THE EFFECT OF PACKAGE SERVICE QUALITY ON CUSTOMERS SATISFACTION (Studies on Customers of Jemur Andayani Post Office, Surabaya City)

This research is motivated by the increasing number of package delivery services other than the post office which results in intense competition. While the object chosen in this study is the customer of the Jemur Andayani Post Office, Surabaya, where there has been a decrease in the level of package delivery at the Jemur Andayani Post Office and an increasing number of competitors. The purpose of this research was to determine the influence of service on satisfaction at Jemur Andayani Post Office. After literature review and formulating hypotheses, data were collected through quantitative methods using a questionnaire to 100 customers of the Jemur Andayani Post Office. This research uses analytical methotd is simple linear regression analysis. The results of the hypothesis test show that the t value is 25.249. T value (25.249)> t table (1.660), then Ho rejected and H1 accepted. So there is a significant influence between package service quality on satisfaction at the Jemur Andayani post office, Surabaya.


A. INTRODUCTION
BUMN is one of the actors in economic activities that has a very important role in the implementation of the national economy of the Indonesian state which aims to realize the welfare of the community as referred to in 1945 Constitution. PT Pos Indonesia has a role that also assists in the implementation of the country's economy, namely in the field of delivery services.
As the only state-owned company that provides general services in the postal service sector, many people depend on PT Pos Indonesia to help deliver their letters and packages. Public enthusiasm in sending letters, documents and goods in the 1980s-1990s using the services of PT Pos Indonesia was very high, plus at that time PT Pos Indonesia did not have competitors like it does today (Medan Bisnis Daily, 2016). This period was known as the heyday of PT Pos Indonesia. Entering the 2000s, PT Pos Indonesia experienced a setback due to the presence of mobile phones and the internet. In addition to the emergence of mobile phone companies, PT Pos Indonesia also received new competition, namely private shipping service companies and the emergence of innovations made by the Bank, namely ATMs.
In an era of increasingly fierce business competition, coupled with the high enthusiasm of consumers for goods delivery services, there are opportunities for entrepreneurs. Currently, many private companies in the shipping service sector are competing with PT Pos Indonesia, such as TIKI, JNE, SiCepat Ekspres, FedEx / RPX, TNT, DHL, UPS, and many more. These companies provide excellent service, through express service between regions and even across countries in just a matter of days, guarantees directly to the recipient, guarantee goods and of course at affordable prices.
According to data from the Top Brand Index in 2020, market control is shown in the following Jasa Pengiriman Lain 29 % Source: TOP Brand Index 2020 Seeing from the above data PT Pos Indonesia only controls the market by 8% and the largest market share was JNE at 27%. PT Pos Indonesia is a stateowned company that should be the benchmark for other private shipping companies. But in fact, PT Pos Indonesia ranks 4th not first. PT Pos Indonesia should pay attention to this to analyze shortcomings and further improve the quality of their services.
The Jemur Andayani Post Office is one of the major post offices in Surabaya. The post office serves the delivery of letters and goods in the South Surabaya area. The author is interested in researching the Jemur Andayani Post Office, Surabaya City because as one of the major post offices in Surabaya, the Jemur Andayani Post Office also experiences the impact of competition between shipping service companies and the impact of increasingly advanced technology. This impact causes the volume of domestic shipments to fluctuate in the Jemur Andayani Post Office. The graph above shows a decrease in the number of packages from 2018 to 2020. For this reason, the Jemur Andayani post office is required to have more value in facing competition, namely through improving the quality of its services. One of the causes of public dissatisfaction is the lack of maximum service quality in delivering delivery services. To be able to realize good service quality to the community as a whole, every company must be able to increase the work productivity of its employees so that it can provide good service to the community. Thus, the community will feel satisfied with the services provided by a company. With an increase in the quality of services provided, of course, satisfaction will also increase (Sumertana, 2016).

