Analysis of User Satisfication with Graduates in Statistical Study Program Universitas Terbuka

Revolution 4.0 requires the Universitas Terbuka Statistics study program to change the educational curriculum that aims to produce quality graduate competencies. Therefore, to collect informationand evaluate the competence of graduates, it is necessary to conduct tracer study research on each graduate. This study aims to measure user satisfaction with graduate competencies using Gap analysis, Importance-Performance Analysis (IPA), Customer Satisfaction Index (CSI), and a multi-attribute Fishbein model. Based on the value of Gap and Science, the main priority that must be improved by graduates to meet user expectations is the ability to solve problems, generate ideas, and be able to present the results of these ideas in the form of reports/journals. The value of the level of suitability between user satisfaction and the importance of the ability of graduates is very good at 92.87% and a CSI value of 78.25%, which means that overall user satisfaction with graduates is good, besides thatbased on the results of the multi-attribute Fishbein model, an Ao value of 158.20 which means that graduate users have a positive attitude towards the abilities of UT Statistics program graduates.

Mathematical Modelling of Deforestation Due to Population Density and Industrialization

The focus of the study in this paper is to model deforestation due to population density and industrialization. To begin with, it is formulated into a mathematical modelling which is a system of non-linear differential equations. Then, analyze the stability of the system based on the Routh-Hurwitz stability criteria. Furthermore, a numerical simulation is performed to determine the shift of a system. The results of the analysis to shown that there are seven non-negative equilibrium points, which in general consist equilibrium point of disturbance-free and equilibrium points of disturbances. Equilibrium point TE7(x, y, z) analyzed to shown asymptotically stable conditions based on the Routh-Hurwitz stability criteria. The numerical simulation results show that if the stability conditions of a system have been met, the system movement always occurs around the equilibrium point.

Factors Affecting Dissolved Oxygen at Bengawan Solo River: A Spatial Filtering with Eigenvector Technique

The quality of the river changes according to the development of the surrounding environment which is influenced by various human activities. Analysis of factors affecting Dissolved Oxygen (DO) at Bengawan Solo River is crucial for river management purpose and pollution control. Previous research suggested the use classic multiple linear regression. However, DO measurement were usually took place of sampling sites along the river channel. Therefore, there is a high chance that the measurements results may spatially correlated. As the consequence, the utilization of multiple linear regression technique for the dataset can be inappropriate. In this paper, we applied a modification of multiple linear regression model to incorporate with spatial autocorrelation that exist in the data by adding control variable such vector eigen to the model which known as Spatial Filtering with Eigenvector (SFE). The results showed that nitrate and nitrite were the predictor variables that have a negative and significant effect. However, the model contains spatial autocorrelation. The application of SFE technique by adding three eigenvectors as control variables in the model succeeded in making the residual model free from spatial autocorrelation. However, a new problem arose where there was a violation of the non-heteroscedasticity assumption.

Using SAPR Model for Solution of Social Poverty Problem Due to Covid-19 in Makassar City

This study aims to build an SAPR model on the problem of poverty, analyze the model, predict the number of poverty rates in the city of Makassar, and determine the parameters that affect the decrease in the number of poverty rates due to Covid-19 in the city of Makassar. This research is quantitative. The population of this study is the number of people in Makassar City who are affected by the spread of COVID-19, while the sample of this study is 400 people. The research stages are: Building the SAPR model on the level of social poverty, determining and analyzing the stability of the equilibrium point, determining the value of the basic reproduction number (R0), conducting model simulations using Maple. The results shown that the mathematical model of SAPR which is a non-linear system of differential equations can be a reference model for the problem of poverty; The results also shown that the analysis of the social poverty level of the population finds two equilibrium points, namely the free equilibrium point for the poor and the poor; the stability of the equilibrium point is free-poor and poor; The basic reproduction number R0 = 0.426 indicates that the poverty level of the social population can be controlled even though it has increased. Based on the model simulation, it was found that the parameter in the form of business funding assistance from the government could reduce the poverty rate due to the Covid-19 pandemic in Makassar city.

Modeling The Types of Online Learning Media Using Multiple Linear Regression Analysis

The research objective is to model the types of learning media Whats App Group, Google Classroom, Zoom and YouTube with multiple linear regression analysis. Multiple linear regression analysis is a linear regression model with one continuous variable and k (two or more) independent variables. This type of research is quantitative research that can model several types of online learning. The object of study in this research is STKIP Pembangunan Indonesia students with a sample of 25 people. The source of data comes from primary data by giving questionnaires to students. Based on the results of the analysis, the type of online learning model obtained is = 70, 376 + 0, 357x1 + 0, 322x2 − 0, 279x1 − 0, 321x2 + ε with a contribution of 21.2%. From the resulting regression model, the best learning models or those often used by Lecturers at STKIP development are WhatsApp Group and Google Classroom. In addition to multiple linear regression analysis, other methods can also be used to model types of online learning media with the addition of media such as LMS Moodle, Edmodo and others.

