Analysis of Promotion and Service Quality on Customer Satisfaction of the State Electricity Company (PT. PLN (Persero) Customer Service Unit of Teluk Betung Sub-District, Bandar Lampung City, Lampung Province, Indonesia

: Promotion and Electronic Service Quality are important elements in achieving customer satisfaction. The purpose of this study was to analyze the impact of promotion and electronic service quality on customer satisfaction both individually and simultaneously. The population studied was customers of PT PLN ULP Teluk Betung who had used the PLN Mobile Application, with a total of 32,632 people. The sample selection technique used the cluster random sampling method with a total of 380 respondents, calculated using the Krejcie & Morgan formula. The results showed that: (1) promotion has a significant effect on customer satisfaction, (2) electronic service quality variables also have a significant effect on customer satisfaction, (3) simultaneous tests show that promotion and electronic service quality together have a significant effect on customer satisfaction. With the results of this study, PT PLN ULP Teluk Betung can evaluate promotional strategies and improve the quality of services provided to customers to increase their satisfaction. It is recommended to PT PLN ULP Teluk Betung to continue to improve promotions by distributing at various points and also making updates to the application to improve the quality of services provided.


Research Background
The fast growing technological advancement, requires some companies to continue to grow their business or provide better services for their customers.This requires providing solutions that are fast and in accordance with the needs and desires of consumers to ensure their satisfaction and loyalty to the goods or services provided.
Electricity is a basic necessity that is used daily.Everyone utilizes "electricity for various functions including lighting, industrial purposes, communication, and other activities.The State Electricity Company (PLN) is the only government-appointed institution responsible for distributing electricity to the entire population of Indonesia nationwide.The State Electricity Company (PLN) must provide the best service to ensure customer satisfaction as a provider of products and services.Customer satisfaction is very important for the existence of a company and plays an important role in shaping the company's positive reputation (Batubara, F et al, 2022).
The State Electricity Company (PLN), a State-Owned Enterprise (SOE), is authorized by the government to oversee all aspects of electricity in Indonesia.As a tangible proof of its concern for consumers, PLN launched the PLN Mobile application that can be accessed via smartphone.The application was launched on October 16, 2016 by the PLN Board of Directors to coincide with the commemoration of the 71st National Electricity Day.This research is categorized as associative research that examines causal relationships.Associative techniques are used in this context to explore the relationship between observed variables to ascertain the existence of causality or causal relationships.This study aims to determine whether changes in one variable have a direct impact on changes in other variables.(Sugiyono, 2019 as cited in Hermawan, T.F., 2020).
The research was conducted in Teluk Betung District, especially for customers The State Electricity Company (PT PLN ULP Teluk Betung).The research was conducted from September 22 to December 4, 2023.

Population and Samples
The population is focused on customers of The State Electricity Company (PT PLN ULP Teluk Betung) who utilize the PLN Mobile application in Teluk Betung District, totaling 32,632 customers.The sampling methodology used is Cluster Random Sampling, which is used to select samples from large and diverse populations such as in countries, provinces, or districts.380 respondents were obtained as a sample based on calculations using the Krejcie & Morgan formula.
The calculation formula is as follows :

Data Analysis Methods and Techniques
The analysis methods used are Validity Test, Reliability Test, and Classical Assumption Test.Data analysis includes Multiple Linear Regression, Coefficient of Determination (R2), and Correlation Analysis.The t test is used for partial hypothesis testing, while the F test is used for simultaneous hypothesis testing.
Multiple linear regression analysis was performed to assess the relationship between the dependent variable and the independent variable using multiple linear regression models.Data was analyzed using SPSS software version 25  Based on Table 2, it shows that the highest score is achieved by item X2.1 with an efficiency indicator.This states that the quality of service in the PLN Mobile application is considered efficient in providing convenience for customers.Based on Table 3, it shows that the highest score is achieved by item Y1.1 with the indicator of conformity of expectations.Thus, it is concluded that customer satisfaction has been fulfilled by matching the expectations of The State Electricity Company (PT PLN ULP Teluk Betung).consumers.

