Penerapan Peta Kendali Neutrosophic Exponentially Weighted Moving Average (NEWMA) X dalam Monitoring Rata-Rata Proses Ketebalan Kaca

In the industrial sector, the measurement results of a quality characteristic often involve an uncertainty interval (interval indeterminacy). This causes the classical control chart to be less suitable for monitoring quality. Currently, a control chart with a neutrosophic approach has been developed. The neutrosophic control chart was developed based on the concept of neutrosophic numbers with control charts. One of the control charts that have been developed to monitor the mean process is the Neutrosophic Exponentially Weighted Moving Average (NEWMA) X control chart. This control chart is a combination of neutrosophic with classical EWMA control chart. The neutrosophic control chart consists of two control charts, namely lower and upper, each of which consists of upper and lower control limits. Therefore, NEWMA X is more sensitive to detect out-of-control observations. In this research, the NEWMA X control chart will be used to monitor the average process of the thickness of the panasap dark grey 5mm glass produced by a glass industry. Through the analysis in this research, it was found that by using weighting λN [0, 10; 0, 10] and constant value kN [2, 565; 2, 675], the average process of the thickness of panasap dark grey 5mm glass has not beet controlled statistically because 21 observations were identified that were outside the control limits (out of control). When compared with the classical EWMA control chart with the same weighting λ, 17 observations were detected out of control. This proves that the NEWMA X control chart is more sensitive in detecting observations that are out of control because the determination of the in-control state is based on two values, lower and upper, both at the lower and upper control limits.

The Impact Of Covid-19 Pandemic On Nurses’ Behavior For Updating Assessment Results By Using The Electronic Medical Record Log Data In A Non- Covid Intensive Care Unit

The primary objective of this paper is to explore whether COVID-19 affects nurses’ behavior on updating assessment results in EMRs in an intensive care unit (ICU) and analyze how the patterns of updating assessment results can be different. The study considered information from March (before the pandemic) and July (during the pandemic) in terms of average process time and frequency. In this study, the response-time measurement system data was used to analyze ICU nurses’ workflow related to EMR documentation. After that, multiple hierarchical task analysis (HTA) charts were developed to find different EMR documentation patterns for assessment results. The results revealed that these patterns were significantly different in terms of average process time and frequency before and during the pandemic. The finding of this study might reveal the possible impact of COVID-19 pandemic on the patterns of updating patient assessment results and how nurses’ preferences can be different in terms of average process time and frequency.

A GAMMA MOVING AVERAGE PROCESS FOR MODELLING DEPENDENCE ACROSS DEVELOPMENT YEARS IN RUN-OFF TRIANGLES

ABSTRACT We propose a stochastic model for claims reserving that captures dependence along development years within a single triangle. This dependence is based on a gamma process with a moving average form of order $p \ge 0$ which is achieved through the use of poisson latent variables. We carry out Bayesian inference on model parameters and borrow strength across several triangles, coming from different lines of businesses or companies, through the use of hierarchical priors. We carry out a simulation study as well as a real data analysis. Results show that reserve estimates, for the real data set studied, are more accurate with our gamma dependence model as compared to the benchmark over-dispersed poisson that assumes independence.

One Dimensional Discrete Scan Statistics for Dependent Models and Some Related Problems

The one dimensional discrete scan statistic is considered over sequences of random variables generated by block factor dependence models. Viewed as a maximum of an 1-dependent stationary sequence, the scan statistics distribution is approximated with accuracy and sharp bounds are provided. The longest increasing run statistics is related to the scan statistics and its distribution is studied. The moving average process is a particular case of block factor and the distribution of the associated scan statistics is approximated. Numerical results are presented.

THE EFFECT OF PROBLEM-BASED PRACTICE TOWARDS LEARNING OUTCOME AND PROCESS SKILL ON CELL MATERIAL

This study aims to determine the effect of problem-based practice on student learning outcome and process skill in cell material in class XI Science Kartika Private High School 1-2 T.P 2018/2019. This research was conducted in July-September, at SMA Kartika 1-2 Medan. The population of this study was all students of class XI as many as 179 people. Samples are taken randomly. There were as many as 72 students. Statistical analysis showed that the average student learning outcomes in the experimental class are pretest of 63.22 and posttest of 82.89, while the control class pretest is 59.55 and the posttest is 69.44. Then hypothesis test (t-test) showed that (tcount = 5.4561 > ttable = 1.997). Which is means that the problem-based practice has a significant effect on the learning outcome. Besides, practice using PBL models can improve student process skills. This is shown in the results of the experimental class observation sheet having an average process skill in the “High” category. Whereas in the control class the average process skill is only up to the “Medium” category. So it can be concluded that the Problem-based practice has a significant effect on the learning outcome and process skill of class XI students of Private Kartika Senior High School 1-2 Medan T.P 2018/2019.