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Spatio Temporal Modeling (Prof. Dr. Budi Nurani R, M.S/Dr. Suhartono) [BNR-Su]

Abstract: In this course, we discuss an introduction of spatio temporal modeling based on time series phenomena. How to build the spatio temporal model using Box-Jenkins approach and to develop the Generalized Space time Autoregressive (GSTAR) models to be GSTARI, GSTAR-X, GSTAR-Kriging models based on real phenomena of data. How to estimate the parameter’s model and to apply the model for forecasting in the future time including the influence of surrounding locations. Description of the Appendices.

Data Mining (Dr. Atje Setiawan Abdullah, MS, M.Kom.) [ASA]

Abstract: in this course, we introduce the KDD method for mining big data/large data in three steps of data mining: pre-processing, data mining and post-processing. We propose some statistics tools for data mining for big data phenomena to get a knowledge for applying in real phenomena. Description of the Appendices.

Optimization Modeling (Dr. Diah Chaerani) [DC]

Abstract: In this course, we discuss how to solve optimization problem in term of Linear Optimization and Nonlinear Optimization. Specific application on Spatial Optimization Problem will be discussed. Description of the Appendices.

Spatial Econometrics (Prof. Dr. Henk Folmer/Dr. Setiawan) [HF-Se]

Abstract: In this course we propose the spatial phenomena, spatial heterogeneity, and  spatial dependence. We also discuss about the weight matrix , spatial correlation and spatial autoregressive models.

Econometrics and Operations Research (Prof. Dr. Anton Abdulbasah Kamil) [AAK]

Abstract: In this course, we will give a description of econometrics definition and introduction of operations research.

An Application of Spatio Temporal Data Mining and Optimization Modeling for Climate Change (Prof. Dr. Eddy Hermawan) [EH]

Abstract: In this discussion, we will give a description of climate change phenomena and how we get a big data of rainfall or temperature  from satellite data, also how to predict the climate parameters using spatio temporal data mining modeling