Development and evaluation of trans-Amadi groundwater parameters: The integration of finite element techniques

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Finite Element ◽  
Polynomial Regression ◽  
Nitrate Concentration ◽  
Strong Relationship ◽  
Total Iron ◽  
Coefficient Of Determination ◽  
Port Harcourt ◽  
Polynomial Expression ◽  
The Relationship ◽  
Best Fit

Mathematical model was developed and evaluated to monitor and predict the groundwater characteristics of Trans-amadi region in Port Harcourt City. In this research three major components were considered such as chloride, total iron and nitrate concentration as well as the polynomial expression on the behavious on the concentration of each component was determined in terms of the equation of the best fit as well as the square root of the curve. The relationship between nitrate and distance traveled by Nitrate concentration by the model is given as Pc = 0.003x2 - 0.451x + 14.91with coefficient of determination, R² = 0.947, Chloride given as Pc = 0.000x2 - 0.071x + 2.343, R² = 0.951while that of Total Iron is given as Pc = 2E-05x2 - 0.003x + 0.110, R² = 0.930. All these show a strong relationship as established by Polynomial Regression Model. The finite element techniques are found useful in monitoring, predicting and simulating groundwater characteristics of Trans-amadi as well as the prediction on the variation on the parameters of groundwater with variation in time.

scholarly journals PENGARUH KUALITAS PELAYANAN DAN NILAI PELANGGAN TERHADAP TINGKAT KEPUASAN MAHASISWA (STUDI KASUS DI UNIVERSITAS AZZAHRA JAKARTA)

2018 ◽  
Vol 13 (2) ◽  
pp. 187-209
Author(s):  
Asep Candra Hidayat
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Student Satisfaction ◽  
Customer Value ◽  
Strong Relationship ◽  
Coefficient Of Determination ◽  
Validity And Reliability ◽  
R Value ◽  
The Relationship ◽  
Positive Effect

This study aimed to analyze how much influence service quality, customer value on the level of customer satisfaction. The sampling method used is Proportionate Random Sampling. The sample in this study followed the formula Slovin, or as many as 100 students of  Azzahra University, Jakarta.Data that has met the test of validity and reliability further processed to produce a regression equation Y = 0.484+ 0021 0686 X1 + X2, where Y is the variable rate Student Satisfaction, X1 is a variable Quality of Service and Customer Value X2 is variable.Hypothesis testing using t test showed that each of the independent variables studied was shown to significantly affect partially dependent variable Student Satisfaction.Quality of service partially positive effect on customer satisfaction shown by the r value of 0.663, which means a strong relationship between them. While the value of the coefficient of determination (R2) amounted to 0,439, which means that service quality may explain the variable of student satisfaction of 43.9%, while the remaining 56.1% is explained by other variables.Customer value partially positive effect on customer satisfaction shown by the r value of 0.832 which means the relationship between them is very strong. While the value of the coefficient of determination (R2) amounted to 0,692, which means that service quality may explain the variable of student satisfaction at 69.2%, while the remaining 30.8% is explained by other variables.Then through the F test can be known simultaneously that both variables of service quality and customer value has a significant impact on customer satisfaction shown by the r value of 0.835 which means the relationship between them is very strong. While the value of the coefficient of determination (R2) is equal to 0.697, which means that service quality may explain the variable of student satisfaction at 69.7%, while the remaining 30.3% is explained by other variables.

scholarly journals Potensi Biomassa Dan Karbon Tersimpan Tegakan di Ruang Terbuka Hijau Kota Polewali, Sulawesi Barat

2020 ◽  
Vol 12 (1) ◽  
pp. 49
Author(s):  
Daud Irundu ◽  
Mir A Beddu ◽  
Najmawati Najmawati
Keyword(s):  
Global Warming ◽  
Urban Areas ◽  
Green Space ◽  
Urban Forest ◽  
Urban Forests ◽  
Tree Height ◽  
Strong Relationship ◽  
Coefficient Of Determination ◽  
Relationship Of ◽  
The Relationship

