scholarly journals MATHEMATICAL MODELING OF MICROBIAL GROWTH IN VACUUM-PACKAGED AND REFRIGERATED FRESH COW MEAT

2021 ◽  
Vol 4 (3) ◽  
pp. e303
Author(s):  
Odangowei Ogidi ◽  
Pere-Ere S. Tobia ◽  
Mike N. Ayebabogha ◽  
Ayebatitari P. Sunny
Keyword(s):  
Linear Regression ◽  
Constant Temperature ◽  
Storage Time ◽  
Microbial Growth ◽  
Aluminum Foil ◽  
Coefficient Of Determination ◽  
Lag Phase ◽  
Perishable Product ◽  
Test Organisms ◽  
Cow Meat

Fresh meat is a highly perishable product due to its biological composition. This study examined the effect of different storage time (24, 48, 72 hours), gaseous permeability of packaging film (Aluminum foil and Polyethylene) on the growth of microorganisms (Bacteria and fungi) isolated from the refrigerated cow meat at constant temperature of 0°C. Microbial growth was modeled using Gompertz and Linear Regression Models. The bacteria count was observed to decrease as the storage time increases. While fungi count was observed to increase with increasing storage time. Aluminum foil packaged cow meat samples recorded lower microbial growth when compared to polyethylene packaged samples. In Gompertz model, the specific growth rate (μ) of the test organisms was observed to increase significantly upon a shift of storage time. The transition from 24 hours to 48 hours resulted in large changes in the growth profile with increased maximum population density (MPD) of the test organisms. However, lag phase of approximately two hours for bacteria and five hours for fungi was observed. An increase of storage time from 48 hours to 72 hours, an accelerated μ, higher MPD with reduced lag phase duration (LPD) was observed. In the linear regression model, the  coefficient of determination (R2) values for aluminum foil packaged samples was 0.3 and polyethylene packaged samples was 0.1. Therefore, it can be concluded that varying storage time at constant temperature; μ and MPD of the test organisms significantly increased with decreasing LPD of both studied vacuum packaging films of the refrigerated fresh cow meat.

FAKTOR-FAKTOR YANG MEMPENGARUHI KUALITAS AUDIT

2019 ◽  
Vol 5 (1) ◽  
pp. 50-63
Author(s):  
Heru Heryanto ◽  
Nur Laela ◽  
Riana R Dewi
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Audit Quality ◽  
Positive Influence ◽  
T Test ◽  
Coefficient Of Determination ◽  
Analysis Tool ◽  
Validity And Reliability ◽  
Test Analysis ◽  
Analysis Technique

This study aims to determine the significance of the influence of competence, independence, professionalism, auditor experience, accountability, and auditor's knowledge of audit quality. This study uses a questionnaire with a population and sample, namely all auditors who work at the Public Accounting Office (KAP) in the Special Region of Yogyakarta and Surakarta. Sampling techniques using Convenience Sampling with a sample of 61 respondents. The data used in this study is a questionnaire using a Likert scale 1 to 5. The data analysis technique used in this study is multiple linear regression using the SPSSprogram for Windows. The analysis tool in this study using validity and reliability, the classical assumption (normality test, multicollinearity, heteroscedasticity test and autocorrelation test) while the data were analyzed using multiple linear regression test, t test, F test and the coefficient of determination (R2).Based on the results of the t-test analysis performed, it shows that there is a positive influence of competence, independence, professionalism, auditor experience, accountability, and auditor's knowledge of audit quality and simultaneously competency, independence, professionalism, auditor experience, accountability, and auditor knowledge variables affect quality audit

Maintaining Customer Loyalty by Intensifying Service Quality and Customer Satisfaction in Commuter Line Jabodetabek

2019 ◽  
Vol 10 (9) ◽  
pp. 902-909
Author(s):  
Umbas Krisnanto ◽  
◽  
Conny Marpaung ◽  
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Hypothesis Testing ◽  
Customer Loyalty ◽  
T Test ◽  
Coefficient Of Determination ◽  
Simple Linear Regression ◽  
Significance Level

