scholarly journals Pengaruh Psychological Capital terhadap Individual Readiness for Change pada Karyawan Sales

2021 ◽  
Vol 7 (1) ◽  
pp. 53-62
Author(s):  
Oktaviani Aditia Ningrum ◽  
Alice Salendu
Keyword(s):  
Linear Regression ◽  
Psychological Capital ◽  
Readiness For Change ◽  
Simple Linear Regression

Faktor penting keberhasilan inisiatif perubahan adalah kesiapan individu menghadapi perubahan. Perubahan organisasi yang dilakukan PT STI melalui inisiatif Optimus menuntut karyawan untuk siap dalam menghadapi perubahan yang terjadi. Kesiapan individu dalam menghadapi perubahan dapat ditingkatkan melalui peningkatan psychological capital yang dimiliki individu. Penelitian ini bertujuan untuk pengetahui pengaruh modal psikologis terhadap kesiapan individu menghadapi perubahan. Penelitian ini merupakan studi kuantitatif. Partisipan pada penelitian ini adalah 123 orang karyawan sales di divisi area operation PT. STI. Instrumen penelitian yang digunakan pada penelitian ini adalah skala individual readiness for change (α=0,939) yang dikembangkan oleh Holt, Armenakis, Field dan Harris (2007) dan skala psychological capital questionnaire (α= 0,922) yang dikembangkan oleh Luthans dkk (2007).  Hasil analisis korelasi menunjukkan secara simultan, keempat dimensi psychological capital berkorelasi positif dengan individual readiness for change dengan nilai r= 0,520. Hasil pengujian hipotesis dengan menggunakan simple linear regression menunjukkan nilai r2 = 0,270 maka 27% variasi dari readiness for change dapat dijelaskan oleh psychological capital dan 73% dijelaskan oleh sebab lain yang tidak diteliti dalam penelitian ini. Penelitian ini menujukkan Psychological capital secara signifikan dapat memprediksi readiness for change dengan F=10,923, sig=0.000.

The Contribution of Sexual Identity Towards the Students’ Perception of Lesbian, Gay, Bisexual, and Transgender

10.32698/0642 ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 120
Author(s):  
Wiwi Delfita ◽  
Neviyarni S. ◽  
Riska Ahmad
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Sexual Identity ◽  
Student Perceptions ◽  
Undergraduate Students ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Simple Linear Regression ◽  
Simple Linear Regression Analysis ◽  
Bisexual And Transgender

Some students perceive lesbian, gay, bisexual, and transgender (LGBT) positively, even though LGBT is a sexual deviation that is not appropriate with values and norms. There are several factors that influence an individual's perception of LGBT, including sexual identity. This study aims at looking at the contribution of sexual identity to student perceptions about LGBT. This research used a quantitative approach with a descriptive method and a simple linear regression analysis. The sample of this research was 385 taken from 15.752 undergraduate students of Universitas Negeri Padang which the sample was drawn by using the Slovin formula and continued with a Proportional Random Sampling technique. The instrument used was the Guttman model's sexual identity scale and the scale of students' perceptions of the LGBT Likert model. After analyzing the data with the descriptive technique and the simple linear regression analysis, the results showed that sexual identity significantly contributed to the students' perceptions of LGBT. This research has implications as a basis for counselors to help students avoid sexual identity mismatches and prevent the emergence of positive perceptions of LGBT.

Pengaruh Penghargaan Terhadap Kinerja Karyawan pada CV. Dino Manunggal Karsa Bogor

2019 ◽  
Vol 4 (2) ◽  
pp. 17
Author(s):  
Dedy Mulyadi ◽  
Didik Purwanto
Keyword(s):  
Linear Regression ◽  
Performance Assessment ◽  
Correlation Coefficient ◽  
Linear Regression Analysis ◽  
Strong Relationship ◽  
Simple Linear Regression ◽  
New Employees ◽  
Company Policy ◽  
Effective Manner ◽  
Relationship Of

