Electronic Journal of Education.
Social Economics and Technology Vol.
No.
2, .
, pp.
Article ID: 824 ISSN 2723-6250 .
DOI: https://doi.
org/10.
33122/ejeset.
Research Article The Influence of Service Quality and Price on Customer Satisfaction of Economy-Type Rooms at Hotel Rajawali in Nanga Pinoh.
Melawi Regency Ferry Kurniawan*, and Helman Fachri Faculty of Economics and Business.
Universitas Muhammadiyah Pontianak.
Pontianak.
Kalimantan Barat, 78123.
Indonesia *Corresponding Author: 211310227@unmuhpnk.
id | Phone: 62 852-5212-1516
ABSTRACT
This study aims to examine the influence of service quality and price on customer satisfaction of economy-type rooms at Hotel Rajawali in Nanga Pinoh.
Melawi Regency.
The research is motivated by the importance of service quality and price in shaping customer satisfaction amid increasing competition in the hospitality industry.
This study employs a quantitative approach using an associative method.
Data were collected through questionnaires distributed to 100 respondents who had stayed at Hotel Rajawali.
The variables examined include service quality (X.
, price (X.
, and customer satisfaction (Y).
Data analysis techniques used include multiple linear regression, validity and reliability tests, as well as classical assumption tests such as normality, linearity, and multicollinearity tests.
The results of the F-test indicate that service quality and price simultaneously have a significant influence on customer satisfaction.
However, the t-test results show that only service quality has a positive and significant partial effect on customer satisfaction, while price does not have a significant effect.
These findings suggest that customer satisfaction at Hotel Rajawali is more strongly influenced by service quality rather than price.
Therefore, it is recommended that hotel management focus more on improving service quality to maintain and enhance customer satisfaction.
Keywords: Service Quality.
Price.
Customer Satisfaction INTRODUCTION The hospitality industry is one of the key sectors in supporting regional economic growth, especially in areas with tourism, trade, and social activity potential.
Melawi Regency, located in West Kalimantan Province, is one such region with considerable potential for the development of this sector.
As the administrative and economic center of Melawi.
Nanga Pinoh plays a strategic role in expanding service networks, including hospitality services.
One hotel that significantly contributes to accommodation services in this area is Hotel Rajawali.
Although classified as a one-star hotel.
Hotel Rajawali has become the primary choice for visitors from outside the city coming for tourism, business, training, or government-related activities.
Hotel RajawaliAos strategic location in the heart of Nanga Pinoh makes it not only a place to stay but also a venue for various events, such as seminars, workshops, and community meetings.
This dual function demonstrates that the hotel is not merely an accommodation provider but also an integral part of the local socio-economic dynamics.
As community mobility and demands for quality services increase, the hospitality sector must continuously adapt and deliver optimal services to its consumers.
The growing competition in the hospitality industry, both locally and nationally, pushes businesses to constantly improve and innovate, particularly in service delivery and pricing strategies.
Service quality is one of the main indicators influencing consumer satisfaction.
Consumers generally have specific expectations for the services they will receive.
According to Lovelock-Wright, translated by Tjiptono .
n Rohaen, 2.
, service quality is defined as the degree of excellence expected from a service to fulfill customer needs and desires.
According to Tjiptono & Chandra .
n Kurniasari, 2.
, the five key dimensions of service quality include tangibles, reliability, responsiveness, assurance, and These dimensions must be consistently maintained to deliver a satisfying customer experience.
In addition to service quality, price is also a crucial factor affecting customer decisions and satisfaction.
Kotler and Armstrong .
define price as the amount of money paid by consumers to obtain a product or service, closely related to the companyAos image and marketing strategy.
Price is not merely a monetary value but also a representation of the quality of goods or services offered.
According to Kotler and Armstrong, the dimensions of price include affordability, suitability of price with the quality and benefits received, and price competitiveness compared to similar products or services offered by competitors.
Therefore, a proper pricing strategy can help build a positive perception among Page 1 of 6 Kurniawan & Fachri Electronic Journal of Education.