This study aims to determine and analyze the influence of Service Quality and Customer Satisfaction on Customer Loyalty in Jabodetabek Commuter Line. The sample of this study was 50 people. Methods of collecting data by distributing questionnaires. Data analysis using the analysis used is simple linear regression, t test and coefficient of determination. The results showed 1) Service Quality has a positive and significant effect on Customer Loyalty in Jabodetabek Commuter Line, with a significance level of 0.048; and supported by the results of hypothesis testing with a t-count value of 4.433 > t-table value of 1.95, with a significance of 0.048 or < 0.05; 2) Customer Satisfaction positive and significant effect on Customer Loyalty in Jabodetabek Commuter Line, with a level significance of 0,000; and supported by the results of hypothesis testing with a t-count value of 4,969 > t-table value of 1.95, with a significance of 0,000 or < 0.05, 3) Service quality and Customer Satisfaction have a positive and significant effect on Customer Loyalty in Jabodetabek Commuter Line, with a significance level of 0,000. This means that the hypothesis H0 is rejected and Ha is accepted so that it can be concluded that service quality and customer satisfaction together have a positive and significant effect on customer loyalty in Jabodetabek Commuter Line.

PENGARUH HARGA DAN BRAND TRUST TERHADAP KEPUTUSAN PEMBELIAN OPPO SMARTPHONE (Studi kasus pada OPPO Store, Sinergy Celular Medan)

2019 ◽  
Vol 14 (1) ◽  
pp. 17
Author(s):  
Andi S Tarigan ◽  
Zulkarnaian Siregar
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Coefficient Of Determination ◽  
Purchase Decision ◽  
Brand Trust ◽  
Significance Level ◽  
Research Hypothesis ◽  
Analysis Technique ◽  
The Relationship

AbstrakPenelitian ini bertujuan untuk mengetahui Pengaruh Harga dan Brand Trust Terhadap Keputusan Pembelian pada Sinergy Celular Medan.Sampel dalam penelitian ini adalah seluruh pengunjung Sinergy Celular Medan sebanyak 77 orang.Teknik pengumpulan data yang digunakan adalah melalui kuesioner (angket) yaitu dengan cara menyebarkan kuesioner kepada sampel (responden) dan mengumpulkannya kembali. Teknik analisis data yang digunakan adalah Regresi Linear Berganda.Sebelum data diregresikan maka terlebih dahulu di uji keterkaitannya antara variabel, datanya diuji menggunakan uji normalitas data, multikolinearitas, dan heterokedastisitas.Serta untuk mengetahui kontribusi faktor Harga dan Brand TrustTerhadap Keputusan Pembelian digunakan rumus Koefisien Determinasi (R2). Hipotesis penelitian diterima apabila t hitung >  t tabel dengan tingkat signifikansi 0,1. Nilai t tabel dalam penelitian ini 1,993. Nilai t hitung variabel X1 sebesar 2,107 t hitung lebih besar dari t tabel maka hipotesis di terima, nilai t hitung variabel X2   sebesar 3,405 t hitung lebih besar dari t tabel maka hipotesis di terima. Kata kunci: Harga, Brand Trust, Keputusan Pembelian AbstractThis study aims to determine the Influence of Price and Brand Trust on Purchasing Decision at Sinergy Celular Medan. The sample in this study is all visitors Sinergy Celular Medan as many as 77 people.Data collection technique used is through questionnaire (questionnaire) that is by distributing questionnaires to the sample (respondent) and collect it back. Data analysis technique used is Multiple Linear Regression. Before the data is diregresikan then first in the test the relationship between variables, the data tested using the test of data normality, multicollinearity, and heterokedastisitas. And to know the contribution of price factors and Brand Trust Against Purchase Decision is used the formula Coefficient of Determination (R2). Research hypothesis accepted if t arithmetic> t table with significance level 0,1. The value of t table in this study is 1,993. Value t arithmetic variable X1 of 2.107 t arithmetic greater than t table then the hypothesis received, the value of t arithmetic variable X2 of 3.405 t arithmetic greater than t table then the hypothesis received. Keywords: Price, Brand Trust, Purchase Decision

FRAUD CONFIRMATION, CLIENT SATISFACTION AND CLIENT LOYALTY

2019 ◽  
Vol 1 (1) ◽  
pp. 39
Author(s):  
Ngurah Pandji Mertha Agung Durya
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Client Satisfaction ◽  
Audit Quality ◽  
Hypothesis Test ◽  
Linear Regression Analysis ◽  
Quality Attributes ◽  
Path Model ◽  
Coefficient Of Determination ◽  
The Government