B. LITERATURE REVIEW a. Service Quality
According to Tjiptono, Chandra and Adriana in Rofiah & Wahyuni (2017), in simple terms, quality can be defined as a defect-free product, in other words the product is in accordance with standards (target targets or requirements that can be defined, observed and measured) . Meanwhile, according to Sugiarto in Prasastono & Mukti (2005) quality is a condition related to the appearance of products, services, people, processes, and the environment that meet or exceed customer expectations. While service is something that is done to meet the needs of other people or customers, the level of satisfaction can only be felt by the officers serving and the customers being served.
Zeithaml et al in Prabawa & Noviari (2012) explained that service quality is the measurement result of the overall value of a good service level. Based on the aforementioned definitions, it can be concluded that quality of service is an assessment of a product or service that is in accordance with what is expected or desired by the customer or user.

b. Dimensions of Service Quality
Parasuraman, Zeithaml, and Berry in Kresnamurti & Sinambela (2011) has mentioned that there are five dimensions of service quality used by customers in evaluating or assessing service quality. The five dimensions include: 1. Tangibles (direct evidence), is physical evidence of a company in showing their existence to outsiders. The appearance, ability, and physical facilities and infrastructure of the company are clear evidence of the services provided by the company 2. Reliability, is the ability to provide promised services in a timely, accurate, and satisfying manner. 3. Responsiveness (responsiveness), is the desire of staff to help customers and provide responsive service. 4. Assurance (assurance of certainty), including knowledge, ability, politeness, and trust possessed by staff. 5. Emphaty (empathy), which includes ease in establishing relationships, good communication, personal attention, and being able to understand customer needs.

c. Public Satisfaction The
Word satisfaction (satisfaction) comes from the Latin static which means good enough and and facio which means doing or making. Therefore, satisfaction is then defined as an effort to fulfill something or make something good enough. Noviyanti (2020) explains that satisfaction is a post-consumption assessment, namely that a selected product can meet or exceed consumer expectations, thereby affecting the decision-making process for repurchasing the same product.
Philip Kotler in Alvioletta, Setyawan, & Saputra (2020) explained that satisfaction arises from feeling happy or disappointed after comparing a product or service from what they think with what they expect. In other words, satisfaction will be high if customers/consumers are satisfied with the service they receive. Likewise, if the customer/consumer is not satisfied or disappointed with the service received, their satisfaction level will be low.

d. Hypothesis
H1: There is influence between service quality and satisfaction package to Office Jemur PostAndayani Surabaya Ho: There is no influence between service quality and satisfaction package to Jemur Andayani Post Office Surabaya

C. METHOD a. Research Design
This research is a quantitative explanatory type. Sugiyono (2018) explains that the quantitative method is a The research method used to examine a specific population or sample through data collection using research instruments then perform quantitative / statistical data analysis with the aim of describing and testing the predetermined hypotheses. Meanwhile, explanatory research is a design used to test the hypothesized relationship between variables (Mulyadi, 2011).

b. Research location
The location is chosen by the researcher was at the Jemur Andayani Surabaya Post Office. The reason the researchers chose this location was because it was in accordance with the research objectives, namely to find out whether there is an effect of service quality on satisfaction in the shipping service sector at the post office. c. Operational Definition of Variables 1. Free Variables (X) Independent variables are variables that affect or variables that cause changes or the emergence of the dependent variable (Sugiyono, 2018). The independent variable in this study is the quality of package services provided by the Jemur Andayani Surabaya Post Office. The dimensions and indicators in this variable can be seen in the table below :

Table 2. Dimensions and Indicators of Service Quality (Variable X)
Source: Zeithaml, Berry and Parasuraman in (Agustina, 2019)

Bound Variables (Y)
Sugiyono (2018) states that the dependent variable is a variable that is influenced or is the result of the independent variable. The independent variable in this study is satisfaction. The dimensions and indicators for this variable can be

d. Pre-Analysis 1. Validity Test
The validity test is a test used to measure the correlation coefficient between the score of the question or indicator being tested and the total score on the variable. To determine whether an item is fit for use or not to be used in a study.

No
Dimensions Indicator 1 Tangibles 1. Satisfaction with the appearance of officers in serving 2. Satisfaction with the comfort of the place and completeness of tools 3. Satisfaction with ease process and service access 2 Reliability 1. Satisfaction with the accuracy of officers in serving 2. Satisfaction with the clarity of service standards 3. Satisfaction with the ability of officers to use tools in the service process 3 Responsiveness 1. Satisfaction with officers' responses 2. Satisfaction with the accuracy of officers 3. Satisfaction with the response of officers in response to complaints 4 Assurance 1. Satisfaction with guarantees on time in service 2. Satisfaction with legality assurance in services 3. Satisfaction with guaranteed costs in service 5 Emphaty 1. Satisfaction with customer interests first 2. Satisfaction with friendly and polite attitudes officer 3. Satisfaction with officers' nondiscriminatory attitudes and respect for officers The significance test of the correlation coefficient is at a significance level of 0.05 (5%), which means that an item is considered valid if it is significantly correlated with the total score of the item. (Herlina, 2019). If r count is greater than or equal to r table (two-sided test with sig. 0.05 or 5%) then the question item has a significant correlation with the total score or is declared valid. In this study, the analysis of the validity of the questionnaire was carried out using the Pearson correlation test and using the assistance of the SPSS version 20 application.