The question of compensation in addition to sensitive to be driving someone to worl due to an effect on morale and discipline employees. Therefore , any  agency or any organization should be able to provide compensation equal to the workload  to create a workforce that efficient and effective manner can be realized. Amaore than that, the company’s goal to improve performance. Performance assessment is a subjective process that involves human judgments. Thus, performance assessment is very likely wrong and very easily influonced by sources that are not actual, so it must be taken into account and considered reasinable. Frformance appraisals are considered  to meet the target if it has a good impact on new employees who rated their performance. Simple linear regression analysis using SPSS version 12:00 data processing obtained tegression equation Y = 0,487 X 74 + with an explanation of X = award, 74 = constant, 0.487 = coefficient awards, and Y = performance based on simple linear regression equation in case of increase of one unit of the  performance award will be increased 0.487 units. If company policy negates the performance award will remain at a constant rate (74) units . (A) Test results obtained thitung significant constants of (12.574) > t table for (1.960 then reject Ho constanta significant meaning. (B) significant Test award coefficient t count the results obtained by (2.164)> t table foe (1.96) then reject Ho the mean coeffent of appreciation affect the performance . (C) correlation coefficient analysis is done by calculating the product moment corration (pearson)  to test  whether or not a strong  relationship between the variables X  dan Y , based on the results of cakculations with SPSS  table valuse obtained by calculating the  correlation coefficient r (0.3100> r on the table for a = 0,05 (0.291) then reject Ho, which means there is a relationship of respect for performance. When we enter these valuse in the table shows the interpretation of the correlation coefficient between the interval from 0.20 to 0.399 which has a low relationship

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 INTELLECTUAL CAPITAL TERHADAP KINERJA KEUANGAN PADA PERUSAHAAN BARANG KONSUMSI YANG TERDAFTAR DI BEI TAHUN 2015-2017

2019 ◽  
Vol 3 (2) ◽  
pp. 26
Author(s):  
Niken Ayu Wulandari ◽  
Tegoeh Hari Abrianto ◽  
Edi Santoso
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Financial Performance ◽  
Intellectual Capital ◽  
Stock Exchange ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Simple Linear Regression ◽  
Return On Equity ◽  
Asset Turnover

This research to analyze and evaluate intellectual capital on financial performance obtained by return on equity, asset turnover and growth in revenue. The population in this study are consumer goods companies listed on the Stock Exchange in 2015-2017. The research sample was received by 21 companies obtained by using purposive sampling technique. The analytical method used is simple linear regression analysis with the SPSS version 20 application and uses the VAICTM method to measure intellectual capital. The results of this study indicate that intellectual capital has a significant effect on financial performance generated by return on equity, but intellectual capital does not have a significant effect on financial performance required by asset turnover and growth in revenue.

IMPLEMENTASI ALGORITMA REGRESI LINEAR SEDERHANA DALAM MEMPREDIKSI BESARAN PENDAPATAN DAERAH (STUDI KASUS: DINAS PENDAPATAN KAB. DELI SERDANG)

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Fransiskus Ginting ◽  
Efori Buulolo ◽  
Edward Robinson Siagian
Keyword(s):  
Data Mining ◽  
Linear Regression ◽  
Visual Basic ◽  
Large Contribution ◽  
Simple Linear Regression ◽  
Information Discovery ◽  
Regional Income ◽  
Local Revenue ◽  
Local Taxes ◽  
The Future

Data Mining is an information discovery by extracting information patterns that contain trend searches in a very large amount of data and assist the process of storing data in making a decision in the future. In determining the pattern classification techniques do to collect records (Training set). Regional income is generally derived from local taxes and levies, local taxes are one source of funding for the region on the national average has not been able to make a large contribution to the formation of local revenue. By utilizing Regional Revenue data, it can produce forecasting and predictions of Regional Revenue income in the future to match the reality / reality so that the planned RAPBD can run smoothly. Simple Linear Regression or often abbreviated as SLR (Simple Linear Regression) is one of the statistical methods used in production to make predictions or predictions about the characteristics of quality and quantity to describe the processes associated with data processing for the acquisition of regional income. So that in the testing phase with visual basic net can help in processing valid Regional Revenue Amount data. Keywords: Data Mining, Local Revenue, Simple Linear Regression Algorithm, Visual Basic net 2008