Global warming is one of the major environmental issues of this century. Carbon dioxide (CO2) emissions are the main cause of global warming. Green open space (RTH) such as urban parks, urban forests and green lines play an important role in mitigating global warming and climate change in urban areas because it is able to reduce CO2 from the atmosphere. This study aims to determine the potential of biomass and carbon stored in the Green Open Green Space of Polewali, West Sulawesi. Data collection for stored biomass and carbon is carried out at three green space locations including; Urban forest and city park and green lane each made three plots measuring 20 m x 20 m, and three plots on the Green Line measuring 1200 m. Retrieval of data by measuring tree height and diameter, analysis to obtain the dry volume, biomass and carbon stored for each tree species contained in the Polewali green space. Biomass is obtained by the formula M = BJ x Vk x BEF, the stored carbon value is obtained from the product of biomass by 0.47. The magnitude of the relationship of volume with biomass and carbon uses a regression equation (Ŷ=a+bX). The results show there are types of Glodokan (Polyalthia longifolia), Johar (Senna siamea), Mahogany (Swetenia sp) and Trambesi (Samanea saman) which are spread in the Polewali open green space. Trambesi is a type that has dominant biomass and stored carbon of 381.95 (tons / ha) and 179.52 (ton/ha). Green lane is the type of green space that has the most stored carbon and is currently 440.94 (ton/ha) and 207.24 (ton/ha). The overall green space biomass is 571.83 (ton/ha) and stored carbon is 268.76 (ton/ha) found in urban forests, urban gardens and green belt. The relationship of volume with biomass and stored carbon shows a very strong relationship with the coefficient of determination (R2) of 0.96.  

scholarly journals Pengaruh Pelatihan Terhadap Produktivitas Karyawan pada PT.Alfaria Trijaya, Tbk Soekarno-Hatta Bandung

KarismaPro ◽  
2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Harun Heri Trismiyanto
Keyword(s):  
Labor Productivity ◽  
Work Productivity ◽  
Strong Relationship ◽  
Coefficient Of Determination ◽  
Employee Productivity ◽  
Workforce Management ◽  
Descriptive Research ◽  
Multiple Correlation Analysis ◽  
The Relationship

So that labor productivity increased labor, one of the ways that must be taken workforce management is providing training to its workforce. This research is classified into associative research and descriptive research. Associative research is research that aims to determine the relationship between two or more variables. in this study, researchers will explain the variables that would be appropriate that occurred in PT.Alfaria Trijaya, Tbk Bandung.The total number of employees PT.Alfaria Trijaya, Tbk part minimarket service in the Bandung area is a total of about 1500 people. The sample will be taken is 62 people. the data analysis is classifying data based on variables and types of respondents, tabulate the data based on the variables of all respondents, presenting the data of each variable studied, perform calculations to test the hypothesis that has been proposed. The results of multiple correlation analysis showed a correlation value 0892. means of training and productivity of employees have a degree of force that is very strong relationship with work productivity. That assumption is taken from the value of 0, 892 which is in the range of 0.8 to 1.The coefficient of determination used to how big the influence of training on labor productivity. Based on the analysis using SPSS 13:00 KD value obtained is equal to 0796 X 100% = 79.6% of the value shows that the effect of training on labor productivity is 79.6% while the remaining 20.4% influenced by other variables. Based on the calculation result is unknown if the training provides a positive and significant effect on employee productivity. The condition is indicated when an increase in the quality of training will result in an increase in employee productivity.

scholarly journals HUBUNGAN PEMANFAATAN LABORATORIUM GAMBAR DENGAN HASIL BELAJAR SISWA

Jurnal PenSil ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 138-145
Author(s):  
Eko Atmaja ◽  
Arris Maulana
Keyword(s):  
Student Learning ◽  
Learning Outcomes ◽  
Descriptive Analysis ◽  
Strong Relationship ◽  
Student Learning Outcomes ◽  
Coefficient Of Determination ◽  
Survey Method ◽  
Analysis Techniques ◽  
Building Information ◽  
The Relationship