Reliability Test
Test of the instrument was carried out by analyzing through internal consistency, by testing the instrument only once, then the data obtained were analyzed with certain techniques. To calculate the rebility of the data obtained through internal consistency analysis, the authors used Cronbach's alpha. Analysis of questionnaire data for reliability testing in this study using SPSS version 20.

Normality Test
The purpose of doing this normality test is to find out whether the distribution of data in the variables used has a normal distribution or not. Data that is normally distributed means that the data has normal data distribution in the sense that the data used can represent a population (Herlina, 2019).
The normality test of this study used the Kolmogorov-Smirnov test. In the Kolmgorov Smirnov test, a comparison is made between the distribution of data (data to be tested for normality) or commonly called a Kolmogorov count with a standard normal distribution or what is commonly called a Kolmogorov table. If the Kolmgorov count is smaller (<) than the Kolmogorov table, the decision is normally distributed sata. Conversely, if the Kolmogorov count is greater (>) than the Kolmgorov table, the data is not normal. Analysis of the questionnaire data for the normality test in this study used the SPSS version 20 application.

Linearity Test
This test is performed as a step in the regression test. The requirement for decision making in the linearity test is that if the two variables have a significance value greater than 0.05, it can be said that the two variables are linear. From this explanation, it can be concluded that the linearity test is used to determine whether two variables have a significant linear relationship or not. Analysis of questionnaire data for linearity testing in this study using the help of the SPSS version 20 application. e. Data Analysis Techniques

Correlation Test
Before conducting a regression test, the first step that must be taken is to test the correlation to find out the relationship between variables. The formula used by researchers to determine the relationship between variables is the Spearman Rho correlation test. The formula for the Spearman correlation coefficient can be seen below: Where: rs atau = rank correlation coefficient d = rank difference between X (RX) and Y (RY) n = number of rank pairs To determine the significance or Whether or not the Rho coefficient is looking for, then the t test can be used with the following conditions: Where : r s = rho correlation coefficient n = number of samples

Simple Regression Test
After conducting a correlation test to determine the relationship between variables, the next step is to conduct a regression test to determine the effect on these two variables. In this study, the regression test used was the Simple Linear Regression test. The researcher used a simple linear regression test because this study only used two variables, namely one dependent variable and one independent variable. The simple linear regression equation can be formulated as follows: The values of a (intercept / constant) and b (regression coefficient) can be calculated with the following formula:

Conditions:
Ho received and H1 rejected if t is smaller (<) than t table Ho rejected and H1 accepted if t is greater (>) than t table

D. EXPLANATION 1. Pre-analysis Test Results 1) Validity Test
In this study, the analysis of the validity test used SPSS application version 20. Questionnaire testing was conducted on 28 respondents with two items of statements for each indicator, so that the number of statement items tested was 60 items.
In the Pearson correlation test, to find out whether the results show a significant relationship or not, the calculated r value is compared with the r table. If r count is greater than r table then the result will show significant, and vice versa if r count is smaller (<) than r table then the result is not significant. To determine the r table, which is to determine the value of the degrees of freedom (df) first by using the formula df = N -2 (Herlina, 2019). Then the value of df = 28-2 or df = 26. With the significance level used is 0.05 or 5%, the r table is 0.3739 or 0.374. After finding the df value, the next step is to analyze the validity test for the variable service quality and satisfaction. Following are the results of the analysis of the questionnaire validity test for the quality variable (X). ,875 Valid Source: questionnaire data that has been processed.
From the table above, it can be seen that of the 30 statement items tested, all of them were valid. Valid because r count all statements greater (>) than r table. Because all statement items are declared valid, only one statement item will be used for each indicator. While the results of the analysis of the validity test of the satisfaction variable are shown in the following table. ,884 Valid Source: processed questionnaire data Of the 30 items tested, all items got valid results. All statements have a calculated r value that is higher than r table. Of the 30 valid statements, only 15 statement items were used in the questionnaire for satisfaction variables.