<p>This study aims to find evidence, the influence of Audit Quality Attributes, Client Satisfaction and Client Loyalty, which are moderated by Fraud Confirmation. The research was conducted at the BKM, a community-based organization, formed by the Government, through the <em>Kotaku</em> Program. The research used Regression statistical analysis and conducted a hypothesis test. Regression analysis used includes Simple Linear Regression Analysis, Multiple Regression Analysis, and MRA Regression Analysis, and Path Model Linear Regression Analysis. This study also pays attention to the calculation of the coefficient of determination to give an idea of the ability of the model in explaining the phenomenon of Client Satisfaction and Client Loyalty. The result that both partially and simultaneously, Audit Quality Attributes, Fraud Confirmation affected Client Satisfaction and Loyalty. The research also succeeded in proving that Client Satisfaction mediates the effect of Audit Quality Attributes on Client Loyalty, but failed to provide empirical evidence, that the Fraud Confirmation moderated the effect of Audit Quality Attributes on Client Satisfaction and Loyalty. Contribution to audit practices, where it is important to realize Client Satisfaction through Audit Quality Attributes and Fraud Confirmation, especially in situations where Fraud acts are suspected.</p>

PENGARUH MOTIVASI KERJA, KOMPETENSI, DAN KOMPENSASI TERHADAP KINERJA KARYAWAN RUMAH SAKIT UMUM DAERAH (RSUD) KABUPATEN KEPULAUAN MENTAWAI

2020 ◽  
Author(s):  
Syofrinal
Keyword(s):  
Linear Regression ◽  
Work Motivation ◽  
Regression Coefficient ◽  
Employee Performance ◽  
Primary Data ◽  
Coefficient Of Determination ◽  
Reliability Test ◽  
Mentawai Islands ◽  
Regression Test ◽  
Analytical Tools

The purpose of this study is to test the Influence of Work Motivation, Competence, and Compensation Against Performance Employees Regional General Hospital (RSUD) Mentawai Islands District. This study is a census. The data used are primary data by taking sample of 79 (seventy nine) respondents. This research uses analytical tools such as validity, reliability test, multiple linear regression test, t test, F test and coefficient of determination (R2). The results of this study illustrate that all variables have an effect on employee performance except the compensation variable. The results can be described by the equation Y = 12.752 + 0.248X1 + 0.396X2 + 0.051 X3, where X1 = Work Motivation, X2 = Competence, and X3 = Compensation. This means that the constant of 12.752 states that factors other than the variables X1, X2, and X3 that affect employee performance of 12,752. Work Motivation coefficient of 0.248 states that if the variable X1 added one unit will add the effect of employee performance of 0.248 with the assumption that the competence and compensation variables are constant. The regression coefficient X2 of 0.396 is that if the variable X2 increases one unit will increase the employee performance by 0.396 with the assumption that the variable of work motivation and compensation is constant. Furthermore, with X3 regression coefficient of 0.051. This means that with other factors considered constant, the effect of compensation is less than that of work motivation and competence.

scholarly journals Developing Equations for Converting Digestible Energy to Metabolizable Energy for Korean Hanwoo Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1696
Author(s):  
Ridha Ibidhi ◽  
Rajaraman Bharanidharan ◽  
Jong-Geun Kim ◽  
Woo-Hyeong Hong ◽  
In-Sik Nam ◽  
...  
Keyword(s):  
Linear Regression ◽  
Beef Cattle ◽  
Strong Relationship ◽  
Dietary Factors ◽  
Metabolizable Energy ◽  
Coefficient Of Determination ◽  
Simple Linear Regression ◽  
Male And Female ◽  
Digestible Energy ◽  
Wide Range