This study aims to determine the relationship between the use of the laboratory drawing with student learning outcomes in the subject of Drawing with Software in the Department of Modeling and Building Information Design at the 6th Vocational High School in Bekasi City. Seeing student learning outcomes that have not met the Minimum Learning Completeness and the use of laboratory images that have not been maximized, this study was conducted to determine the relationship between the two. This research is a correlational research, quantitative approach, survey method with a sample of 50 students. Data collection used 29 items of laboratory utilization questionnaire and 30 test questions for student learning outcomes. The instrument validity uses product moments. Instrument reliability was tested using Alpha Chronbach. Data analysis techniques using descriptive analysis techniques of 0.612 which means that there is a strong relationship between the use of image laboratories with student learning outcomes. Based on the significance of the correlation coefficient test (t-test), the results show that tcount> ttable with the calculation result of tcount of 5.367 and ttable of 1.9996 this indicates that there is a significant relationship between the two variables. Based on the calculation of the coefficient of determination for the two variables obtained 37.5% which means that the use of drawing laboratories can affect student learning outcomes by 37.5%.

scholarly journals BUDAYA ORGANISASI DAN KINERJA PEGAWAI PADA BAGIAN UMUM SEKRETARIAT DAERAH KABUPATEN KEPULAUAN TANIMBAR

2021 ◽  
Author(s):  
Hilarius Wandan
Keyword(s):  
Organizational Culture ◽  
Organizational Performance ◽  
Employee Performance ◽  
Strong Relationship ◽  
Research Data ◽  
Coefficient Of Determination ◽  
Simple Linear Regression ◽  
A Value ◽  
Independent Variable ◽  
The Relationship

ABSTRAK Data penelitian yang diperoleh sesuai masalah yang diteliti, dianalisa dengan menggunakan rumus regresi linier sederhana, dan diperoleh persamaan Y=6,18+0,58X.Persamaan dimaksud menunjukkan bahwa setiap kali terjadi perubahan (kenaikan atau penurunan) pada variabel X (budaya organisasi) sebesar 1 poin akan diimbangi dengan perubahan (kenaikan atau penurunan) variabel Y (kinerja pegawai) sebesar 1 poin pada konstanta 6,18. Dari analisis korelasi diperoleh gambaran bahwa hubungan antara variabel bebas (budaya organisasi) dengan variabel terikat (kinerja pegawai) sebesar 0,59 yang berada pada nilai interval 0,40 – 0,599 dengan kategori hubungan cukup kuat. Analisa kontribusi variabel X (budaya organisasi) terhadap variabel Y (kinerja pegawai) dengan menggunakan persamaan koefisien determinasi, diperoleh nilai 34,81%. Hal ini menunjukkan bahwa variabel X (budaya organisasi) memberikan kontribusi sebesar 34,81% terhadap variabel Y (kinerja organisasi), sedangkan sisanya, yakni 65,19% ditentukan oleh faktor-faktor lain. Kata kunci : Budaya Organisasi, Kinerja Pegawai.ABSTRACTThe research data obtained is in accordance with the problem under study, analyzed using a simple linear regression formula, and the equation Y = 6.18 + 0.58X is obtained. The equation shows that every time there is a change (increase or decrease) in variable X (organizational culture) 1 point will be offset by a change (increase or decrease) in Y variable (employee performance) by 1 point at a constant of 6.18. From the correlation analysis, it can be seen that the relationship between the independent variable (organizational culture) and the dependent variable (employee performance) is 0.59 which is in the interval value 0.40 - 0.599 with a fairly strong relationship category.Analysis of the contribution of variable X (organizational culture) to variable Y (employee performance) using the coefficient of determination equation, obtained a value of 34.81%. This shows that variable X (organizational culture) contributes 34.81% to variable Y (organizational performance), while the rest, namely 65.19% is determined by other factors.Keywords: Organizational Culture, Employee Performance.

scholarly journals Pengaruh Pemberian Insentif Terhadap Prestasi Kerja Karyawan Pada PT Wahyu Promo Citra Jakarta

2019 ◽  
Vol 19 (2) ◽  
pp. 201-206
Author(s):  
Nurlaela Eva puji Lestari
Keyword(s):  
Human Resources ◽  
Work Performance ◽  
Employee Performance ◽  
Strong Relationship ◽  
Coefficient Of Determination ◽  
Individual Member ◽  
Calculation Results ◽  
Incentive Policies ◽  
The Relationship ◽  
A Company