2) Reliability Test
This study uses the Cronbach's Alpha reliability test method. The results on the reliability test are then matched with the reliability level table which includes the following categories: a) The result of Cronbach's Alpha is less than 0.6, it means that the reliability is bad b) The results of Cronbach's Alpha are between 0.6 -0.79, it means that the reliability is acceptable c) The result of Cronbach's Alpha is greater than 0.6, it means that the reliability is good Analysis of questionnaire data for reliability testing in this study using the SPSS version 20 application. The data used are the same as the data in the validity test that has been done previously. With the same respondent and with the same statement items. Below are the results of the analysis to test the reliability of the questionnaire for the package service quality variables and satisfaction variables. Cronbach's Alphas is 0.985 so it can be concluded that the questionnaire for the two variables is declared to have Reliability Good in accordance with the reliability level of Cronbach's Alpha. previously described.

3) Normality Test
In this study, the normality test was performed statistically using the Kolmogorov-Smirnov test. In the normality test, the data used is the residual value, not the value of the indicator item. After the residual value is found, the Kolmogorov-Smirnov normality test can be performed. A data can be said to be normally distributed or not, it can be searched using the following standards: a) If the Asymp.Sig value obtained is greater than 0.05, the data is normally distributed b) If the Asymp.Sig value obtained is less than 0.05, the data is not normally distributed.
The results of the normality test carried out using the SPSS version 20 application are as follows. ,830 a. Test distribution is Normal. b. Calculated from data. Source: processed questionnaire data In the table above, the Asymp.Sig value obtained is 0.830, which means that the questionnaire data is normally distributed because it is > 0.05.

4) Linearity Test
The linearity test that is carried out has the aim of knowing whether there is a significant linear relationship or not between the two variables being tested. This test is usually used as a prerequisite in correlation or linear regression analysis (Herlina, 2019). Guidelines for drawing conclusions for the linearity test and the meaning of the regression direction are as follows.
For the regression direction significance test, what must be considered is the sig.linearity value. If the sig.linearity value obtained is less than 0.05, the relationship between the independent variable and the dependent variable has meaning. However, if the sig.linearity value is> 0.05, the relationship between the two variables is meaningless. For the linear test what we have to pay attention to is the sig value. linearity value. If the value is sig. The linearity value obtained is greater than 0.05, so the direction of the regression from the independent variable to the dependent variable is linear. However, if the value is sig. linearity value is less than 0.05, so the direction of the regression from the independent variable to the dependent variable is not linear.From the linearity test that was carried out using the SPSS version 20 application,obtained results wereas follows Within Groups 65,667 7 9,381 Total 7101,857 27 Source: questionnaire data which has been processed From the table above, Sig. Linearity obtained a value of 0.000 <0.05, which means that between the independent variable and the dependent variable is meaningful. As for Sig. Deviation from Linearty obtained a value of 0.233> 0.05, which means that the direction of the regression from the independent variable to the dependent variable is linear.

1) Correlation Test
Data analysis is the most important part of a study. Data analysis was carried out to help answer the objectives of the study and to prove the truth of the proposed research hypothesis. The purpose of this study was to determine whether or not there is an effect of package service quality on satisfaction at the Jemur Andayani Post Office, Surabaya City.
This study uses the Spearman Rho Correlation Analysis. Spearman Rho Correlation Analysis is used to measure the degree or closeness of the relationship between two ordinal scale variables, as well as interval / ratio data that has been converted into ordinal data (Siswanto & Suyatno, 2018). Thus, Spearman Correlation Analysis is used to determine the effect of Service Quality (Variable X) and Satisfaction (Variable Y). The formula for the Spearman correlation coefficient is Or Where : r s or = rank correlation coefficient d = rank difference between X (RX) and Y (RY) n = number of rank pairs Spearman Correlation Analysis Testing in this study uses assistance from the Statistical Package for Social Science (SPSS) application version 20. Following are the results of testing the Spearman Correlation Analysis using SPSS version 20 Sig. (2-tailed) ,000 . N 100 100 **. Correlation is significant at the 0.01 level (2-tailed). Source: processed questionnaire data From the above test results, several results can be obtained, namely: 1. The significance of the relationship between Service Quality and Satisfaction variables. Based on the output above, the significance value or Sig. (2-tailed) is 0,000. Because of Sig. (2-tailed) 0,000 is less than 0.05, meaning that there is a significant (meaningful) relationship between Service Quality and Satisfaction variables.