Social Economic and Technology.
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Article ID: 824 Customer satisfaction is a critical aspect reflecting a hotelAos success in meeting customer expectations.
According to Kotler and Keller .
n Azhari et al.
, 2.
, satisfaction arises from the comparison between pre-purchase expectations and the actual performance of a product or service.
When the service received meets or exceeds expectations, customers are likely to feel satisfied and become loyal patrons.
Zeithaml et al.
n Maulina & Cahyono, 2.
identify four key dimensions of customer satisfaction: initial expectations, service delivery, fulfillment of promises .
, and complaint behavior as a response to unmet expectations.
Considering the importance of service quality and pricing as key factors influencing customer satisfaction, this study aims to analyze the extent to which these two variables affect the satisfaction levels of guests staying at Hotel Rajawali Melawi.
The results of this research are expected to provide valuable insights for hotel management in developing better service and pricing strategies that align with market needs and expectations.
Moreover, the findings are anticipated to contribute to the development of knowledge, particularly in the field of hospitality marketing management in regional RESEARCH METHOD This study uses an associative approach, which aims to examine the relationship between two or more variables (Sugiyono.
In this case, the study aims to determine the influence of Service Quality and Price on Customer Satisfaction at Hotel Rajawali Melawi.
The data collection techniques used in this research involve primary and secondary data.
Primary data refers to data directly provided to the data collector (Sugitono, 2.
In this study, primary data were collected through questionnaires distributed to all respondents who had stayed at Hotel Rajawali.
The questionnaires contained statements related to the variables being studied.
Secondary data refers to data not directly provided to the data collector but obtained through intermediaries or documents (Sugiyono, 2.
The secondary data used in this study included room price lists, sales data, and data on available rooms.
The population in this study comprises customers who used the economy room type at Hotel Rajawali, totaling 3,183 customers over the past three years.
The sample was determined using the Slovin formula, resulting in a minimum sample size of 96.
95 respondents.
The researcher decided to use a total of 100 respondents as the The sampling technique used was purposive sampling, which is a sampling method based on specific considerations or criteria (Sugiyono, 2.
The sample criteria were as follows: Respondents aged at least 18 years.
Respondents who had stayed at Hotel Rajawali at least twice.
This study involves two types of variables: Independent variables (X): Service Quality (X.
and Price (X.
Dependent variable (Y): Customer Satisfaction.
The measurement instrument used in this study is the Likert scale.
According to Sugiyono .
, the Likert scale is used to measure a personAos attitude, opinion, and perception toward a social phenomenon.
The Likert scale used in this study consists of five response options, ranging from strongly agree .
to strongly disagree .
The data analysis techniques began with validity and reliability testing.
Validity was tested using the Pearson Product Moment correlation (Ghozali, 2.
Reliability was tested using CronbachAos Alpha (Ghozali, 2.
Classical assumption tests were conducted to ensure the data met statistical requirements.
These included:
Normality test using the Kolmogorov-Smirnov method (Ghozali, 2.
Linearity test using the Test for Linearity (Ghozali, 2.
Multicollinearity test by checking Tolerance and VIF values (Ghozali, 2.
The main analytical method used in this study is multiple linear regression, which is applied to determine the influence of each independent variable on the dependent variable (Sugiyono, 2.
The F-test was used to assess the simultaneous effect (Ghozali, 2.
The t-test was used to assess the partial effect (Ghozali, 2.
To measure the extent to which independent variables contribute to the dependent variable, the study used the coefficient of determination (RA), as well as the correlation coefficient to assess the strength of the relationship between variables (Ghozali, 2.
RESULTS AND DISCUSSION
1 Test Research Instruments 1 Validity Test The r table value is obtained by looking at the r table with .
= n-2= 100-2 =98 and a significance level of 0.
Thus, the r table value in this study is 0.
To determine the results of the validity test for all variables in this study, see Table 1.
Table 1.
