### Reducing Bitrate and Increasing the Quality of Inter Frame by Avoiding Quantization Errors in Stationary Blocks

- Research Article in EAI Endorsed Transactions on Industrial Networks and Intelligent Systems: Online First
- Authors:
- Xuan-Tu Tran, Ngoc-Sinh Nguyen, Duy-Hieu Bui, Minh-Trien Pham, Hung K. Nguyen, Cong-Kha Pham
- Abstract:
In image compression and video coding, quantization error helps to reduce the amount of information of the high frequency components. However, in temporal prediction the quantization error contributes its value as noise in the total residual information. Therefore, the residual signal of the inte…

more »In image compression and video coding, quantization error helps to reduce the amount of information of the high frequency components. However, in temporal prediction the quantization error contributes its value as noise in the total residual information. Therefore, the residual signal of the inter-picture prediction is greater than the expected one and always differs zero value even input video contains only homogeneous frames. In this paper, we reveal negative effects of quantization errors in inter prediction and propose a video encoding scheme which is able to avoid side effects of quantization errors in the stationary parts. We propose to implement a motion detection algorithm as the first stage of video encoding to separate the video into two parts: motion and static. The motion information allows us to force residual data of non-changed part to zero and keep the residual signal of motion regularly. Beside, we design block-based filters which improve motion results and filter those results fit into block encode size well. Fixed residual data of static information permits us to pre-calculate its quantized coefficient and create a bypass encoding path for it. Experimental results with the JPEG compression (MJPEG-DPCM) showed that the proposed method produces lower bitrate than the conventional MJPEG-DPCM at the same quantization parameter and a lower computational complexity.

### Histogram-based Feature Extraction for GPS Trajectory Clustering

- Research Article in EAI Endorsed Transactions on Industrial Networks and Intelligent Systems: Online First
- Authors:
- Chi Nguyen, Thao Dinh, Van-Hau Nguyen, Nhat Phuong Tran, Anh Le
- Abstract:
Clustering trajectories from GPS data is a crucial task for developing applications in intelligent transportation systems. Most existing approaches perform clustering on raw data consisting of series of GPS positions of moving objects over time. Such approaches are not suitable for classifying mo…

more »Clustering trajectories from GPS data is a crucial task for developing applications in intelligent transportation systems. Most existing approaches perform clustering on raw data consisting of series of GPS positions of moving objects over time. Such approaches are not suitable for classifying moving behaviours of vehicles, e.g., how to distinguish between a trajectory of a taxi and a trajectory of a private car. In this paper, we focus on the problem of clustering trajectories of vehicles having the same moving behaviours. Our approach is based on histogram-based feature extraction to model moving behaviours of objects and utilizes traditional clustering algorithms to group trajectories. We perform experiments on real datasets and obtain better results than existing approaches.

### A New Mixture Distribution for Extreme Excess Zeros: Negative Binomial-Generalized Exponential (NB-GE) Distribution

- Research Article in Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia
- Authors:
- Junifsa Afly Prameswari, Ida Fithriani, Siti Nurrohmah
- Abstract:
Negative Binomial-Generalized Exponential (NB-GE) distribution is a distribution that capable for modeling overdispersion data with extreme excess zeros, which is more than 80% zeros in a data. The distribution is a mixture distribution that obtained by mixing the Negative Binomial (NB) distributio…

more »Negative Binomial-Generalized Exponential (NB-GE) distribution is a distribution that capable for modeling overdispersion data with extreme excess zeros, which is more than 80% zeros in a data. The distribution is a mixture distribution that obtained by mixing the Negative Binomial (NB) distribution with the Generalized Exponential (GE) distribution. The formation of the Negative Binomial-Generalized Exponential (NB-GE) distribution and the characteristics of the Negative Binomial-Generalized Exponential (NB-GE) distribution such as the probability density function, kth moment, mean, variance, skewness and kurtosis are discussed in this paper. Estimation of the parameters from the Negative Binomial-Generalized Exponential (NB-GE) distribution using the maximum likelihood method. As an illustration, Negative Binomial-Generalized Exponential (NB-GE) distribution used to model the data of fatal crash that has more than 80% zeros.