The level of strength (closeness) of the Variable Relationship between Service Quality and Satisfaction
The result that can be seen from the output above is the correlation coefficient value of 0.893 **, which is the level of strength of the relationship between the Service Quality and Satisfaction variables of 0.893 or the correlation is very strong.

Direction (Type) of Relationship between Service Quality Variables and Satisfaction
The correlation coefficient value obtained in the results above is positive, namely 0.893. So that the relationship between the two variables is unidirectional (type of unidirectional relationship). Thus it can be interpreted that if the quality of service is improved, satisfaction will also increase.

2) Simple Regression Test
After conducting a correlation test to find out the relationship between variables, the next step is to conduct a regression test to find out the effect of these variables. In this study, the regression test used was the Simple Linear Regression test with the help of the SPSS version 20 application. The following are the results of the simple regression test. Anova table shows the influence of the two variables. If the significance value shows a number less than 0.05, the variable X / can be used to predict variable Y or in other words, there is an influence between the two variables. The table above shows a significance value of 0.000 which is smaller than 0.05. This means that there is a variable influence of Service Quality (X) on Satisfaction (Y). Meanwhile, the value of the regression coefficient is 0.943. The simple regression equation formula is Y = a + bX. Where Y is the predictable dependent variable, a is a constant value, b is the value of the regression coefficient and X is the independent variable. Then the calculation results when entered into the formula become: Y = 2.893 + 0.943X. This means that if the value of service is 0, then satisfaction is worth 2.893. Meanwhile, if the Customer Quality has increased by one unit, then satisfaction will also increase by 0.943 units.

3) Hypothesis Testing
To test the research hypothesis regarding the effect of service quality on satisfaction, the following formula is used:

Disscusion
from the results of the recapitulation of the respondents' answers regarding the Quality of Service Packages on Satisfaction, all dimensions scored for either category. This is because the quality of service provided by the Jemur Andayani Surabaya Post Office is good. Meanwhile, there is no dimension of service quality that gets a bad score. This means that the services provided and provided to customers are good.
To recapitulate the results of respondents' answers regarding satisfaction (Variable Y), the dimension that gets a very good category score is empthy. Meanwhile, the other four dimensions get good categories. This shows that the customer is very satisfied with the empathy shown by the officer attitude when providing package delivery services.
From the results of the Sperman correlation test, it can be seen that the significance value is smaller than (<) 0.05, which means that there is a significant (significant) relationship between Service Quality and Satisfaction variables. Meanwhile, the level of strength of the relationship between the Service Quality and Satisfaction variables is 0.893, which means that the two variables have a very strong correlation.
In a simple regression test, the variable service quality (X) affects satisfaction (Y). The significance result shows the number 0.000 which is smaller than 0.05. This means that there is a variable influence of Service Quality (X) on Satisfaction (Y). To test the hypothesis using the t test, where the result of t arithmetic is greater than (>) t table, so that H o is rejected and H 1 is accepted. So there is a significant influence between the quality of the service package on satisfaction. This supports the research results (Sumertana, 2016). which states that service quality and satisfaction have a relationship, namely with the increase in service quality, satisfaction will also increase. So that to increase satisfaction must pay attention to the quality of services.

E. CONCLUSION
The results of the Spearman Rho correlation test obtained several results. First, the significance value obtained is 0.000 which means that there is a significant relationship between Service Quality Variables and Customer Satisfaction. The second result is that the correlation coefficient is 0.893, which means that the level of strength of the relationship between service quality variables and customer satisfaction is very strong. And the third result is that the correlation coefficient number obtained is positive, which means that if the quality of service is improved, customer satisfaction will also increase.
The results for simple regression testing are obtained a significance value smaller than 0.05, which is equal to 0.000, which means that there is an influence between the service quality variable (x) on customer satisfaction (y). While the results of hypothesis testing are obtained t count of 25.249 while for t table the value is 1.660. Thus it can be interpreted that t is greater (>) than t table, then H0 is rejected and H1 is accepted. So it can be concluded that there is a significant influence between service quality on customer satisfaction.