ANALYSIS OF THE EFFECT OF CUSTOMER SATISFACTION ON PURCHASE DECISIONS AT COFFEESHOP"SELASA_COMMUNA" MEDAN

This study aims to analyze how far the relationship between customer satisfaction and purchasing decisions for customers of the selasa_communa coffee shop. In this study, purposive sampling with certain criteria amounted to 40 customers. The data collected uses a scale from customer satisfaction and purchasing decisions. Data were analyzed using simple regression analysis. The results showed a significant positive relationship between customer satisfaction and purchasing decisions for consumers at the selasa_communa coffee shop. In this study, customer satisfaction who have purchased at the selasa_communa coffee shop can be used as a stimulus for prospective customers in making purchasing decisions.


INTRODUCTION
The Minister of Cooperatives and SMEs (MenKopUKM) Teten Masduki said that the coffee commodity had driven the performance of MSMEs and cooperatives from the upstream and downstream sides. This is evidenced by the fact that 1.3 million farmers control 96 percent of Indonesia's coffee plantations, and more than 2,950 coffee shops are managed by young people and creative economy actors (Kompas, 2022). In Indonesia, there has been an increase in the high interest in coffee. According to research conducted by Toffin and MIX Marcom Magazine in 2019, the number of coffee shops in Indonesia grew to 2,950 outlets, which has tripled compared to the previous year. Coffee is a very popular drink in the world. There are several countries whose residents are fond of drinking coffee, so they are listed as the largest coffee consumers. Figure 1.1 shows data on countries that consume the most coffee. The consumption of coffee in Russia is 4.7 million bags measuring 60 kg. Figure 1.2 shows coffee consumption in Indonesia.

Figure 2. Coffee Consumption
Sources: International Coffee Organization (ICO) According to data from the International Coffee Organization (ICO), coffee consumption in Indonesia will reach 5 million bags measuring 60 kilograms in 2020/2021. That number increased by 4.04% compared to the previous period, which amounted to 4.81 million 60 kg bags. Coffee consumption in Indonesia in 2020/2021 will also be the highest in the last decade. Furthermore, Indonesia's coffee consumption is one of the largest in the world. Indonesia is in fifth place or below Japan, whose coffee consumption reaches 7.39 million bags measuring 60 kg. Meanwhile, Indonesia's coffee production will reach 774.6 thousand tons in 2021. This value is up 2.75% from the previous year, which was 753.9 thousand tons. South Sumatra is Indonesia's largest coffee-producing region based in the province because it produces 201.4 thousand tons. Then there is Lampung, with coffee production of 118 thousand tons. Coffee production in North Sumatra is 76.80 thousand tons. Meanwhile, Aceh and Bengkulu produced 74.20 thousand tons and 62.40 thousand tons of coffee, respectively.
The trend of coffee shops in Medan is increasingly mushrooming. At least for young people, school children, college students, and employees, coffee shops are a place for them to gather with friends and colleagues and even discuss business opportunities. Instantly hangout places such as coffee shops have sprung up, so the culinary business is growing in Medan (Lubis, K 2019). One of the business actors who joined Among the many coffee shops is "selasa_comuna." This coffee shop in the city of Medan 2019 by offering an outdoor layout where customers will feel and enjoy an open atmosphere, with a cup of coffee and views of the sky. As this continues, coffee shop consumers will want innovations and look for unique coffee shops. Customer satisfaction is very important for the company to continue its business. According to (Saidani & Arifin, 2012), customer satisfaction is the customer's reaction to the customer's perceived discrepancy between expectations and actual service performance. Consumer satisfaction is the main goal in the success of his business. According to (Tjiptono et al., 2012), several factors influence customer satisfaction, including: based on research conducted by (Faradisa et al., 2016) says that product variety is a company strategy by diversifying its products with the aim that consumers get the product that it wants and needs. Coffeeshop "Selasa_communa" and its competitors in Medan are competing to attract consumers' attention. With a price range almost the same as its competitors, coffee shop owners in Medan are always guided to innovate and provide different added value for their customers.
Its main foundation lies in its strength in understanding consumer behavior and interpreting this understanding to design, deliver and implement marketing strategies more effectively than competitors (Tjiptono, 2012). Every business organization depends on customer satisfaction and loyalty. The more satisfied customers are with the products and or services offered, the higher the business's success level. It is inseparable from this; one of the coffee shops in Medan offers products to its customers in the hope that customers will be satisfied and return to the coffee shop to buy or try other products. Interestingly, the sales data that researchers obtained from the sales report at "selasa_communa" saw a decline in sales that was quite volatile, as shown in Figure 3 below:

