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[CT083]

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Industrial Contributed Talk
Abstract : COVID-19 continuing challenges to health and socio-economic crisis. Geopolitical and demographic may possible affecting COVID-19 spread and this research focus on COVID-19 spread level classification. The method used is Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA), OPLS-DA projects predictor that have the best correlation with responses so that they can separate predictor variables from variables that are not correlated. OPLS-DA effectively identifies sources of variability between classes to produce good classification results with an accuracy rate 84.44%. The results also explain how predictor variables can affect the level of spread of COVID-19.
Classification : 62H30, 68U01, Classification and Discriminant Analysis for Outlier and High-dimensional data
Author(s) :
- Noviana Pratiwi (Gadjah Mada University)
- Dedi Rosadi (Gadjah Mada University)
- Abdurakhman Abdurakhman (Gadjah Mada University)

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Contributed Talk
Abstract : In this work, we propose an unsupervised methodology for analyzing temporal sequences of satellite images. Images decompose into disjoint tiles, and we embed sequences of tiles into multidimensional time series. The proposed embedding captures valuable information about the terrain and its evolution. It allows the partitioning of the ground into different types of terrain and understanding of the relationship between them. The proposed methodology shows promising results when analyzing a region of Navarre, Spain.
Classification : 62H35
Author(s) :
- Aritz Pérez (Basque Center for Applied Mathematics)
- Carlos Echegoyen (Public University of Navarre)
- Guzmán Santafé (Public University of Navarre)
- Unai Pérez (Public University of Navarre)
- María Dolores Ugarte (Public University of Navarre)

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Contributed Talk
Abstract : Yield curve in bond investment will provide visualization of yields of bond as the function of the time to maturities. In this study, we analyze Indonesian Government Yield Curve (IGYSC) during the pandemic Covid-19. We apply the Nelson Siegel (NS) class model and compare the performance of the optimization method of based on numerical optimization and based on heuristic optimization. All the computation are done using R software.
Classification : 62J02, 62P05, 65K05, 68W50, 90C20
Author(s) :
- Dedi Rosadi (Universitas Gadjah Mada)
- Dinda Awanda Ramadhani (Universitas Gadjah Mada)
- Agus Sihabuddin (Universitas Gadjah Mada)

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Industrial Contributed Talk
Abstract : Within-Groups Generalized M-Estimators (WGM) is a method for determining robust estimators of outliers for panel data models. This study will conduct a simulation to compare WGM in one-way unbalanced panel data model with fixed-effects approach using different multivariate locations and scale estimators, namely S-multivariate, Minimum Volume Ellipsoid (MVE), and Minimum Covariance Determinant (MCD). Then apply it to economic growth data in Kalimantan. Based on the simulation results and applications, it is known that the WGM with the S-multivariate estimator gives a better MSE value.
Classification : 62J99
Author(s) :
- Desi Yuniarti (Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada, Yogyakarta)
- Dedi Rosadi (Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada, Yogyakarta)
- Abdurakhman Abdurakhman (Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada, Yogyakarta)

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Contributed Talk
Abstract : Home factors, social and school environment factors are attributed to the causes of girl child school-dropout in Ghana. Mitigating school dropout menace calls for a scientific approach in determining the most contributory factors. Sampling respondents from Junior High Schools and stakeholders in the Tano North District of the Brong Ahafo Region in Ghana, a multiple regression model was constructed to determine the most contributory factor of girl child school dropout in order to advise on government policies.
Classification : 62Jxx
Author(s) :
- Emmanuel Apraku Amankwah (University of Energy and Natural Resources)