Human resource management can also produce a good performance in a company by assessing, giving rewards for each individual member of the organization or company in accordance with their respective work capabilities. The human resources department that designs and administers incentive policies as one part of compensation. If a company is able to provide incentives precisely and precisely, it will be one of the most appropriate ways for employees to improve their work performance. Samples used for collection the data in this research are 44 employees at PT Wahyu Promo Citra Jakarta. The purpose of this study is to find out and analyze the relationship between Giving Incentives (X) on Employee Performance (Y) at PT Wahyu Promo Citra Jakarta. Based on the analysis and processing of data based on the calculation of the correlation coefficient, it can be seen that Giving Incentives has a strong relationship that is equal to 0.664 and according to the calculation results the coefficient of determination can be known which is 44.1%, so the relationship between Giving Incentives (X) and Employee Performance (Y) it can be concluded that there is a strong relationship. Keywords: Incentives, Employee Performance

Tumor mutational burden (TMB) and response rates to immune checkpoint inhibitors (ICIs) targeting PD-1, CTLA-4, and combination.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 2578-2578 ◽  
Author(s):  
Arsen Osipov ◽  
Aleksandra Popovic ◽  
Alexander Hopkins ◽  
Garrett M. Frampton ◽  
Lee A. Albacker ◽  
...  
Keyword(s):  
Checkpoint Inhibitors ◽  
Statistical Significance ◽  
Objective Response ◽  
Strong Relationship ◽  
Coefficient Of Determination ◽  
Clinical Activity ◽  
Average Improvement ◽  
Tumor Mutational Burden ◽  
Tumor Types ◽  
The Relationship

2578 Background: ICIs targeting PD-1/L1 and/or CTLA-4 have activity against many different cancers. We and others have previously shown that a higher TMB, a surrogate for an increased number of expressed tumor neoantigens, is an important biomarker for response to anti-PD-1/L1 monotherapy. Whether the relationship between the TMB and response to ICIs extends beyond anti-PD-1/L1 is unknown. Methods: We identified 30 major solid tumor types for which TMB has been described using a genomic profiling assay performed by Foundation Medicine. We conducted searches of MEDLINE (from Jan 1, 2010 to Jan 20, 2019), as well as abstracts presented at ASCO, ESMO, AACR Annual Meetings 2010-2018 to identify the objective response rate (ORR) for anti-PD-1/L1, anti-CTLA-4 and combination anti-PD-1/L1 plus anti-CTLA-4, in each of these cancer types. We pooled the response data from the largest published studies that evaluated the ORR. We excluded studies that; enrolled < 10 evaluable patients, investigated ICI therapies in combination with other agents, and studies that selected patients based on immune-related biomarkers. Across tumor types, median TMB was compared to ORR utilizing the coefficient of determination (r2) derived from simple linear regressions. Results: TMB is strongly associated with response to anti-PD-1/L1 monotherapy (n = 8798, r2= 0.4704, p < 0.001), and combination anti-PD-1/L1 plus anti-CTLA-4 (n = 2280,r2= 0.4082, p = 0.004). Available ORR data were more limited with CTLA-4 monotherapy and the relationship between ORR and TMB did not meet statistical significance (n = 1377, r2= 0.2606, p = 0.1086). The additional ORR benefit of adding a CTLA-4 inhibitor to anti-PD-1/PDL1 therapy increased with increasing TMB. In tumor types with a lower TMB ( < 10 mutations/MB), combined ICI therapy led to an average improvement of 5.5% in ORR over PD-1/L1 monotherapy, versus 21.8 % ORR improvement in high TMB tumors (≥10 mutations/MB). Conclusions: A strong relationship exists between TMB and clinical activity of both PD-1/L1 monotherapy and combination ICIs with PD-1/L1 plus CTLA-4. The clinical benefit of adding anti-CTLA-4 to anti-PD-1/L1 is greatest in high TMB tumors and limited in low TMB tumors.