Figure 3. Sales Report "selasa_communa"
Based on Figure 3, you can see a decrease in sales on "sela_communa." Based on one of the interviews that the researchers conducted with one of the customers who bought drinks at the coffee shop, it was stated that the service provided was good, various types of payment transaction methods, pleasant atmosphere, menu choices for coffee lovers, not many menu choices to choose from. One of the stages in purchasing decisions, according to (Kotler, 2016), is problem recognition, namely problem recognition. Buyers see their needs by buying the products they need. Based on this background, the decline in sales experienced by "selasa_communa" can be identified by which customer satisfaction indicators can increase customer satisfaction with purchasing decisions. This makes the company continue to carry out its operations effectively and efficiently in marketing. This instrument is expected to help predict effective ways to determine a strategy and what needs to be seen in carrying out that strategy. This research is important to see the influence of Customer Satisfaction on Purchase Decisions at selasa_communa and find out opportunities to increase customer satisfaction by creating new strategies that can be utilized in purchasing decisions. Researchers wish to conduct research entitled "Analysis of the influence of customer satisfaction on coffee shop purchasing decisions on tuesday_communa."

Conceptual Framework
One of the goals of a business is to continue to grow. In making it happen, it is hoped that business owners will not only continue to innovate so that the business they manage will survive. Business managers are also expected to continue to look for and make customers feel satisfied. Customer satisfaction is an overall assessment of a product or service based on the experience of buying and consuming it from time to time (Zhong & Moon, 2020). (Rahmat H, 2015) which states that there is an influence of consumer satisfaction on the decision to purchase Philips lamps for Telkom University students. A study found that increasing customer satisfaction positively affects purchasing decisions (Moudi et al., 2021).

Hypothesis
Based on the phenomenon and from the theoretical basis that has been stated previously, the hypotheses in this study are as follows: H1 = Customer satisfaction has a positive and significant effect on purchasing decisions

IMPLEMENTATION METHOD
In this study, researchers used a simple regression method to know the extent of the direct relationship between the independent variables and the dependent variable. This research was conducted at the "selasa_communa" coffee shop located on Jl. Major General D. I Panjaitan no.30 North Sumatra Medan. Meanwhile, the object of research is potential customers who have made transactions on "selasa_communa" with a research time of April-May 2023. Respondents were determined using the Non-Probability Sampling technique using Accidental Sampling. Accidental Sampling is a technique of determining a sample based on coincidence. That is, anyone who meets a researcher by chance can be used as a sample if it is deemed that the person meets the criteria that become the standard for the sample. Respondents in this study are potential customers who are the target market of "selasa_communa." Potential customers were chosen because they have a high probability of reaching and making purchases at the "selasa_communa" coffee shop. The criteria for potential customer respondents are as follows: 1. Age Between 18 to 34 years 2. Never made a repeat purchase at a coffee shop 3. Lives in Medan and its surroundings In this study, data were collected by a questionnaire. The questionnaire is a data collection method that gives respondents a series of written questions/sentences to answer or ask for answers (Sugiyono, 2019). This study addressed the questionnaire to customers and prospective customers of the coffee shop selasa_communa. The measurement scale in this study used the Interval Scale. The interval scale is used to measure the preferences of each indicator.

RESULTS AND DISCUSSION Validity Test and Reliability Test (Pre-Test) Validity Test (Pre-Test)
This sub-chapter validity is measured by analyzing 30 respondents or customers who have made study program purchase transactions at "selasa_communa." Table 1 shows the results of the pretest validity test based on calculations using SPSS 25. Below is a measurement of the validity of the Pearson Correlation. Source: SPPS ver 25 and Excel data processing Table 1 shows the existence of instruments on the customer satisfaction variable with invalid criteria. According to (Murti, 2011), measurement errors can be called measurement bias (measurement error). When the instrument produces invalid data, the research results are invalid. Invalid indicators can occur when statements are biased or have double meanings. Achievement of a valid instrument, one of which is by cutting an invalid statement instrument. Table 2 is the result of the validity test with the instrument that has been cut.
In Table 1, all instruments are valid and can be continued later.

Reliability Test (Pretest)
This reliability test aims to measure the consistency of the instrument statement on the variable. With Croanbach's alpha > 0.6 limit value, the instrument can be considered consistent and reliable concerning the variable.   Table 3 shows the pre-test reliability test results show that the research variables proved reliable and consistent with the variables of this study.

Normality test
In this study, normality testing was carried out using the Kolomogorov-Smirov. The following data processing results with SPSS version 25 are listed in Table 4.