This study was performed to update and generate prediction equations for converting digestible energy (DE) to metabolizable energy (ME) for Korean Hanwoo beef cattle, taking into consideration the gender (male and female) and body weights (BW above and below 350 kg) of the animals. The data consisted of 141 measurements from respiratory chambers with a wide range of diets and energy intake levels. A simple linear regression of the overall unadjusted data suggested a strong relationship between the DE and ME (Mcal/kg DM): ME = 0.8722 × DE + 0.0016 (coefficient of determination (R2) = 0.946, root mean square error (RMSE) = 0.107, p < 0.001 for intercept and slope). Mixed-model regression analyses to adjust for the effects of the experiment from which the data were obtained similarly showed a strong linear relationship between the DE and ME (Mcal/kg of DM): ME = 0.9215 × DE − 0.1434 (R2 = 0.999, RMSE = 0.004, p < 0.001 for the intercept and slope). The DE was strongly related to the ME for both genders: ME = 0.8621 × DE + 0.0808 (R2 = 0.9600, RMSE = 0.083, p < 0.001 for the intercept and slope) and ME = 0.7785 × DE + 0.1546 (R2 = 0.971, RMSE = 0.070, p < 0.001 for the intercept and slope) for male and female Hanwoo cattle, respectively. By BW, the simple linear regression similarly showed a strong relationship between the DE and ME for Hanwoo above and below 350 kg BW: ME = 0.9833 × DE − 0.2760 (R2 = 0.991, RMSE = 0.055, p < 0.001 for the intercept and slope) and ME = 0.72975 × DE + 0.38744 (R2 = 0.913, RMSE = 0.100, p < 0.001 for the intercept and slope), respectively. A multiple regression using the DE and dietary factors as independent variables did not improve the accuracy of the ME prediction (ME = 1.149 × DE − 0.045 × crude protein + 0.011 × neutral detergent fibre − 0.027 × acid detergent fibre + 0.683).

scholarly journals Microbial Growth Study on Pork Loins as Influenced by the Application of Different Antimicrobials

Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 968
Author(s):  
David A. Vargas ◽  
Markus F. Miller ◽  
Dale R. Woerner ◽  
Alejandro Echeverry
Keyword(s):  
Storage Time ◽  
Microbial Growth ◽  
Storage Conditions ◽  
Indicator Bacteria ◽  
Aerobic Bacteria ◽  
Growth Study ◽  
Treatment Interventions ◽  
Pork Industry ◽  
Bacterial Enumeration ◽  
The Impact

The use of antimicrobials in the pork industry is critical in order to ensure food safety and, at the same time, extend shelf life. The objective of the study was to determine the impact of antimicrobials on indicator bacteria on pork loins under long, dark, refrigerated storage conditions. Fresh boneless pork loins (n = 36) were split in five sections and treated with antimicrobials: Water (WAT), Bovibrom 225 ppm (BB225), Bovibrom 500 ppm (BB500), Fit Fresh 3 ppm (FF3), or Washing Solution 750 ppm (WS750). Sections were stored for 1, 14, 28, and 42 days at 2–4 °C. Mesophilic and psychrotrophic aerobic bacteria (APC-M, APC-P), lactic acid bacteria (LAB-M), coliforms, and Escherichia coli were enumerated before intervention, after intervention, and at each storage time. All bacterial enumeration data were converted into log10 for statistical analysis, and the Kruskal–Wallis test was used to find statistical differences (p < 0.05). Initial counts did not differ between treatments, while, after treatment interventions, treatment WS750 did not effectively reduce counts for APC-M, APC-P, and coliforms (p < 0.01). BB500, FF3, and WS750 performed better at inhibiting the growth of indicator bacteria when compared with water until 14 days of dark storage.

scholarly journals Calibrations of Low-Cost Air Pollution Monitoring Sensors for CO, NO2, O3, and SO2

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 256
Author(s):  
Pengfei Han ◽  
Han Mei ◽  
Di Liu ◽  
Ning Zeng ◽  
Xiao Tang ◽  
...  
Keyword(s):  
Random Forest ◽  
Linear Regression ◽  
Short Term Memory ◽  
Hot Spot ◽  
Low Cost ◽  
Field Evaluation ◽  
Pollution Monitoring ◽  
Coefficient Of Determination ◽  
Air Pollution Monitoring ◽  
National Monitoring

Pollutant gases, such as CO, NO2, O3, and SO2 affect human health, and low-cost sensors are an important complement to regulatory-grade instruments in pollutant monitoring. Previous studies focused on one or several species, while comprehensive assessments of multiple sensors remain limited. We conducted a 12-month field evaluation of four Alphasense sensors in Beijing and used single linear regression (SLR), multiple linear regression (MLR), random forest regressor (RFR), and neural network (long short-term memory (LSTM)) methods to calibrate and validate the measurements with nearby reference measurements from national monitoring stations. For performances, CO > O3 > NO2 > SO2 for the coefficient of determination (R2) and root mean square error (RMSE). The MLR did not increase the R2 after considering the temperature and relative humidity influences compared with the SLR (with R2 remaining at approximately 0.6 for O3 and 0.4 for NO2). However, the RFR and LSTM models significantly increased the O3, NO2, and SO2 performances, with the R2 increasing from 0.3–0.5 to >0.7 for O3 and NO2, and the RMSE decreasing from 20.4 to 13.2 ppb for NO2. For the SLR, there were relatively larger biases, while the LSTMs maintained a close mean relative bias of approximately zero (e.g., <5% for O3 and NO2), indicating that these sensors combined with the LSTMs are suitable for hot spot detection. We highlight that the performance of LSTM is better than that of random forest and linear methods. This study assessed four electrochemical air quality sensors and different calibration models, and the methodology and results can benefit assessments of other low-cost sensors.