### Determination of General Circulation Model Domain Using LASSO to Improve Rainfall Prediction Accuracy in West Java

- Research Article in Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia
- Authors:
- Nanda Fadhli, Aji Hamim Wigena, Anik Djuraidah
- Abstract:
The Statistical downscaling technique has often been used to predict rainfall. This technique needsa domain of general circulation model (GCM) data. The selection of GCM domain is an important factor to improvepredictionaccuracy.The goal of this study is to determine the optimum domain. This study …

more »The Statistical downscaling technique has often been used to predict rainfall. This technique needsa domain of general circulation model (GCM) data. The selection of GCM domain is an important factor to improvepredictionaccuracy.The goal of this study is to determine the optimum domain. This study uses GCM data from CFSRv2 with gridresolution "2.5°×2.5°" and local rainfall data in West Java. The GCM domain is determined basedon minimum correlation value of 0.3 between GCM data and local rainfall data. Correlations are calculated for the grid in the four directions of the compass with one grid as the reference that straightly above the local rainfall station. The domains are evaluated using the regression model with L1 (LASSO) regularization. The result showed that the optimum domain was 8×5 grids.

### Unordered Features Selection of Low Birth WeightDatain Indonesiausing the LASSO and Fused LASSO Techniques

- Research Article in Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia
- Authors:
- Yenni Kurniawati, Khairil Anwar Notodiputro, Bagus Sartono
- Abstract:
This paper aims to analyze the Low Birth Weight (LBW) data of infants in Indonesia by using the LASSO and Fused LASSO techniques. Fused LASSO is usually used to select parameters for ordered features. In this case, the features are unordered. Therefore, this research adopts three techniques in orde…

more »This paper aims to analyze the Low Birth Weight (LBW) data of infants in Indonesia by using the LASSO and Fused LASSO techniques. Fused LASSO is usually used to select parameters for ordered features. In this case, the features are unordered. Therefore, this research adopts three techniques in ordering features. Furthermore, all these Fused LASSO techniques and LASSO are compared. This paper utilizes data on 1,176 LBW infants collected from the 2017 Indonesian Demographic and Health Survey (IDHS). The results showed that LASSO has the sparsest solutionbased on the 5-fold cross-validation. Thefeatures that contribute to LBW are mothers' occupation, mothers' age, antenatal care, multiple birth, and birth order. However, Fused LASSO 1 has the lowest AIC and BIC valuecompared to other ordering techniques.Ordering features using the correlation between the features and the outcomes is recommended as an alternative technique to sort unordered features.

### Quasi Poisson Model for Estimating Under-Five Mortality Rate in Small Area

- Authors:
- Nofita Istiana, Anang Kurnia, Azka Ubaidillah
- Abstract:
Under-Five Mortality Rate (U5MR) is an important indicator because it reflects the socio-economic conditions and developments in health sector. U5MR is obtained from Demographic and Health Survey (DHS) where the level of estimation is designed for national and provincial level. The decentralization…

more »Under-Five Mortality Rate (U5MR) is an important indicator because it reflects the socio-economic conditions and developments in health sector. U5MR is obtained from Demographic and Health Survey (DHS) where the level of estimation is designed for national and provincial level. The decentralization system makes the importance of U5MR for sub-domain of province such as district/municipality level. Small area estimation (SAE) can be used for estimating U5MR in district/municipality level by using a mixed model. The model that is often used is generalized linear mixed model (GLMM). Direct estimation of U5MR produces a large proportion of zero values (excess zero), so the Poisson model is not suitable for modeling the data. Excess zero is the reason for violating the equidispersion in Poisson model. In this study, quasi Poisson modelproduces better predictions than direct estimation. In addition, the U5MR estimation for municipality makes it possible to produce U5MR maps in municipality level.

