Abstract:Advances in technology such as the presence of social media require companies to be able to adjust in carrying out their activities such as marketing using influencer marketing. This study aims to determine the effect of…
influencer marketing on purchasing decisions for the Makassar branch of Chaca Burgo. This research uses qualitative methods by conducting observations, questionnaires, and interviews. Data were analyzed using a simple linear regression analysis method that used SPSS data processing results to prove the hypothesis. The results showed that the influencer marketing variable had a positive and significant effect on the purchasing decision variable. So that the better influencer marketing is in carrying out promotions, the purchasing decisions by consumers will increase.
Abstract:This study aims to determine the effect of motivation and work environment on employee performance at the Department of Trade and Industry of Gowa Regency. The population in this study were all employees at the Department…
t of Trade and Industry of Gowa Regency, totaling 40 people. The number of samples used is the entire population because there are less than 100 people, namely the type of saturated cover, with this type of quantitative research. The data used are primary data and secondary data obtained using a questionnaire distribution technique.The results of the research after being processed with SPSS. 21 Based on the results of the research it shows that motivation (X1) has a positive and significant effect on employee performance. work environment (X2) has an effect on employee performance, and in terms of positive influence it also has a significant impact. And together motivation and work environment affect employee performance.
Abstract:This study aims to determine the influence of the solvency ratio has an influence on the ratio at PT. Unilever Tbk for the 2014-2022 quarter, the data in this study are secondary data for 32 samples. The methods used to…
analyze the relationship between variables are descriptive analysis, classical assumption test, multiple linear regression and hypothesis testing. The findings in this study show that partially the solvency ratio has no effect on the solvency ratio. It is also known that the solvency ratio does not have a significant effect on changes in earnings
Abstract:This study aims to determine the effect of lifestyle and self-concept on consumptive behavior in students of the Faculty of Economics, Makassar State University. The population in this study were 2757 students of the Faculty…
ulty of Economics, Makassar State University and a sample of 96 students was drawn. This study uses a type of quantitative research with a regression approach. Data collection techniques were carried out by observation, interviews, documentation and distributing questionnaires (questionnaires). The analysis technique used is multiple linear regression. The results showed that partially, the lifestyle variable (X1) had a positive effect on consumptive behavior (Y) with a value of T count (5.732) > T table (1.985) and the self-concept variable (X2) had a positive effect on consumptive behavior (Y) with a value of T count (3.085) > T table (1.985), while simultaneously the lifestyle variable (X1) and self-concept (X2) had a positive effect on consumptive behavior (Y) with a value of F count (51.087) > F table (3.10).
Abstract:This study aims to determine the effect of motivation on employee performance at the Department of Trade and Industry of Gowa Regency. The population in this study were all employees at the Department of Trade and Industry…
ry of Gowa Regency, totaling 40 people. The number of samples used is the entire population because there are less than 100 people, namely the type of saturated cover, with this type of quantitative research. The data used are primary data and secondary data obtained using a questionnaire distribution technique. The results of the research after being processed with SPSS.21 Based on the results of the research it shows that motivation (X) has a coefficient value of 0.841 and t_count > t_table (3.385 > 2.026) and the value of Sig. of 0.002 <0.05, which means that motivation has a positive and significant effect on employee performance.
Abstract:The Effect of Compensation on Employee Organizational Commitment of PT. Vale Tbk in Sorowako. The purpose of this study was to determine the Effect of Compensation on Employees' Organizational Commitment at PT. Vale Tbk…
in Sorowako. This type of research is quantitative research. The number of samples in this study were 60 employees who were employees in the Maintenance Department of PT. Vale The results of the study after the data were processed showed that there was a positive influence between the financial compensation (X1) and non-financial compensation (X2) variables on the Organizational Commitment variable (Y) which can be shown through the results of the T test, namely variable X1 has variable X1 has t count 4.653 > 2.002 (t table) and sig. 0.000 < 0.05. Variable X2 has a t count of 3.392 > 2.002 (t table) and a sig. 0.000 < 0.05.
Abstract:This study aims to analyze the effect of job satisfaction on turnover intention. The population in this study are employees who are at PT. Hadji Kalla Makassar, Urip Sumoharjo Branch, with a total sample of 51 employees.…
This research is a quantitative study and quantitative analysis, using a simple regression test model using the SPSS version 25 software. The results of this study indicate that job satisfaction has a negative and significant effect on turnover intention with a correlation coefficient value of 32.5%
Abstract:The purpose of this study was to determine the effect of the work environment on the job satisfaction of the Samsat Office UPT Regional Income Makassar 1 regionally partially and simultaneously. The samples used were 40…
employees of the UPT Regional Revenue Samsat Office Makassar Region 1. The data collection technique was carried out by means of a questionnaire. Data analysis techniques consist of validity test, reliability test, classic assumption test consisting of normality test, multicollinearity test, and heteroscedasticity test, multiple linear analysis test, hypothesis test, test of the coefficient of determination. Physical Work Environment Variables have a positive and significant effect on job satisfaction, and Non-Physical Work Environment variables have a positive and significant effect on job satisfaction. The most dominant variable affecting job satisfaction is the non-physical work environment variable. The dependent variable job satisfaction can be explained by variables consisting of the physical work environment, and the remaining non-physical work environment is explained by other variables that were not examined in this study.