The Effectiveness of Vaccination Against The Spread of COVID-19 with SEIR Mathematical Modeling in Gowa District

The spread of disease in epidemic range, endemic range, as well as in the pandemic range that is spreading of the disease can be stopped with getting vaccinated. The vaccines that are effective and efficient can be the missile that stopped this Covid-19 pandemic. The aim of this research is to (1) know the mapping model of mathematics SEIR in distributing vaccines toward the spread of Covid-19 in Kabupaten Gowa, (2) know the analysis and model simulation of mathematics SEIR in distributing vaccine toward the spread of Covid-19 in Kabupaten Gowa, also (3) know the impact of distributing vaccine toward the spread of Covid-19 in Kabupaten Gowa. The method we used is the literature review, the collecting data obtained by an interview and documentation review. The research result discovered that the model of mathematics SEIR is used to describe the distribution of vaccines toward the spread of Covid-19 in Kabupaten Gowa. The analysis and simulation results model of mathematics SEIR showed that the higher vaccines effectiveness and the number of the population in Kabupaten Gowa that already had vaccinated is higher, then showed no more spreads of Covid-19 and the pandemic is over.

Value-At-Risk Analysis Using ARIMAX-GARCHX Approach For Estimating Risk Of Bank Central Asia Stock Returns

Before buying a stock, an investor must estimate the risk which will be received. VaR is one of the methods that can be used to measure the level of risk. Most stock returns have a high fluctuation, so the variant is heteroscedastic, which is thought to be caused by exogenous variables. The time series model used to model data that is not only influenced by the previous period but is also influenced by exogenous variables is ARIMAX. In contrast, the GARCHX model is used to obtain a more optimal stock return data model with heteroscedasticity cases and is influenced by exogenous variables. This study uses the ARIMAX-GARCHX model to calculate the VaR of the stock returns of PT Bank Central Asia Tbk. The exogenous variables used are the exchange rate return of IDR/USD and the return of the JCI in the period January 3, 2017, to March 31, 2021. The best model chosen is the ARIMAX(2,0,1,1)-GARCHX(1,1,1). VaR calculation is carried out with the concept of moving windows with time intervals of 250, 375, and 500 transaction days. The results obtained at the 95% confidence level, the maximum loss obtained by an investor is 1,4%.

Comparative Analysis of The Growth of School Students Using Autoregressive Integrated Moving Average Methods Analisis

This study aims to analyze and predict the number of Elementary School Students using Autoregressive Integrated Moving Average (ARIMA) method using data from the last 17 years, case studies in three provinces namely Bali, West Nusa Tenggara (NTB), and East Nusa Tenggara (NTT). This type of research is quantitative by comparing the final value on the first graph to the fourth graph to analyze on the graph what the predictive value is most accurate. Based on the results of the simulation of the number of elementary school students in Bali, NTB, and NTT provinces using the G-MFS application program and mathematical model calculations that the predicted results in 2021 on the data of the number of elementary school students in Bali province amounted to 417,805.40 with a percentage decrease of 0.1%, then the predicted result in the data of the number of elementary school students in NTB province of 512,381.76 with a percentage increase of 1.0%. The predicted result on the data of the number of elementary school students in NTT province amounted to 705,335.11 with an increase of 1.0%. The results of the forecasting of the number of elementary school students are expected to provide important information for the government to improve development in the education sector, especially at the elementary school education level in one way that is to improve the quality of educational infrastructure and many more developments that need to be done by the number of students in the future.

Hausman and Taylor Estimator Analysis on The Linear Data Panel Model

Panel data modelling in the field of econometrics applies two main approaches, namely fixed effect estimators and random effects. The application of the Hausman and Taylor estimator to real data is used to test for fixed effects or random effects based on the idea that the set of estimated coefficients obtained from the fixed effect estimates is taken as a group. A good estimator is an estimator that is as close as possible to represent the characteristics of the population. The characteristics of a good estimator include unbiasedness, efficiency, and consistency. The purpose of this study is to identify the properties of the Hausman and Taylor estimator in the linear model of panel data. Based on the analysis using panel data, it is found that the Hausman and Taylor estimator on the random effects panel data is an estimator that is consistent and efficient even though it is not unbiased.

Forecasting Foreign Tourist Visits to West Nusa Tenggara Using ARIMA Method

West Nusa Tenggara (NTB) is one of the provinces in Indonesia that has its own charm in the world of tourism and is known as a pioneer of halal tourism. In addition to domestic tourists, NTB tourism always has an attraction for foreign tourists. This is evidenced by the increasing number of foreign tourists visiting NTB from year to year before the Covid-19 pandemic. This condition certainly has a positive impact on increasing NTB’s economic growth in the tourism sector and indirectly on the optimization of existing infrastructure. The purpose of the study is to predict the number of foreign tourist visits to NTB so that it can assist the government in making decisions in preparing adequate facilities and infrastructure in the event of a surge in tourist visits. The method used in this study is the Box-Jenkins-ARIMA model. The ARIMA method is based on 3 models that are formed from the results of plot data. The data used in this study is secondary data sourced from the Central Statistics Agency (BPS) of West Nusa Tenggara (NTB), from January 2010 to June 2019. The results show that the ARIMA (4,1,1) model is the most widely used model. This model is suitable for predicting the number of foreign tourists visiting NTB because this model produces the lowest SSE and MSE values compared to other models.