Analyze The Effect of Service Quality, The Role of Social Media Technology, and Company Reputation On Increasing Power Sales

ABSTRACT


Introduction
PT PLN (Persero) is an electricity SOE that continues to be committed and innovate to carry out a big mission to illuminate and move the country (Prabu Mangkunegara, 2015).Having a vision to become the leading power company in Southeast Asia, PLN is moving to become the customer's number one choice for Energy Solutions.PLN as a monopoly SOE (sole provider) in the field of electricity services, but the trend of electricity sales performance is still stagnant and does not grow significantly in 2022 (Amudha, Motha, Alamelu, Nalini, & Srinivasan, 2017).Electricity sales in 2021 were recorded at 257.63 TWh or grew 5.77% compared to 2020 which was recorded at only 243.58 TWh or grew minus 0.79% compared to 2019.Of course, minus growth in 2020 is understandable considering that at that time there was an outbreak of the Covid-19 pandemic (Rao, Rao, Krishna, & Krishna, 2004).However, since the new normal era in 2021, electricity sales in 2022 were in fact only recorded at 270.82 TWh or only grew by 5.12% compared to 2021 (0.65% smaller).This is a condition that needs to be mitigated, because electricity is the basis driving the economic activity of the State.The size / small economic growth of a country is very closely related to the large / small growth of electrical energy (Alhusin, 2013).
The phenomenon that should occur today is a change in people's lifestyles, which previously relied on fuel-based energy to electrical energy, such as: the use of electric/battery-based vehicles, the use of electric electronic devices for cooking, etc.This of course should be a driving factor for increasing electricity consumption (Dessler & Phillips, 2017).In addition, PLN also continues to make various efforts to increase sales of electrical energy by supporting productive activities of the community.One of PLN's efforts is through the Electrifying Agriculture (EA) Program aimed at the agriculture, livestock and fisheries sectors.This program is designed to encourage the use of technology to increase the productivity of farmers or ranchers through the use of electrical energy (Flin, Mearns, O'Connor, & Bryden, 2020).
PLN UP3 Ponorogo as one of the granary areas of Electrifying Agriculture should be one of the regions that can contribute to better growth in electricity sales when compared to other regions (Kuo, Kao, Tang, & Tsai, 2023).
Through this research, we will analyze things that affect the high / low sales of electricity, especially at PLN UP3 Ponorogo, in this case the influence of service quality, the role of social media technology, and company reputation (Kuncoro, 2013).
In accordance with the formulation of the problem above, the goal to be achieved in this study is to know and analyze the effect of service quality on increasing electricity sales at PLN UP3 Ponorogo; Knowing and analyzing the influence of the role of media technology on increasing electricity sales at PLN UP3 Ponorogo; and Know and analyze the effect of company reputation on increasing electricity sales at PLN UP3 Ponorogo?

Research Methods
This research is an explanatory research using hypothesis testing methods and quantitative approaches.The goal is to explain the causal relationship between one variable that affects another variable, namely independent variables in the form of service quality, the role of social media technology and company reputation on the dependent variable that is increased sales (Cooper & Schindler, 2014).
Researchers collect data using survey methods using questionnaires as instruments to obtain data from research subjects in a short time.The survey method is an investigation method carried out on individuals or units simultaneously at the same time, both using samples and censuses (Azwar, 2003).
Population refers to the complete set of elements that are expected to be studied and from which conclusions can be drawn, where elements in the population are individual participants or objects chosen to be investigated.In this study, the population is all PLN UP3 Ponorogo customers.This population is determined according to the purpose of the study, which is to analyze the increase in electric power sales.The sample is a subset of the total target population, and the sample size must be carefully selected to represent the population.After the sample is selected, the researcher needs to determine the characteristics of the respondents, the number of individuals to be interviewed, the selection of events and the number of events to be studied, or the amount of data to be analyzed.The sampling technique used in this study is probability sampling, which is by using a simple random sampling method where every element in the population has the same opportunity to be selected as a sample (Malhotra, Mukhopadhyay, Liu, & Dash, 2012).The sample size for this study was set at 10 respondents.

Overview of PT PLN (Persero) UP3 Ponorogo
PT PLN (Persero) Ponorogo Customer Service Implementation Unit is one of PLN's Implementing Units under PLN East Java Distribution Main Unit.PT.PLN (Persero) has a vision "To become the leading power company in Southeast Asia and the #1 customer choice for energy solutions" (Malhotra et al., 2012).The achievement of this vision will be carried out through four missions, namely running the electricity business and other related fields, oriented to customer satisfaction, company members and shareholders; making electric power a medium to improve the quality of people's lives; strive for electric power to be a driver of economic activity; and carry out environmentally sound business activities (Mathis & Jackson, 2022).

Validity Test Results
Testing the validity of research instruments is carried out to measure the validity or absence of a questionnaire.A questionnaire is said to be valid if it has a correlation coefficient (r) value of ≥ 0.300.The number of respondents in this validity test is 30 samples.The results of the research instrument validity test are presented in Table 1 below (Mondy, Noe, & Mondy, 2015).Based on Table 1, it can be seen that all statement items on the research instrument used to measure the variables of transformational leadership, organizational citizenship behavior, work motivation, and employee performance have a correlation coefficient value greater than 0.300.This means that the statement item is valid and worthy of use as a research instrument (Rijanto, 2010).