Numerical-Experimental Model and Polynomial Regression Method for Interpretation of G-BHN Relation of Kraft-Based Fibrous Composites Evaluated by Using Brinell Analysis

2019 ◽  
Vol 798 ◽  
pp. 370-375 ◽  
Author(s):  
Rakdiaw Muangma ◽  
Supattra Wongsaenmai ◽  
Tawat Soitong
Keyword(s):  
Shear Modulus ◽  
Polynomial Regression ◽  
Brinell Hardness ◽  
Testing Machine ◽  
Quadratic Function ◽  
Quadratic Model ◽  
Coefficient Of Determination ◽  
Fibrous Composites ◽  
The Mathematical Model ◽  
The Relationship

This research focused on the mathematical model that could be simplified as the series function. This function used for macroscopic explanation of the relationship between shear modulus and Brinell hardness of fibrous composites. Kraft paper was used as the sample for this testing. The paper-grammage was varied as following:150, 230, and 420, whereas, the dwell time of indentation was ranging as: 10, 20, and 30 seconds, respectively. And then, the correlation between shear modulus (G) and Brinell Hardness Number (BHN) was obtained by using the simulation of experimental results. These were collected by the Brinell hardness testing machine. After that, the refitting process was analyzed using the polynomial based on linear and quadratic model, respectively. It was found that the interpretation of G-BHN relation using the quadratic be better than the linear one. Because of the coefficient of determination (R2) that analyzed by quadratic function present in higher value than another one.

scholarly journals Parameter Estimation of Fractional Trigonometric Polynomial Regression Model

2019 ◽  
Vol 27 (1) ◽  
pp. 519-526
Author(s):  
Taiwo Abass Ishola ◽  
Olatayo Timothy Olabisi ◽  
Adesanya Kazeem Kehinde
Keyword(s):  
Blood Pressure ◽  
Trigonometric Polynomial ◽  
Predictive Power ◽  
Polynomial Regression ◽  
Blood Pressure Level ◽  
Coefficient Of Determination ◽  
Outcome Variable ◽  
Risk Variable ◽  
High Level ◽  
The Relationship

 Trigonometric Polynomial Regression is a form of non-linear regression in which the relationship between the outcome variable and risk variable is Fractional modeled as 1/nth degree polynomial regression by combining the function of cos(nx) and sin(nx) on the value of natural numbers. The model was used to analyze the relationship between three continuous and periodic variables. Coefficients of the model were estimated using the Maximum Likelihood Estimate (MLE) method. From the results, the model obtained indicated that an increased in body mass index will increase the level of blood pressure while age may or may not have an influence on the blood pressure level. The values of the Coefficient of variation showed the variation in the dependent variable was well explained by the independent variables and the value of the adjusted coefficient of determination showed the model had a good fit with a high level of predictive power.  

The Influential Effect On Job Performance At PT. Honda Perdana City of Sukabumi, West Java

2020 ◽  
Author(s):  
endang naryono
Keyword(s):  
Work Performance ◽  
Employee Performance ◽  
Sampling Technique ◽  
Strong Relationship ◽  
Primary Data ◽  
Coefficient Of Determination ◽  
Positive Role ◽  
Incentive Value ◽  
Incentive Variable ◽  
The Relationship

This research is about the effect of incentives on work performance at PT. Honda Perdana Sukabumi during the 4th period from 2016 to 2019, sampling technique using saturated samples where all populations are sampled, namely all salesman salespeople and sales counters using primary data that is by distributing questionnaire, this study aims to determine the significant and positive influence between incentives on work performance at PT. Honda Prime Sukabumi.The method used in this research is associative descriptive by taking secondary data and primary data from the 2016-2019 vehicle sales report and the results of the questionnaire and analysis of influence using regression analysis, correlation and coefficient of determination. The results of this study show a correlation value (r) of 0.677 or 45.80%, this means that the influence of the insetive turnaround on work performance is strong enough and the nature of the relationship is positive, meaning that if the incentive value increases, the resulting work performance will increase.The value of the relationship between the Incentive variable and employee performance is indicated by the correlation value r = 0.770, which means that it is between the values 0.76 - 1.00, which means it has a very strong relationship, the nature of the positive relationship, which means that if incentives increase, employee performance will increase also. The value of the effect of the Incentive variable on employee performance is shown by the regression equation y = 1.881 + 0.503x. Which means if the incentive value goes up by 1 point, the work performance is 1,881 + 0.503 = 2.338. This means that if incentives increase, employee performance will also increase. While the magnitude of the coefficient of determination 59.29%. This value shows the magnitude of the role of incentives for employee work performance by 59.29% while the remaining 40.71% is influenced by other variables outside the incentive and the positive role character, meaning that the better the incentives, the more will improve employee work performance.

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