Linearity Test
This test determines whether the two variables have a linear or significant relationship. A good correlation should have a linear relationship between the predictor or independent variable (X) and the criterion or dependent variable (Y). In Figure 5., the data processing results will be presented to test linearity. Based on Table 5, several values form the basis that the linearity test can be said between variables there is a linear relationship, including: 1) Based on the value of Sig. From Table 5, the output results show the Linearity Sig value. of 0.108, which value is greater than 0.05. Based on Table 5, it can be concluded that there is a significant linear relationship between the variables of Customer Satisfaction and Purchase Decision 2) Based on the F Score From Table 5, the calculated F value is 1.842, and Ftable is 2.27. Based on the Fcount value of 1,842 <Ftable 2.27, the Fcount value is smaller than Ftable, and it can be concluded that there is a significant linear relationship between the variables of customer satisfaction and purchasing decisions

Heteroscedasticity Test
After carrying out the Normality Test and Linearity Test, the next step will be to test heteroscedasticity. The heteroscedasticity test is part of the classical assumption test in regression analysis to test whether there is an inequality of variance from the residual value or observation to other observations in the regression model. One way to detect heteroscedasticity is the Glejser test. The basis for decision-making is useful as a guideline in determining a conclusion for a decision based on the results of the analysis that has been carried out, as shown in Table 6. Based on Table 6. the data on the results of the respondents were processed using SPSS ver 25. It is known that the sig. greater (>) 0.05 indicates that the data does not have symptoms of heteroscedasticity or can be said to be homoscedasticity data. Homoscedasticity is when the residual value at each predicted value varies, and the variations tend to be constant.

Hypothesis Test Simple Regression Test
Simple Regression Test, showing the effect of the independent variable on the dependent variable with the following equation Y = a + bx, this regression test is shown in Table 7. following: Based on Table 7. It is known that the SPSS output value is 0.000 or smaller (<) than the probability of 0.05, so it can be concluded that H_0 is rejected and H_1 is accepted. H_1 is accepted, which means that "There is an influence of Customer Satisfaction on Purchasing Decisions."

t Test
The basis for making decisions in the t-test is: • If the calculated t value is greater (>) than the t table, then there is an effect of Customer Satisfaction (X) on Purchase Decision (Y) • If on the other hand, the calculated t value is smaller (<) than the t table, then there is no effect of Customer Satisfaction (X) on Purchase Decision (Y) Based on the SPSS output in Table 7, it is known that the t count is 5,965. After knowing the t count, the next step is to find the t table. Ttable can be known by the formula df = n-k and the value a/2.
(df) = 40 -2 = 38 The value of a /2 = 0.025. After looking through the distribution of the t table values, the t table is 0.68100. Customer Satisfaction has t count 5.965 > t table 0.68100, H_1 is accepted, it means that "There is an influence of Customer Satisfaction on Purchasing Decisions."

Test the Coefficient of Determination or R square.
It can be seen from the R square value to determine the magnitude of the influence of customer satisfaction (X) on purchasing decisions (Y) in simple linear regression. Table 8 shows the R square test as follows:  Table 8, it is known that the Rsquare value is 0.799. This value can be interpreted that there is an influence of Customer Satisfaction (X) on Purchase Decisions (Y).

Discussion
The study shows that customer satisfaction influences purchasing decisions, meaning that customer satisfaction is one of the elements that can encourage customers to make decisions to make purchases of an item or service. According to (Pakurár et al., 2019), customer satisfaction is the customer's feelings about the evaluation process results that compare expectations with performance. When customers are satisfied with the goods or services offered, they become loyal and recommend their experiences using those provided to others (Rohaeni & Marwa, 2018). Judging from the Simple Regression value results, customer satisfaction has a positive relationship to purchasing decisions, meaning that if the level of customer satisfaction is higher, the customer's decision to make purchases of an item or service will increase. These results provide empirical evidence that customer expectations for atmosphere, quality of goods or services, costs, and overall satisfaction with purchases are indicators that can increase customer satisfaction (Mannan et al., 2019). Previous research said that customer satisfaction could influence purchasing decisions is research (Atma & Nio, 2019). The results of this study show that customer satisfaction can increase purchasing decisions if the customer experience of an item or service can exceed the expectations and needs of what is offered. So that customers will feel satisfied and tend to make repeat purchases in the future. The results of this study are also in line with previous research, such as research (Purba et al., 2021), where customer satisfaction can influence purchasing decisions. This study supports the previous theory that customers will repurchase the goods or services they have purchased if they are satisfied. Satisfied customers will also give good reviews about goods or services to others and vice versa.

CONCLUSION
Customer satisfaction significantly affects purchasing decisions at the coffee shop "selasa_communa.' The influence of customer satisfaction variables on purchasing decisions is 79%, and 21% are other variables not examined. For further research wishing to examine the same topic, it is expected to add independent variables that have the potential to increase customer satisfaction and expand the scope of the research object. The aim is to make research more varied and more corroborative about the theory of customer satisfaction and purchasing decisions. For companies, based on the results of this study, researchers suggest paying more attention to the factors that can trigger customer satisfaction because customer satisfaction is a measure of the success of a product/service that the company has offered to customers.