Multicollinearity is a severe problem in multiple regression. High collinearity in some explanatory variables leads to the high standard error estimates. It becomes a problem for the hypothesis test on the slope of regression. The ridge regression is the most popular method used to minimize the standard error estimates. However, the hypothesis testing in regression model has been not solved yet. It does not provide the statistical hypothesis test. Therefore, the alternative method is needed. The method must be able to obtain the parameter estimates with a high level of precision and also facilitates the hypothesis test of regression parameters simultaneously. We proposed the Bayesian method with an informative prior as an alternative solution. The Monte Carlo simulation concludes the Bayesian method outperformed to ridge regression in term of Bias, Mean Square Error and power of the test. Based on the simulation result, the Bayesian method can be used to solve hypothesis testing in regression analysis with multicollinearity problem effectively.

Aplikasi pemodelan spasial ekonometrika dalam berbagai bidang ilmu semakin banyak khususnya dalam ruang lingkup spasial regional dan spasial epidemiologi. Metode ini berkembang karena kemampuan metode ini mengakomodasi adanya ketergantungan spasial dalam data. Analisis ekonometrik biasa tidak mampu memberikan hasil yang baik pada saat data tidak berdistribusi independen. Metode Maksimum likelihood adalah metode yang umumnya digunakan untuk menaksir parameter model spasial econometrics. Namun metode ini tidak cukup baik dalam mengestimasi parameter model pada saat unit spasialnya sangat banyak. Metode alternative Bayesian diperkenalkan untuk mengatasi masalah tersebut. Penelitian ini mengkaji pendekatan metode Bayesian pada model Spasial Autoregresive (SAR). Model SAR merupakan satu dari delapan model spasial ecokometrik yang paling banyak digunakan. Pendekatan Bayesian akan diaplikasikan pada pemodelan kasus TB Paru di Kota Bandung

Spatiotemporal analysis has been used widely to explain some geographic phenomenon, especially in an epidemiology study. Spatial and temporal autocorrelation coefficients are usually used to assess the spatial and temporal dependencies in set geographic events. However, those statistics are usually computed separately and may lead to the misleading conclusion. Analysing spatiotemporal autocorrelation would be useful to understand the geographical evolution simultaneously. Spatiotemporal autocorrelation can be used to identify the spatiotemporal clustering and outlier via local spatiotemporal autocorrelation. This paper develops a method to estimate and test the local spatiotemporal autocorrelation based on the local spatial Moran’s Index. Randomization permutation test is used to obtain the p-value which is used to construct the disease clustering. The method was applied to identify the spatiotemporal clustering and outlier detection for dengue disease data in Bandung city. Based on image analysis, this method presents the better result compare than the local spatial Moran’s Index which is done for every time separately.

Corresponding author: davila.rubianti06@gmail.com b) bertho@unpad.ac.id c) Resa.pontoh@gmail.com Abstract. Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.

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