Vol. 06, No. 07 [July 2020]

This study aims to determine the significant influence Education & Training on work productivity, System of reward / reward on work productivity, Quality of work life on work productivity and self promotion & development on work productivity in order to create employee loyalty. The study population was employees of PT Pama Persada Nusantara Tanjung Tabalong, South Kalimantan Indonesia, as many as 2009 employees, a sample of 147 respondents using a selected purposive random sampling method. The technique used in SEM analysis research is with the help of the Amos 24 program to obtain conclusions about the conditions and results of the data obtained. Empirical testing conducted tests on hypotheses put forward with a quantitative approach. Through this approach, the research process is carried out in a structured manner and uses research samples in an amount that can be considered representative of the population under study. The method used is purposive sampling by determining the subjects to be given a list of questions with the criteria of respondents in the study. Data collection techniques are carried out by means of surveys and distributing questionnaires as a primary data collection tool and equipped with observation, interviews and documentation. The test results prove the existence of a strong relationship between independent variables and the dependent variable is the factor of education & training, reward & reward systems and promotion & self-development significantly influence work productivity, while the quality of work life factor has no significant effect on work productivity and promotion and factors work productivity has a significant effect and four variables of quality, reward and training have no significant effect on employee loyalty. Likewise, the product has a significant effect on employee loyalty.
Keywords: Quality of work life, productivity, employee loyalty

The presented methodology consists on fitting a series of probability distribution functions among which were used the extreme variable distribution function, the logistics function, the tlocation scale and the normal time series data of daily dioxide nitrogen concentration from 2010 to 2020, for analysis and concentrations, to know the adjustment quality, the estimators adjustment such as the R2, RMSE, MSE and the Approximation Index were used. Subsequently, the Bayesian inference for the data or time series of the daily maximums of ozone and nitrogen dioxide was used to see how great the impact it have on the ozone generation in México City. Only the last 3 years were used as example, but it has been evaluated since 2010, the database is from the oficial Mexico´s goverment page of the air quality monitoring control. http://www.aire.cdmx.gob.mx/default.php
Keywords: Nitrogen Dioxide, Air Pollution, Random and Extreme Variable Distribution Functions, Bayesian Inference.

We all very well know that today use of Internet has been increased like anything. [1][4][6]The data on internet is growing like anything day by day. As per the latest survey on data, everyday, every minute around 550+ websites are being uploaded. Along with this every day is important as far as sending secure data is concerned. Our data is very much important and it is very necessary that the data must be sent in a secured way. There are various types of algorithms which are called either Symmetric or Asymmetric work on block of data where as some work as a stream cipher. In our previous paper, we compared symmetric algorithms but only by keeping their encryption and decryption time in mind here we have tried to cover other parameters along with only encryption and decryption time. We tried to compare various types of files i.e. Image, Audio and Video. Total 48 comparisons were made again with AES, DES, 3DES, Blowfish and Twofish. In this, we have used various types of padding techniques. Various parameters which are taken into consideration in this paper are Encryption and Decryption time, Usage of CPU while doing encryption and decryption, Memory usage while doing encryption and decryption, Memory swap size for encryption and decryption. By looking all above parameters the comparison is made.
Keywords: Encryption, Decryption, Cryptography, Symmetric, Asymmetric, Image Encryption, Audio Encryption, Video Decryption, AES, DES, 3DES, Blowfish, Multimedia

Intelligent transportation system and satellite communication technology have made great progress. The satellite navigation system can transmit the image to the land vehicle in real time, so that it can get the traffic information immediately. In addition, deep learning technology has been widely used in intelligent transportation and driverless technology. Therefore, this paper proposes a vehicle deflection angle detection model based on satellite image and deep learning. So, the proposed model needs to output the vehicle deflection angle in real time. To achieve this function, regression convolutional neural network (CNN) is introduced into this paper. First, the regression CNN architecture is constructed for vehicle deflection angle detection. Then the vehicle deflection angle data set is made according to the network requirements. Finally, appropriate activation function, learning rate and optimization method are selected according to the training situation. The experimental results show that the obtained vehicle deflection angle detection model can not only detect the vehicle deflection angle in real time, but also has high accuracy.
Keywords: Intelligent transportation; satellite communication technology; deep learning; regression convolutional neural network; vehicle deflection angel detection.

The purpose of this study was to examine the relationship of Retirement Planning with Attitude towards retirement planning, financial literacy, and goal clarity among Thai citizens. Also, the impact of demographic profile was tested as a moderator. A sample set of 151 units was used in the study which were collected through random sampling from different centers of Bangkok during the period of Oct-Nov, 2019. A moderated regression model was developed for hypothesis testing and the same was tested by the process of Andrew F. Hayes moderated regression model and the model is found significant at less than 1 percent level since the F-value (5,145) is 46.17, where p < 0.01. The explanatory power of the model is 61.42 percent (R-sq=0.6142) and there is high degree of positive correlation (R = 0.78) between Retirement Planning (DV) and the independent variables. The effect of the moderator variable ‘income’ on ‘attitude’ increases as the income level raises and that has a significant influence on retirement planning. The moderated regression model of Retirement Planning has been proved to be valid and significant for Thai people who are in the age group of 22 to 55 years and having a sufficient regular income of THB 20,000 or more per month. It was also proved that there exists a higher level of financial literacy and goal clarity among the above class of Thai citizens. Therefore, the investment products like pension plans, retirement plans, mutual funds, annuities, insurance etc. that are offered by investment / insurance companies shall be attractive among the above class of people in Thailand.
Keywords: Attitude, Investment, Pension Plan, Retirement Plan, Thailand