a. Validity Test
Sugiyono (2017: 125) defines the validity test as a measure of how close the data collected from the research subject is to the actual data.This validity test is designed to evaluate the accuracy and reliability of data obtained from research, especially from measuring instruments such as questionnaires.Source: SPSS 25 processed data, 2023 Table 4 shows the correlation coefficient value, namely 7 statements relating to the promotion variable (X1), 10 statements for the electronic service quality variable (X2), and 6 statements for the customer satisfaction variable (Y), all of which show a calculated r value greater than the r table (0.2353), so it can be concluded that the data is valid.

b. Reliability Test
Reliability testing assesses the consistency of measurement findings obtained from the same object, resulting in similar data (Sugiyono, 2017: 130).Source: SPSS 25 processed data, 2023 In table 5, all statements related to promotion variables, electronic service quality, and customer satisfaction have a Cronbach's Alpha (α) value greater than 0.60.Each statement item in this study is considered to have good reliability and is considered suitable for research purposes.

Classic Assumption Test
Classical assumption testing is an important stage in multiple linear regression analysis using the Ordinary Least Square (OLS) method.OLS involves one dependent variable and several independent variables.Ghozali (2018: 159) states that to evaluate the suitability of the model, it is necessary to test many classical assumptions such as normality, multicollinearity, and heteroscedasticity.

a. Normality Test
The normality test assesses whether the residuals in the regression model are normally distributed.A normal distribution of the residual data indicates a high quality regression model.The normality distribution of residuals can be assessed using the Kolmogorov-Smirnov (K-S) non-parametric statistical test provided in the SPSS software.Data is considered to follow a normal distribution if the significance value of the test results exceeds 0.05.(Ghozali, 2018: 161-167).

Source: SPSS 25 Processed Data, 2023
The significance value from table 6 of 0.30 shows greater than 0.05.Therefore, it can be concluded that the data is normally distributed.

b. Multicollinearity Test
The multicollinearity test assesses whether there is a correlation between independent variables in a regression model.An ideal regression model shows no relationship between independent variables and has no symptoms of multicollinearity.Identification of multicollinearity symptoms involves monitoring the Variance Inflation Factor (VIF) and Tolerance levels.Tolerance measures the amount of variability of a variable that is not accounted for by other independent variables.The symptoms of multicollinearity are indicated by a VIF score below 10.00 and a Tolerance value above 0.10 (Ghozali, 2018: 107).

Source: SPSS 25 processed data, 2023
The data in table 7 shows the VIF value is below 10 and the tolerance value exceeds 0.1.Therefore, it can be concluded that there are no signs of multicollinearity in this study.

c. Heteroscedasticity Test
The heteroscedasticity test is conducted to assess whether there is a variation in residual variance between different observations in the regression model (Ghozali, 2018: 120).This test can be done by looking at the scatterplot graph between SRESID and ZPRED to find out if there is a special pattern.Decisions are made based on the following criteria: 1. Identifying a consistent wave pattern or variation in the width of the residual distribution over time in the scatter plot indicates the presence of heteroscedasticity.2. If the scatterplot displays a random distribution of dots above and below the 0 value on the Y axis without a visible pattern, then it indicates the absence of heteroscedasticity" (Ghozali, 2018: 137-138).

Figure 2. Heteroscedasticity Test Source: SPSS 25 processed data, 2023
From the scatterplot graph shown in Figure 2, it can be concluded that the data is randomly scattered above and below the 0 (zero) value on the Y-axis, and there is no consistent pattern in the distribution of the data.Therefore, it can be concluded that there is no heteroscedasticity in the regression equation model.

Hypothesis Testing a. F-Test
Sugiyono (2014: 96) states that the F test is used to assess the collective impact of independent variables.A model is considered feasible if the F significance value is less than or equal to the alpha level of 0.05.