Validity Test Results Variable Service Quality (X.
Indicators r count X1.
0,242
X1.
0,235
X1.
0,303
X1.
0,234
Page 2 of 6 r table Description 0,196 Valid Kurniawan & Fachri Price (X.
Customer Satisfaction (Y) Electronic Journal of Education.
Social Economic and Technology.
Vol.
No.
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Article ID: 824 X1.
0,313
X1.
0,217
X1.
0,210
X1.
0,216
X1.
0,237
X1.
0,255
X2.
0,272
X2.
X2.
0,261
0,308
X2.
0,340
X2.
0,486
X2.
0,239
X2.
0,435
X2.
0,219
X2.
0,416
X2.
0,331
0,321
0,432
0,375
0,357
0,532
0,281
0,351
0,311
0,449
0,196
Valid
0,196
Valid Source: Processed Data, 2025 Based on Table 2, it can be seen that all statement items have a calculated r count > r table of 0.
Thus, all statement items in all variables can be declared valid and suitable for use in this study.
2 Reliability Test The results of the reliability test can be seen Table 2.
Variable Service Quality (X.
Price (X.
Customer Satisfaction (Y) Source: Processed Data, 2025 Table 2.
Reliability Test Results CronbachAos Alpha
0,591
0,776
0,816
Description Reliable From the reliability test calculations in Table 2, it can be concluded that all variables used in this study are reliable, because all statement items have a Cronbach's Alpha value greater than 0.
2 Classic Assumption Test 1 Normality Test This normality test aims to determine the distribution of data in the variables that will be used in the study.
Data normality can be seen using the normal kolmogorov-Sminov test.
The results of the Normality test calculation can be seen in the following Table 3.
Page 3 of 6 Kurniawan & Fachri Electronic Journal of Education.
Social Economic and Technology.
Vol.
No.
2, .
, pp.
Article ID: 824 Table 3.
Normality Test Results Test N (Sampl.
Test Statistic Asymp.
Sig.
-taile.
Source: Processed Data, 2025 Value Based on the normality test results.
Asymp.
Sig.
-taile.
was obtained at 0.
Because sig > alpha .
, the regression residuals are normally distributed.
2 Linearity Test Linearity testing in this study used the Test for Linearity.
The testing criteria were that if the significance of Deviation from Linearity > alpha .
, then there was a linear relationship between the independent and dependent variables, or vice versa.
The results of the linearity test for all variables in this study can be seen in Table 4.
Table 4.
Result of Linearity Variable Deviation From Linearity Customer Satisfaction * Service Quality Customer Satisfaction * Price Source: Processed Data, 2025 Description Linear Based on Table 4, it can be seen that the significance value of deviation from linearity > 0.
Therefore, it can be concluded that all variables in this study have a linear relationship.
3 Multicollinearity Test Multicollinearity testing is useful for testing whether the regression model finds correlations between independent The way to determine whether multicollinearity exists is by looking at the Tolerance and VIF values of each independent variable.
If the Tolerance value is > 0.
10 and the VIF value is < 10, then the regression model is free from The results of the multicollinearity test can be seen in Table 5.
Table 5.
Multicollinearity Test Results Variable Tolerance Service Quality Price
Dependent Variable: Customer Satisfaction Source: Processed Data, 2025
VIF
Based on Table 5, the results of the multicollinearity test indicate that each variable.
Service Quality (X.
and brand Price (X.
, has a tolerance value of 0.
205, which is greater than 0.
10, meaning that there is no multicollinearity.
Additionally, the VIF values for each variable.
Service Quality (X.
and brand Price (X.
, are 4.
873, which is less than 10.
00, indicating that there is no multicollinearity.
3 Multiple Linear Regression Analysis The results of multiple linear regression analysis can be seen in Table 6.
Table 6.
Multiple Linear Regression Analysis Results Research Variable Coefficients t Statistic (Constan.
