Abstract:This study aims to assess and analyze whether the marketing strategy STP (Segmentation, targets, and position) to the level of sales has been implemented by Upnormal Coffee Beach in Palu which has reached more than one year…
ear (2021- 2022). This type of research is quantitative descriptive. The population in this study were all employees of Upnormal Coffee while the sample of this research is all employees of Upnormal Coffee as many as 36 employees as respondents using saturation sampling, the sampling technique when all members of the population were used as a sample. The data collection techniques were performed by means of a questionnaire conducted interviews and questionnaires. Based on the results of this study with multiple linear regression analysis, regression equation Y = 8,944+ 0.164 X1 + 0.061 X2 + 0,032 X3 + e. Basedonn statistical analysis data, the indicators in this study is valid and the variables are reliable. In the classical assumption, in said that indicator otherwise normal distribution and correlation Linear in significance between each independent variable and the dependent variable, to the amount of influence Segmentation, Targeting and Positioning are all having a positive direction and not significant in their influence on the level of sales in Upnormal Coffee in the city of Palu
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: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.
Abstract:The purpose of this study was to determine the effect of trust and perceived risk on purchasing decisions at E-commerce Shopee partially and simultaneously. The sample used was 100 students of the Faculty of Economics and…
d Business who had been selected based on predetermined criteria. Data collection techniques were carried out using questionnaires and literature study. 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. The Trust variable has a positive and significant influence on purchasing decisions, the Perceived Of Risk variable has a positive and significant influence on purchasing decisions. the dependent variable of purchasing decisions can be explained by variables consisting of Trust and Perceived Of Risk, the rest is explained by other variables that were not examined in this study
Abstract:This study aims to find out how the effect of psychological empowerment on the workforce agility of the employees of the housing supply work unit in the province of West Sulawesi. This study uses a qualitative descriptive…
e approach through data collection by interviews and documentation and analyzed by reducing data, presenting data, and drawing conclusions and verification. The results of this study illustrate that psychological empowerment has an influence on the workforce agility of the employees of the housing supply work unit in the province of West Sulawesi, but it is not significant because there is one indicator of psychological empowerment that is not fulfilled, namely self-determination. On this indicator employees are limited in determining their own way of working because they are bound by contracts and rules that apply in the workplace. The indicators of unfulfilled workforce agility are proactive indicators. While other indicators are met. Based on the results of the research above, it is known that psychological empowerment has an insignificant effect on workforce agility.
Abstract:This study aims to determine the effect of marketing mix on sales volume at PT. Megahputra Prosperous Pettarani Makassar Branch. The population in this study are consumers at PT. Megahputra Sejahtera Pettarani Makassar Branch…
ranch who purchased Suzuki Ertiga car products in 2018-2022. Data collection was carried out using documentation and questionnaire methods. The data analysis technique used is multiple linear regression analysis. Multiple linear regression equations produce equations Y ̂= 0.308+ 0.248X_1+ 0.009X_2+ 0.027X_( 3)+ 0.094X_4 + ( -0.151 ) X_5+ 0.403X_6 + 0.137X_7. This the results of this study found that simultaneously the Marketing Mix variable (X1, X2, X3, X4, X6, and X7) has a positive effect on Sales Volume while X5 has a negative effect on Sales Volume. The results of the determination correlation analysis (R Square) were 0.343 which indicated that 34.3% of the independent variables namely X1, X2, X3, X4, X5, X6, and X7 had an effect or were able to explain the characteristics of the dependent variable (Y). While the remaining 65.7% is influenced or explained by other variables not included in this research model. The results of the F test explain that the seven Marketing Mix variables have a significant effect on the Sales Volume variable with a calculated F value (6.157) > F table (2.16) with a significance level of 0.000 <0.05 and the t test results explain that the Product variable (X1) with value 0.017 <0.05 and Process (X6) with a value of 0.001 <0.05 has a significant effect on Sales Volume variable
Abstract:This research examines The Influence of Work Stress on Employee Work Motivation in Financial Institutions and Regional Assets of Barru Regency. The purpose of this research is to find out The Influence of Work Stress on…
Employee Work Motivation in Financial Institutions and Regional Assets of Barru Regency. This research approach is quantitative. This research was conducted at the Regional Financial and Asset Agency of Barru Regency. The sample used was 68 people. Data collection techniques in the form of observation, questionnaires and documentation. Data analysis techniques include validity test, reliability test, normality test, descriptive analysis, simple linear regression analysis, t test (partial) and coefficient determination test (r2). The research results show thatwork stress has a negative and effect onwork motivation. The higher the work stress experienced by employees, the morework motivationemployees are decreasing. When an employee in carrying out his duties, gets a high work load, will take actions that can reduce the quality of his work there by reducing motivation at work. So it is concluded thatwork stress havenegative influenceto work motivation at the Regional Financial and Asset Agency of Barru Regency.