Prediction Models for Truck Accidents at Freeway Ramps in Washington State Using Regression and Artificial Intelligence Techniques

1998 ◽  
Vol 1635 (1) ◽  
pp. 30-36 ◽  
Author(s):  
Wael H. Awad ◽  
Bruce N. Janson
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Linear Regression ◽  
Prediction Models ◽  
Washington State ◽  
Training Data ◽  
Coefficient Of Determination ◽  
Training Process ◽  
Truck Accidents ◽  
High Level

Three different modeling approaches were applied to explain truck accidents at interchanges in Washington State during a 27-month period. Three models were developed for each ramp type including linear regression, neural networks, and a hybrid system using fuzzy logic and neural networks. The study showed that linear regression was able to predict accident frequencies that fell within one standard deviation from the overall mean of the dependent variable. However, the coefficient of determination was very low in all cases. The other two artificial intelligence (AI) approaches showed a high level of performance in identifying different patterns of accidents in the training data and presented a better fit when compared to the regression model. However, the ability of these AI models to predict test data that were not included in the training process showed unsatisfactory results.

PENGARUH STRES KERJA TERHADAP TURNOVER INTENTION PADA KARYAWAN PT INTERNUSA JAYA SEJAHTERA MERAUKE

2018 ◽  
Vol 13 (1) ◽  
pp. 59
Author(s):  
Samrotu Sa’adah ◽  
Arif Partono Praseti
Keyword(s):  
Linear Regression ◽  
Work Stress ◽  
Turnover Intention ◽  
Descriptive Analysis ◽  
Linear Regression Analysis ◽  
Coefficient Of Determination ◽  
A Value ◽  
Employee Turnover Intention ◽  
Analysis Technique ◽  
Positive Effect

This study aims to examine the effect of work stress on employee turnover intention at PT Internusa Jaya Sejahtera Merauke, Papua. This study obtained data from questionnaires distributed to 117 employees of PT Internusa Jaya Sejahtera. The questionnaire used has 14 point statements and uses a 6 point Likert scale. The technique used in this research is descriptive analysis technique used to analyze the level of work stress and turnover intention level on employees. Simple linear regression analysis is also used to determine the effect between work stress variables and turnover intention variables. The results showed that work stress had a significant positive effect on turnover intention on employees of PT Internusa Jaya Sejahtera. The coefficient of determination in this study has a value of 0.571 which means that the level of job stress to turnover intention of 57.1%.Keywords : work stress, turnover intention, linear regression ABSTRAK Penelitian ini bertujuan untuk meneliti pengaruh stres kerja terhadap turnover intention pada karyawan di PT Internusa Jaya Sejahtera Merauke, Papua. Peneltian ini memperoleh data dari hasil penyebaran kuesioner kepada 117 karyawan PT Internusa Jaya Sejahtera. Kuesioner yang digunakan memiliki 14 butir pernyataan dan menggunakan skala Likert 6 poin. Teknik yang digunakan pada penelitian kali ini adalah teknik analisis deskriptif yang digunakan untuk menganalisis tingkat stres kerja dan tingkat turnover intention pada karyawan. Analisis regresi linier sederhana juga digunakan unntuk mengetahui pengaruh antara variabel stres kerja dan variabel turnover intention. Hasil penelitian menunjukkan bahwa stres kerja berpengaruh signifikan positif terhadap turnover intention pada karyawan PT Internusa Jaya Sejahtera. Koefisien determinasi pada penelitian ini memiliki nilai 0.571 yang memiliki arti bahwa tingkat stres kerja terhadap turnover intention sebesar 57,1%.Kata kunci : stres kerja, turnover intention, regresi linier.

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