The uniform continuity of characteristic function from convoluted exponential distribution with stabilizer constant

Proceedings of the Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bog

2020

Self Cite

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.

Section: Artificial Neural Networkmentioning

confidence: 99%

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

Yollanda¹,

Proceedings of the Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bog

2020

Self Cite

“…In logistic regression, the response variables are not normally distributed, so characteristic function as Fourier-Stieltjes transform is used to explain its characterization because the characteristic function is available for every distribution. The properties of characteristic function for some special distributions have been explained in [11], [12], [13] and its canonical representation of characteristic functions of exponential distribution has been shown in [14]. The probability distribution of ordinal logistic regression response could be characterize by using characteristic function.…”

Section: Ordinal Logistic Regressionmentioning

confidence: 99%

Determining Factors That Affecting Financial Performance of Sharia Small Business Bank by Using Ordinal Logistic Regression with Bootstrap Estimation

Ridho¹,

Proceedings of the Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bog

2020

Self Cite

The aim of this study is to find out the financial performance's affecting factors of sharia small business bank in Indonesia. Financial performance is the response variable which grouped into three categories, they are bad, medium, and good. Predictor variables involved in this study consisted of 11 numerical data and 1 categorical data. The numerical data are financial capital, productive assets, credit, third party funds, income, capital adequacy ratio, return on assets, return on equity, financing deposit ratio, non performing financing, and operational efficiency. Whereas the categorical data is the location of sharia small business bank (1 if it is in rural areas, 2 if it is in the business center, and 3 if it is in a business and urban center). Ordinal logistic regression with a bootstrap estimation is performed to determine the predictor variable that affects the response variable. This study found that two predictor variables affected the response variable significantly, namely return on assets and return on equity with a hit ratio of 96.41%. So that it can be concluded that the model obtained has been able to determine the level of performance of sharia small business bank in Indonesia.

“…Khan. N et al [5] explain that EWMA control chart for monitoring exponential distributed quality characteristics where the exponential distribution contained the characteristic function and term of convolution had researched by Devianto [6] and [7]. The sum of exponential distribution is the hypoexponential distribution can setting by stabilizer constant such as describe by Devianto et al [8] and [9].…”

Section: Introductionmentioning

confidence: 99%

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

Sari¹,

Proceedings of the Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bog

2020

Self Cite

Cement is one of the industrial products that has a quality control process. Major component that consists of SiO 2 , Al 2 O 3 , Fe 2 O 3 , CaO, MgO and SO 3 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. ParameterARL 0 is the average run observation of in control data. In this research, it is assumed the data was in control. The optimization of ARL 0 by weighted parameter of MEWMA control chart for λ=1, that is equal to Hotteling T 2 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.