Reliability Test Results
Reliability testing of research instruments is carried out to measure the extent to which the questionnaires used in the study are trustworthy or reliable.Reliability tests are performed by calculating Cronbach's Alpha.A construct or variable is said to be reliable if it has a Cronbach's Alpha value of > 0.700.The number of respondents in this reliability test is 30 samples (Sekaran & Bougie, 2017).The results of the reliability test of the research instrument are presented in Table 2 below.Based on Table 4.2 it can be seen that all research instruments have a Cronbach's Alpha coefficient greater than 0.700.This means that all variables have met the requirements of reliability or reliability so that they can be used as research instruments (Tsiotsou & Diehl, 2022).Based on Table 2 it can be seen that all research instruments have a Cronbach's Alpha coefficient greater than 0.700.This means that all variables have met the requirements of reliability or reliability so that they can be used as research instruments (Wulandari, Suratman, & Pahlevi, 2019).

Descriptive Analysis
Based on the data that has been collected, answers from respondents have been recapitulated and then analyzed to find out respondents' research on items Service Quality, the Role of Social Media Technology, Company Reputation and Sales Improvement.This data analysis goes through two stages, namely descriptive analysis and quantitative analysis.The categories of each interval are as follows:

Descriptive Statistics of Service Quality Variables
The following is respondent's assessment of Service Quality:

Descriptive Statistics of Social Media Technology Role Variables
The following is respondents' assessment of the Role of Social Media Technology:

Descriptive Statistics of Company Reputation Variables
The following is respondents' assessment of Company Reputation:

Descriptive Statistics of Sales Increase Variables
The following is respondents' assessment of Increased Sales: Based on the results of the normality test with the Kolmogorov Smirnov Test above, it can be seen that the probability value > 0.05, then the regression model meets the normality assumption.Likewise, when viewed from the diagonal axis of the Normal Probability Plot, the diagram diagram shows the data spread around the diagonal line, so the regression model satisfies the assumption of normality.

Multicollinearity Test
A multicollinearity test is a state in which one or more independent variables can be expressed as a linear combination of other independent variables.One of the assumptions of classical linear regression is the absence of no perfect multicollinearity.A regression model is said to be exposed to multicollinearity when there is a perfect or exact linear relationship between some or all independent variables.As a result, it will be difficult to see the influence of individual independent variables on non-free variables (Ghozali, 2017).The detection of multicollinearity in this study was carried out by the VIF method.Test criteria : If VIF > 5, then Ho is rejected If VIF < 5, then Ho is accepted The results of the multicollinearity test with the VIF method are as follows: This means that all independent variables do not occur multicollinearity, so they do not refract the interpretation of the results of regression analysis.

Heteroscedasticity Test
Homoscedasticity is a situation where the variance (σ2) of the disturbance term is the same for all observations of X. Deviation from this assumption is called heteroscedasticity, that is, if the variance value (σ2) of the non-free variable (Yi) increases as a result of increasing variance of the independent variable (Xi), then the variance of Yi is not the same (Insukindro, 2016: 62).The detection of heteroscedasticity in this study was carried out by the spearman rank method.You do this by looking at the probability value of > 0.05, so it is not exposed to heteroscedasticity (Ghozali, 2017).
The results of the heteroscedasticity test with spearman rank are as follows: Based on the results of the heteroscedasticity test using spearman rank , it can be seen that the probability value > 0.05.This means that the estimated model is free of heteroscedasticity.

Hypothesis Testing Results
Quantitative analysis is an analysis that uses numbers.In this study, the analytical tool used is Multiple Linear Regression Analysis with the aim of determining the influence of Service Quality, the Role of Social Media Technology, and Company Reputation on Increasing Electric Power Sales.

Multiple Linear Regression Analysis
To find out how the effect of Service Quality, the Role of Social Media Technology, and Company Reputation on Increasing Power Sales is used Multiple Liniear Regression Test, with results as shown in the following table.The results of regression with the OLS method obtained R2 (Coefficient of Determination) of meaning that the variable of Sales Increase can be explained by system variables Service Quality, Role of Social Media Technology, and Company Reputation simultaneously by 58.9%, while the remaining 41.1% is explained by other variables outside the model.

Conclusion
Based on the discussion in the previous chapters and answering the problem formulation, research objectives and referring to the process and results of data analysis in this study, the following conclusions can be drawn: There is a positive and significant influence between service quality and increased electricity sales at PLN UP3 Ponorogo.
There is a positive and significant influence between the role of social media technology and the increase in electricity sales at PLN UP3 Ponorogo.
There is a positive and significant influence between the company's reputation and the increase in electricity sales at PLN UP3 Ponorogo.

Table 8 Respondents' Assessment of Sales Increase
The normality test aims to test whether in the regression model the dependent variable and the independent variable have a normal distribution or not.A good regression model is to have a normal or near-normal data distribution (Ghozali, 2017).To test normality, you can analyze by looking at the probability value.The basis for decision making is that if the probability value is >0.05, then the regression model satisfies the assumption of normality.The results of the normality test with the Kolmogorov Smirnov Test are as follows:

Table 12 Multiple Linear Regression
Based on the results of multiple linear regression tests between independent variables, namely, Service Quality, the Role of Social Media Technology, and Company Reputation on Increasing Power Sales, the regression equation can be arranged as follows: Based on the results of data analysis and regression equations, it can be concluded about the following: a.A constant value of 7.729 indicates the pure value of the variable Increase in Sales (Y) without being influenced by independent variables; b.The regression value (β1) of Service Quality of 0.603 indicates that there is a