Source: SPSS 25 data processing results, 2023
The significance value of the effect of Promotion (X1) and Electronic Service Quality (X2) on Customer Satisfaction is 0.000, which is less than 0.05.The estimated F table value of 37.882 is greater than the F table value of 3.20 as shown in Table 8.The Nol Hypothesis (Ho3) is rejected and the Alternative Hypothesis (Ha3) is accepted, indicating that there is an influence of Promotion (X1) and Electronic Service Quality (X2) on Customer Satisfaction (Y).

b. T-Test
Sugiyono (2014: 213) explains that the T test is used to test hypotheses regarding the relationship between two or more variables in the presence of controlled variables.If the significance value is less than 0.05 and the regression coefficient is in accordance with the hypothesis, the hypothesis is accepted.

Multiple Linear Regression Analysis
Sugiyono (2014: 277) states that multiple regression analysis is used to anticipate how the dependent variable will behave when two or more independent variables are used as predictors.In this research, multiple linear regression tests were used to assess how the independent variables (promotion and electronic service quality) affect the dependent variable (customer satisfaction).From the results of table 10, the multiple linear regression equation is obtained as follows : Y = 2,892 + 0,264X2 + 0,350X2 + e Based on the multiple linear regression equation, when Promotion and Electronic Service Quality are both zero, the average Customer Satisfaction is estimated at 2,892 units.The regression coefficient of each independent variable is positively correlated with Customer Satisfaction, indicating a unidirectional relationship between Promotion, Electronic Service Quality, and Customer Satisfaction.

a. Correlation Coefficient (R)
Correlation coefficient analysis assesses the direction and degree of relationship between two or more variables.The direction of the relationship can be positive or negative, and its strength is determined by the correlation coefficient value (Sugiyono, 2018).
The correlation coefficient (r) measures the degree of correlation between the independent and dependent variables.The value of the correlation coefficient ranges from -1 to +1, giving rise to several possibilities: a.A positive sign indicates a positive correlation between the evaluated variables, indicating that any change in the value of one variable is related to a change in the other variable.b.A negative sign indicates a negative correlation between variables, where an increase in one variable results in a decrease in the other variable, and vice versa.An r result close to -1 or equal to -1 indicates a weak negative correlation between the variables under study.c.If the r value is 0 or around 0, it means that the correlation between the variables studied is weak or nonexistent.

b. Coefficient of Determination (R2)
The coefficient of determination (R2) assesses how well the model is able to account for variations in the dependent variable.The coefficient of determination ranges from 0 to 1.A lower value indicates that the model has little explanatory power for variations in the dependent variable, while a value close to 1 indicates that the independent variable is the main source of information for predicting variations in the dependent variable (Ghozali, 2018: 97).The determination analysis in this study tries to evaluate the extent to which independent factors can cause variations in the dependent variable.

Source: SPSS 25 data processing results, 2023
Table 11 shows a correlation coefficient of 0.786 between the independent and dependent variables.The positive correlation coefficient indicates that there is a significant and one-way correlation between the variables Promotion and Electronic Service Quality with Customer Satisfaction, this indicates that the greater the value of the independent variable, the value of the dependent variable also increases.The Adjusted R2 value of 0.617 means that 61.7% of the variation in the dependent variable can be explained by the independent variables evaluated.The remaining 38.3% is caused by additional factors not included in this research.

Discussion Of The Research
The F test results explain that Promotion and Electronic Service Quality have a simultaneous influence on Customer Satisfaction.Effective advertising and high quality services on the PLN Mobile Application lead to increased customer satisfaction at PT PLN (Persero) ULP Teluk Betung.This finding is in line with research conducted by Gloria Ribka Lengkey and Silvya L. Mandey in 2022 on the Effect of Promotion and Electronic Service Quality on PLN Mobile Application on Customer Satisfaction of PT PLN (Persero) ULP Tomohon.This research shows that promotion and electronic service quality are important factors in increasing customer satisfaction.
The results of the multiple linear regression test show that the linear regression coefficient of promotion has a positive effect on the level of customer satisfaction of PT PLN (Persero) ULP Teluk Betung.Therefore, it can be concluded that the H1 hypothesis is supported, which states that the promotion regression coefficient in the PLN Mobile application has a significant effect on customer satisfaction at PT PLN (Persero) ULP Teluk Betung.Fatimah Batubara's research (2022) on "The Effect of Electronic Service Quality, PLN Mobile Application Promotion on Customer Satisfaction of PT PLN (Persero) ULP Sibuhuan" is in line with these findings, showing that promotion has a significant impact on customer satisfaction.This study revealed a favorable and significant correlation between e-service quality and customer satisfaction.Higher electronic service quality causes customer satisfaction to increase, while lower service quality causes customer satisfaction to decrease.This research is in line with Fadillah's 2017 research on the Effect of Electronic Service Quality, Customer Value, and Trust on Consumer Satisfaction.The results show that electronic service quality has a significant impact on customer satisfaction. EM-2024-5936