Abstract:Emas merupakan salah satu jenis komoditi yang paling banyak diminati untuk tujuan investasi, karena dipandang sebagai instrumen yang lebih aman dibandingkan saham serta memiliki nilai jual yang selalu bergerak mengikuti…
kondisi pasar. PT Victoeria Vici, sebagai pelaku usaha perhiasan emas custom, menghadapi kendala dalam menentukan estimasi harga jual kepada pelanggan, sebab proses pengerjaan pesanan custom membutuhkan waktu hingga 14 hari, sementara harga emas bergerak fluktuatif dan tidak terstruktur setiap harinya sehingga estimasi harga menjadi tidak akurat dan tidak efektif. Berdasarkan permasalahan tersebut, penelitian ini menerapkan konsep Data Mining dengan algoritma Trend Moment untuk mengestimasi harga emas pada rentang waktu tertentu. Data yang digunakan merupakan data historis harga emas per gram pada PT Victoeria Vici periode Agustus–Oktober 2021 sebanyak 92 data. Tahapan penelitian meliputi pengumpulan data, penentuan variabel X dan Y, eliminasi untuk memperoleh nilai konstanta a dan slope b, serta penerapan persamaan Y = a + bX untuk memperoleh nilai estimasi. Hasil perhitungan menunjukkan nilai a = 720.871,725 dan b = 3,108 sehingga model estimasi mampu menghasilkan proyeksi harga emas yang mendekati pola data historis. Model ini kemudian diimplementasikan ke dalam aplikasi berbasis desktop menggunakan Microsoft Visual Basic 2010 dan basis data Microsoft Access, dilengkapi Crystal Report untuk pencetakan laporan hasil estimasi. Hasil penelitian menunjukkan bahwa algoritma Trend Moment dapat membantu PT Victoeria Vici dalam memperoleh estimasi harga emas secara lebih cepat, konsisten, dan terdokumentasi.
Gold is one of the most sought-after commodities for investment purposes, as it is regarded as a safer instrument compared to stocks and has a selling value that constantly fluctuates with market conditions. PT Victoeria Vici, a custom gold jewelry business, faces difficulty in determining the estimated selling price offered to customers because the production process for custom orders takes up to 14 days, while gold prices move in an unstructured and fluctuating manner every day, making manual price estimation inaccurate and ineffective. Based on this problem, this study applies the concept of Data Mining using the Trend Moment algorithm to estimate gold prices over a certain period of time. The data used is historical daily gold price data per gram from PT Victoeria Vici for the period of August–October 2021, consisting of 92 records. The research stages include data collection, determination of the X and Y variables, elimination to obtain the constant value a and the slope b, and the application of the equation Y = a + bX to obtain the estimated value. The calculation results show a value of a = 720,871.725 and b = 3.108, so that the estimation model is able to produce gold price projections that closely follow the pattern of historical data. This model was then implemented into a desktop-based application using Microsoft Visual Basic 2010 and a Microsoft Access database, equipped with Crystal Report for printing estimation result reports. The results show that the Trend Moment algorithm can help PT Victoeria Vici obtain gold price estimations more quickly, consistently, and in a well-documented manner.
Abstract:This study aims to examine the influence of tourist attractions, facilities, and accessibility on tourist satisfaction at the Pondok Halimun Tourist Destination, Sukabumi Regency. The research employed a quantitative approach…
roach using a causal associative design. The population consisted of tourists who visited Pondok Halimun between April and July 2025. A total of 95 respondents were selected using accidental sampling techniques. Data were collected through questionnaires measured on a five-point Likert scale and analyzed using multiple linear regression with SPSS software.
The results indicate that tourist attractions, facilities, and accessibility individually have a positive and significant effect on tourist satisfaction. Furthermore, the simultaneous test confirms that these three variables collectively have a strong influence on tourist satisfaction. The coefficient of determination reveals that a substantial proportion of tourist satisfaction can be explained by the combined effects of tourist attractions, facilities, and accessibility. These findings suggest that integrated destination management focusing on attraction quality, adequate facilities, and ease of access is essential to enhance tourist satisfaction and support sustainable tourism development.
Abstract:This study aims to analyze the influence of entrepreneurship education on entrepreneurial interest among students at Lingga Buana PGRI University Sukabumi. Entrepreneurship is a key driver of economic growth and job creation,…
tion, thus higher education institutions need to optimize entrepreneurship education to foster students' entrepreneurial interest. This research employs a quantitative approach with descriptive and correlational design. The population consists of students who have taken entrepreneurship courses, with a sample of 300 respondents selected using proportionate stratified random sampling technique. The research instrument is a structured questionnaire using a 5-point Likert scale that has been tested for validity and reliability. Data analysis technique uses simple linear regression analysis with SPSS version 25 software. The results show that entrepreneurship education has a positive and significant effect on students' entrepreneurial interest with a correlation coefficient (R) of 0.721 and coefficient of determination (R²) of 0.520. This means that 52% of the variation in entrepreneurial interest can be explained by entrepreneurship education. Descriptively, entrepreneurship education received a "Good" rating (mean = 3.78) and students' entrepreneurial interest was in the "High" category (mean = 3.92). This research provides an important contribution to developing more effective entrepreneurship education strategies in higher education institutions.