### Hybrid Model of Seasonal ARIMA-ANN to Forecast Tourist Arrivals through Minangkabau International Airport

- Authors:
- Mutia Yollanda, Dodi Devianto
- Abstract:
The number of tourist arrivals forecasting is required for the future development of tourism industry to improve the economic growth. The number tourist arrivals data can be analyzed by building a model so that it will help to find out the number of tourist arrivals in the next period which is thro…

more »The number of tourist arrivals forecasting is required for the future development of tourism industry to improve the economic growth. The number tourist arrivals data can be analyzed by building a model so that it will help to find out the number of tourist arrivals in the next period which is through Minangkabau International Airport. The linear model that is used is Seasonal Autoregressive Integrated Moving Average (SARIMA) used and continued to build a nonlinear model of the residual SARIMA model using Artificial Neural Network (ANN). In this research, SARIMA model which obtained is SARIMA (1, 0, 1) (1, 1, 0)12. But, residual of SARIMA model has not been fulfilled an autocorrelation assumption so that it isproposed a new model of SARIMA-ANN. The residual model of SARIMA is built using the ANN model architecture with 2–2–2–1 network topology. The performance rate of time series model of tourist arrivals which is the data started on January 2012 until March 2019 is measured using Mean Absolute Percentage Error (MAPE). Based on the MAPE value of 17.1770% indicates that the model obtained having good performance to forecast the number of tourist arrivals through Minangkabau International Airport in the future.

### Hidden Markov Model for Exchange Rate with EWMA Control Chart

- Authors:
- Rahmawati Ramadhan, Dodi Devianto, Maiyastri Maiyastri
- Abstract:
Nowadays, the US dollar exchange rate is still very influential on the exchange rate stability of many countries, including Indonesia. The effect of the US Dollar exchange rate has caused the fluctuation of Rupiah exchange rate. That is one of the cases that can be modeled with the Hidden Markov Mo…

more »Nowadays, the US dollar exchange rate is still very influential on the exchange rate stability of many countries, including Indonesia. The effect of the US Dollar exchange rate has caused the fluctuation of Rupiah exchange rate. That is one of the cases that can be modeled with the Hidden Markov Model (HMM) as the development of a Markov chain in which its state is not able to be observed directly (hidden), but it is only able to be observed through a set of other observations. In this paper, Exponentially Weighted Moving Average (EWMA) control chart will be used to determine the state of HMM. Based on the EWMA control chart, there are three states which are increase, decrease, and constant. The probability of the changes of exchange rate will be predicted in 2019 with the Baum Welch Algorithm on HMM. By using 240 exchange rate data of US Dollar to Rupiah in 2018, it is predicted the changes of exchange rate in 2019 are increased with a probability of 0.57. The results of HMM have connected to the EWMA control chart where they have eight uncontrolled data with two states increase and six states decrease. Thus, the existence of uncontrolled data implies the probability of increasing of the exchange rate in 2019.

### Hierarchical Generalized Linear Mixed Models for Multilevel Analysis of Indonesian Student’s PISA Mathematics Literacy Achievement

- Authors:
- Tonah Tonah, Anang Kurnia, Kusman Sadik
- Abstract:
Generally, learning assessment and evaluation data in educational has a hierarchical structures one of which is PISA data. Multilevel models are methods that can be used to analyse hierarchical data structures and can be considered as HGLM models. This study has two objectives namely, examine the …

more »Generally, learning assessment and evaluation data in educational has a hierarchical structures one of which is PISA data. Multilevel models are methods that can be used to analyse hierarchical data structures and can be considered as HGLM models. This study has two objectives namely, examine the distribution of variable mathematical literacy and selecting the best HGLM model to determine student and school level variables that significantly influence students' mathematical literacy achievement. The result we have obtained are mathematical literacy achievement has lognormal distribution and M7 model is the best model.

### The Use Of MEWMA Control Chart In Controlling Major Component Of Cement Product

- Authors:
- Surya Puspita Sari, Dodi Devianto
- Abstract:
Cement is one of the industrial products that has a quality control process. Major component that consists of SiO2, Al2O3, Fe2O3, CaO, MgO and SO3 as basic component in cement product. This research explains about quality control of major component of cement by using MEWMAcontrol chart. The way to …

more »Cement is one of the industrial products that has a quality control process. Major component that consists of SiO2, Al2O3, Fe2O3, CaO, MgO and SO3 as basic component in cement product. This research explains about quality control of major component of cement by using MEWMAcontrol chart. The way to measure the performance of the control chart is used ARL as the average run observation to find the first out of control data. ParameterARL0 is the average run observation of in control data. In this research, it is assumed the data was in control. The optimization of ARL0 by weighted parameter of MEWMA control chart for λ=1, that is equal to Hotteling T2 chart. Optimal value of the weight parameter is determined by using the bisection method for then the variables did not show the outlier data. Finally, this research shows that cement production process is in control.