Pengaruh Corporate Social Responsibility Terhadap Nilai Dan Kinerja Perusahaan Manufaktur

2011 ◽  
Vol 3 (1) ◽  
pp. 1-13
Author(s):  
Agustin Ekadjaja ◽  
Vony Vony
Keyword(s):  
Corporate Social Responsibility ◽  
Linear Regression ◽  
Confidence Level ◽  
Stock Exchange ◽  
Tobin’S Q ◽  
Manufacturing Companies ◽  
Simple Linear Regression ◽  
Tobin's Q ◽  
And Performance ◽  
Corporate Social

This study aims to determine the effect of CSR Index to the value and performance of manufacturing companies listed on the Indonesia Stock Exchange (BEI), and to find out how much the ability of the variable CSR Index in explaining the variable Tobin’s Q, ROA, and ROE manufacturing companies listed on Indonesia Stock Exchange (BEI). This study uses data sampled during the 75 years from 2007 to 2009. A statistical method used to test the research hypothesis is a simple linear regression model. Therefore, before performing hypothesis testing carried out tests of classical assumptions. The results of this study prove that, CSR Index has a significant effect on Tobin’s Q and ROE with 95% confidence level. However, CSR Index has no significant influence on ROA with 95% confidence level. Key words : CSR Index, Variabel Tobin’s Q, ROA, ROE

PENGARUH KUALITAS PRODUK DAN KUALITAS LAYANAN TERHADAP KEPUASAN PELANGGAN

2017 ◽  
Vol 5 (3) ◽  
Author(s):  
Ismail Razak, SE., MS. ◽  
Nirmala Putri Sari
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Product Quality ◽  
Sampling Method ◽  
Primary Data ◽  
Analysis Method ◽  
Simple Linear Regression ◽  
The City

The aim of this study was to analize the effects of product quality and service quality on the customer satisfaction. This study took place in the City of Bekasi and objects in this study are all customer who use the Matrass GM-9000. Primary data was obtained from customers of Matrass GM-9000 in Bekasi City through admission filling of questionnaire by using scale of Likert. The respondent of this study was chosen through accidental sampling method, and data analysis method was simple linear regression and multiple linear regression. The results of this study indicated that product quality and service quality positively and significant influenced the customer satisfaction

PENGARUH KUALITAS LAYANAN DAN NILAI PELANGGAN TERHADAP KEPUASAN PELANGGAN

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Ismail Razak, SE., MS. ◽  
Silviana Fadilla Prasevie
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Service Quality ◽  
Multiple Linear Regression ◽  
Customer Value ◽  
Sampling Method ◽  
Analysis Method ◽  
Simple Linear Regression ◽  
Central Java ◽  
Data Analysis Method

The purpose of this study was to analize the impacts of service quality and customer value on the satisfaction of customers. Questionnaires are used to collect data from Boks Café customer in Bumiayu, Kabupaten Brebes, Central java by using scale of Likert. In this study, accident sampling method was used and data analysis method was simple linear regression and multiple linear regression. The results of this study indicated that service quality and customer value positively and significant influenced the satisfaction of customers. The conclution of this study is that customer value was dominant than service quality in influencing the satisfaction of customers

PENGARUH KUALITAS LAYANAN DAN CITRA PERUSAHAAN TERHADAP KEPUASAN NASABAH

2017 ◽  
Vol 5 (2) ◽  
Author(s):  
Ismail Razak, SE., MS. ◽  
Elza Finnora
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Sampling Method ◽  
Services Quality ◽  
Corporate Image ◽  
Primary Data ◽  
Analysis Method ◽  
Simple Linear Regression ◽  
Data Analysis Method

The aim of this study was to analize the influence of services quality and corporate image on the satisfaction of customers. Primary data was obtained from customers of Standard Chartered Bank through admission filling of questionnaire by using scale of Likert. In this study, accident sampling method was used and data analysis method was simple linear regression and multiple linear regression. The results of this study indicated that services quality and corporate image positively and significant influenced the satisfaction of customers. The conclution of this study is that services quality was dominant than corporate image in influencing the satisfaction of customers.

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).

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