Conclusions And Advice Conclusions
Conclusions can be drawn from the results of the study and analysis.Individually, promotion has a major influence on customer satisfaction in using the PLN Mobile Application.Promotion can increase customer service awareness directly leading to higher customer satisfaction.Second, the quality of electronic services has a major impact on customer satisfaction of PLN Mobile application users.This shows that the quality of electronic services has a significant impact on consumer perceptions and satisfaction.Third, the F test results show that the independent variables of promotion and electronic service quality together have a considerable influence on the dependent variable of customer satisfaction.Effective promotion combined with strong e-service quality can have a major impact on overall customer satisfaction.It is important for companies to not only prioritize promotions but also improve the quality of electronic services to optimize customer satisfaction when using the PLN Mobile application.

Advice
The research findings provide recommendations for PT PLN ULP Teluk Betung to improve service quality and customer satisfaction with the PLN Mobile application.Efforts made must focus on expanding the scope of promotion through increased innovation in the Teluk Betung area.This is intended to increase customer knowledge of the PLN Mobile application, with the hope that it can have a positive influence on the level of customer satisfaction.In addition, companies need to consistently improve the quality of electronic service applications.Companies can improve service quality and adapt to future customer demand by consistently updating and improving their operations.It is recommended to conduct additional studies that are more thorough and detailed.This study shows that about 61.7% of other variables affect customer satisfaction with the PLN Mobile application.
Additional research is needed to gain a deeper understanding of these aspects, therefore allowing the company to implement more effective strategies to improve overall customer satisfaction.The implementation of such suggestions aims to help The State Electricity Company (PT PLN ULP Teluk Betung) improve its performance and services in the ever-evolving era of electronic services.
. T The regression equation used in the investigation is as follows:

4. Research Results And Discussion Research ResultsTable 1
It is suspected that the Quality of Electronic Services has a partial influence on Customer Satisfaction of PLN Mobile Application users of The State Electricity Company (PT PLN ULP Teluk Betung).H-3 : It is suspected that Promotion and Electronic Service Quality have a simultaneous influence on Customer Satisfaction of PLN Mobile application users The State Electricity Company (PT PLN ULP Teluk Betung).
EM-2024-5929Conceptual FrameworkFigure.1 Conceptual Framework H-1 : It is suspected that Promotion has a partial influence on Customer Satisfaction of PLN Mobile Application users of The State Electricity Company (PT PLN ULP Teluk Betung).H-2 :

Table 3 .
Y Data Tabulation

Table 5 .
Reliability Test

Table 8 .
F-Test Results

Table 9 .
T-Test ResultsBased on the calculation results from table 9, the result is obtained : 1.The t value of the Promotion variable (X1) of 3.012 is more than the t table value of 2.012 at a significance level of 0.004 <0.05.The zero hypothesis (Ho) is rejected, this shows that Promotion (X1) has a significant effect on Customer Satisfaction (Y) so that the alternative hypothesis (Ha) is accepted. 2. The calculated t value of the Electronic Service Quality variable (X2) of 4.742 exceeds the t table value of 2.012 at a significance level of 0.000 <0.05.This indicates the rejection of the zero hypothesis (Ho) that Electronic Service Quality has a significant effect on Customer Satisfaction (Y), so that the alternative hypothesis (Ha) is accepted.

Table 10 .
Multiple Linear Regression