (space-time integrated moving average) model is a special form of Vector IMA model that combines the interdependence of time and location that is known by space-time model. STIMA model requires the same parameter values for all locations, so Generalized-STIMA (GSTIMA) model is developed to overcome this problem. This paper compares the implementation of two models in forecasting the price of sugar in capital provinces in Sumatra Island, Indonesia. The first step is model building for each model. This step is similar to Box-Jenkins’s procedure. It is begun with the determination of temporal order by using AICC, while spatial order is restricted on order 1, the parameter estimation uses nonlinear least square method that are minimized by a Gauss-Newton algorithm, and then diagnostic checking of white noise errors. The normalization of cross-correlation between the locations at the appropriate time lag is used as space weight. The last, the implementation of forecast is evaluated by using the Root Mean Square Error (RMSE) where the error is defined as the differences between the actual value and the forecast value. The implementation of STIMA model is better compared with GSTIMA model in forecasting the price of sugar, although STIMA model produces the same parameters for each location. Key words: Space-time, STIMA, GSTIMA, Modeling, Forecasting

Model Perilaku Keselamatan Kerja Karyawan Pada Industri Berisiko Tinggi

. Workplace accident rate in Indonesia is still high and likely to increase each year. The most dominant factor which causes accidents to happen in high-risk industries is because of the low behaviour of the workers' safety work. The research was conducted on the employees of LPG Bulk Filling Station (SPBE) in Bogor Region. The aim of this research is conducted to develop a model of the worker's safety behavior on high-risk industries. Some of the factors that have an influence on the safety behavior, among others: safety leadership style, safety climate, job satisfaction, fatigue, and safety motivation. The population of this research is all employees of SPBE ini Bogor region. The samples were taken by using multy stage cluster random sampling technique with two stages. The first stage, SPBE separated by location, and the second, employees is separated by working environment; office and field. A total of 100 questionnaires were distributed, of which 92 were returned and 69 were analyzed. Respondent data were analyzed by SEM-PLS using smart PLS software. The resulting model showed that safety leadership by participating and delegating style has a positive effect on safety climate and workers' safety behaviour. Worker's safety motivation has a positive effect on workers' safety behaviour, and worker's safety motivation affected by the safety climate

Pemodelan Pengukuran Luas Panen Padi Nasional Menggunakan Generalized Autoregressive Conditional Heteroscedastic Model (GARCH)

This study was aimed to build a model for the estimation of national harvested area of rice by incorporating element of variant heterogeneity and the influence of asymmetry factors on time series data using five types of GARCH models, namely: symmetric GARCH, exponential asymmetric GARCH, quadratic asymmetric GARCH, Threshold GARCH, and non-linear asymmetric GARCH. Those models were compared and evaluated, and then the best model was used to predict the accuracy of the national rice harvested area. The results showed that two types of GARCH had significant coefficient, indicating the validity of the model. Those models were symmetric GARCH and quadratic GARCH models. Based on the value of mean absolute percentage error (MAPE) for the twelve month periods ahead, quadratic GARCH model was better than the symmetric GARCH model. Furthermore, based on the value of mean absolute deviation (MAD) and mean square error (MSE), quadratic GARCH model also seemed to be a better model than symmetric GARCH model. The best model can be used to predict the harvested area in the subsequent year

Rapid assessment of the cash transfer for the poor students program/ bantuan siswa miskin (BSM)

With the announcement of the fuel price increase in June, 2013, the Government adopted a new approachtoto assist low income families to maintain their welfare. The compensation scheme covered: (1) Direct Cash Assistance for the People Program (BLSM), consisting of Rp 150,000 in cash for four months for around 15.5 million financially disadvantaged and vulnerable households paid in two installments; (2) increased rice rations being allocated as part of the rice-for-the-poor program (RASKIN), consisting of 15 kg per household for a period of 3 months (June, July, September 2013); (3) increased the nominal value of the assistance and number of recipients of the Poor Students Assistance Program (BSM); (4) increased the nominal value of the assistance targeted for 2.4 million households who participate in the Family Hope Program (PKH) from an average of Rp 1.4 million per year to Rp 1.8 million per year. The Cash Transfer for the Poor Students Program (BSM) policy is based upon results of assessments and monitoring carried out in 2012 by TNP2K(Tim Nasional Percepatan Penanggulangan Kemiskinan (National Team for Acceleration of Poverty Reduction)) and the World Bank. The objectives of the new scheme include: development of an effective and efficient scholarship system to benefit the poor; right-sizing of the scholarship for each level of schooling; improving fund channeling and monitoring systems; institutional development and better definition of the roles and responsibilities of local government, schools and communities in the channeling, monitoring and evaluation of implementation of the BSM Program. A main feature of the new scheme is the integration of support for poor students with the targeting and access mechanism developed by TNP2K for cash transfers utilizing the Unified Data Base which contains the names and addresses of some 96 million persons from 60 million households (source is PPLS data) and BSM Cards (Kartu BSM) and Social Protection Cards (KPS). To support this program MoEC was intended to implement a communications strategy with the roll-out of funds to overcome the incomplete take-up rate. The new BSM policy which came into effect in July 2013 essentially doubled the amounts of previous years for this program (for example, for elementary the amount increased from Rp 360,000 to Rp. 450,000) and about doubled the number of beneficiaries -- initially for 8.7 million school-aged children, now for 16.6 million children. Two will be made per year, at beginning of a new semester. The first tranche under the new scheme was intended to be disbursed from July to September, beginning with the most accessible regions

Pendekatan Geographically Weighted Zero Inflated Poisson Regression (Gwzipr) dengan Pembobot Fixed Bisquare Kernel pada Kasus Difteri di Indonesia

The number of deaths due to diphtheria is counts data and there is a considerable presence of zeros (excess zeros). Besides, data on the spread of disease are generally geographically oriented or observed in each particular region, which is a type of spatial data. Geographically Weighted Zero Inflated Poisson Regression (GWZIPR), as the development of Geographically Weighted Regression (GWR) and Zero Inflated Poisson (ZIP) models will be used as a model in processing provincial diphtheria data in Indonesia in 2018, with the independent variable percentage of diphtheria cases (X1), percentage of vaccinated numbers (X2) and percentage of the population (X3) in each province in Indonesia. Estimating model parameters uses the method of maximum likelihood estimation. While the weighting function used is fixed bisquare kernel. Data is processed using software R packages lctools. The results were obtained if the model involved all three independent variables, the effect of the three independent variables on the number of deaths due to diphtheria was not significant. This is because there is a strong and significant relationship between independent variables, so that if the model does not involve a variable percentage of the population (population density), the percentage of vaccinated people affects the number of deaths caused by diphtheria significantly in an area. So that the provision of immunization vaccines can reduce the number of deaths caused by diphtheri