Abstract:This study aims to determine the effect of electronic word of mouth and price on purchasing decisions for Big Bananas in Makassar City partially and simultaneously. The population in this study are followers of the Big Bananas…
ananas Instagram account, totaling 78,182 users as of November 2022. The sample used is based on the slovin formula with an error rate of 10%, namely 100 respondents. The sampling withdrawal technique is systematic random sampling. Data collection techniques were carried out using questionnaires, literature studies and interviews. The data analysis technique used is multiple regression analysis using SPSS 22.00 for windows. The results showed that electronic word of mouth and price had a positive and significant effect on purchasing decisions for Big Bananas in Makassar City.
Abstract:The purpose of the study was to determine the effect of product quality and service quality on customer satisfaction at the SLV Room Boutique. The population in this study were consumers of SLV Room Boutique. the sampling…
g in this study was carried out using a purposive sampling technique so that 80 respondents were sampled. The type of research used is quantitative. The data used is primary data obtained by distributing questionnaires to consumers. The results of the study after the data was processed with SPSS.23 show that there is a partially significant effect between the independent variable and the dependent variable which can be proven by the calculated t value of the product quality variable (X1) of 2,938> t table 1.665 with a significant value of 0.004 <0.05 and the calculated t value of the service quality variable (X2) of 4.700> t table 1.665 with a significant value of 0.000 <0.05. Simultaneously there is a positive and significant effect on the dependent variable (X2). Simultaneously, there is a positive and significant influence between the independent variables on the dependent variable as evidenced by the multiple linear regression equation, namely Y = -0.754 + 0.167 X1 + 0.338 X2 + e and a significant effect with a calculated F value of 56.016 > F table 3.965 with a significant level of 0.00 <0.05. The R Square value or the coefficient of determination of 0.593 indicates that 59.3% of the customer satisfaction variable (Y) is influenced or can be explained by the independent variables of product quality and service quality, while the remaining 40.7% is explained by other variables not included in this study. Simultaneously there is a positive and significant effect on the dependent variable (X2). Simultaneously, there is a positive and significant influence between the independent variables on the dependent variable as evidenced by the multiple linear regression equation, namely Y = -0.754 + 0.167 X1 + 0.338 X2 + e and a significant effect with a calculated F value of 56.016 > F table 3.965 with a significant level of 0.00 <0.05. The R Square value or the coefficient of determination of 0.593 indicates that 59.3% of the customer satisfaction variable (Y) is influenced or can be explained by the independent variables of product quality and service quality, while the remaining 40.7% is explained by other variables not included in this study. Simultaneously there is a positive and significant effect on the dependent variable (X2). Simultaneously, there is a positive and significant influence between the independent variables on the dependent variable as evidenced by the multiple linear regression equation, namely Y = -0.754 + 0.167 X1 + 0.338 X2 + e and a significant effect with a calculated F value of 56.016 > F table 3.965 with a significant level of 0.00 <0.05. The R Square value or the coefficient of determination of 0.593 indicates that 59.3% of the customer satisfaction variable (Y) is influenced or can be explained by the independent variables of product quality and service quality, while the remaining 40.7% is explained by other variables not included in this study. there is a positive and significant influence between the independent variables on the dependent variable as evidenced by the multiple linear regression equation, namely Y = -0.754 + 0.167 X1 + 0.338 X2 + e and a significant effect with a calculated F value of 56.016> F table 3.965 with a significant level of 0.00 <0.05. The R Square value or the coefficient of determination of 0.593 indicates that 59.3% of the customer satisfaction variable (Y) is influenced or can be explained by the independent variables of product quality and service quality, while the remaining 40.7% is explained by other variables not included in this study. there is a positive and significant influence between the independent variables on the dependent variable as evidenced by the multiple linear regression equation, namely Y = -0.754 + 0.167 X1 + 0.338 X2 + e and a significant effect with a calculated F value of 56.016> F table 3.965 with a significant level of 0.00 <0.05. The R Square value or the coefficient of determination of 0.593 indicates that 59.3% of the customer satisfaction variable (Y) is influenced or can be explained by the independent variables of product quality and service quality, while the remaining 40.7% is explained by other variables not included in this study. 338 X2 + e and a significant effect with a calculated F value of 56.016> F table 3.965 with a significant level of 0.00 <0.05. The R Square value or the coefficient of determination of 0.593 indicates that 59.3% of the customer satisfaction variable (Y) is influenced or can be explained by the independent variables of product quality and service quality, while the remaining 40.7% is explained by other variables not included in this study. 338 X2 + e and a significant effect with a calculated F value of 56.016> F table 3.965 with a significant level of 0.00 <0.05. The R Square value or the coefficient of determination of 0.593 indicates that 59.3% of the customer satisfaction variable (Y) is influenced or can be explained by the independent variables of product quality and service quality, while the remaining 40.7% is explained by other variables not included in this study.