Service Quality Price Dependent Variable: Customer Satisfaction Source: Processed Data, 2025 Significance Value Based on Table 6, it can be seen that the multiple linear regression equation is as follows:
Y = -4,583 0,553X1 0,535X2
From the multiple linear regression equation, it can be explained as follows:
The constant value .
This means that if the Service Quality (X.
and Price (X.
variables are zero .
, then the Customer Satisfaction variable (Y) is -4.
583 units.
Page 4 of 6 Kurniawan & Fachri Electronic Journal of Education.
Social Economic and Technology.
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Article ID: 824 The regression coefficient .
of the Service Quality (X.
variable is 0.
This value indicates that if the Service Quality (X.
variable increases by 1 .
unit, the Customer Satisfaction variable (Y) will increase by 0.
553 units.
The regression coefficient .
of the Price variable (X.
This value indicates that if the Price variable (X.
increases by 1 .
unit, the Customer Satisfaction variable (Y) will increase by 0.
535 units.
4 Correlation Coefficient Analysis (R) The results of the correlation coefficient test calculation can be seen in the following Table 7.
Table 7.
Correlation Coefficient Test Results (R) Model R Square Adjusted R Square Std.
Error of the Estimate Predictors: (Constan.
Price.
Service Quality Dependent Variable: Customer Satisfaction Source: Processed Data, 2025 Based on Table 7 shows that the correlation between Service Quality (X.
and Price (X.
with Customer Satisfaction (Y) 993, which means that Service Quality (X.
and Price (X.
have a very strong relationship with Customer Satisfaction (Y).
5 Analysis of the Coefficient of Determination ycI 2 The coefficient of determination in this study can be seen in Table 7.
The coefficient of determination value is 0.
997, which means that the Customer Satisfaction variable (Y) can be influenced by the Quality (X.
and Price (X.
variables by 99.
while the remaining 0.
3% is explained by other variables not included in this study.
6 Simultaneous Test (F Tes.
The results of the simultaneous test (F tes.
can be seen in the following Table 8.
Table 8.
Simultaneous Test Results (F Tes.
Model Sum of Squares Mean Square Regression Residual Dependent Variable: Customer Satisfaction Predictors: (Constan.
Price.
Service Quality Source: Processed Data, 2025 Significance Based on Table 8, the calculated F value of 7256.
355 is greater than the F table value of 3.
94, and the significance value .
000 is less than 0.
Therefore, it can be concluded that HCA is rejected and HCa is accepted.
This means that there is a significant simultaneous influence of brand image and brand reputation on purchase decisions.
7 Partial Test .
Tes.
The t-test is used to determine how much influence an independent variable has individually in explaining the dependent variable at a significance level of a = 0.
The formula for obtaining the t-table value is .
/ 2: 100-2-.
, so .
05 / 2: 100-.
025: 97 = 1.
, resulting in a t-table value of 1.
The results of the partial influence test can be seen in Table 9.
Table 9.
Partial Test Results .
Tes.
Research Variable Coefficients t Statistic Significance Value (Constan.
Service Quality Price Dependent Variable: Customer Satisfaction Source: Processed Data, 2025 The partial test results in Table 9 can be explained as follows:
The partial effect of Service Quality on Customer Satisfaction in Table 9 above can be seen that the t-value of 26.
440 > ttable value of 1.
984 and the significance value of 0.
000 < 0.
05, so it can be concluded that H 0 is rejected and Ha is accepted.
This means that there is a significant partial effect between Service Quality and Customer Satisfaction.
The partial influence of Price on Customer Satisfaction in Table 9 above can be seen that the t-value of 29.
672 < t-table 984 and the significance value of 0.
000 > 0.
05, so it can be concluded that H o is rejected and Ha is accepted.
This means that there is a significant partial effect between Price and Customer Satisfaction.
Page 5 of 6 Kurniawan & Fachri Electronic Journal of Education.
Social Economic and Technology.
Vol.
No.
2, .
, pp.
Article ID: 824
CONCLUSION
Based on the results of the analysis and discussion, it was found that the number of respondents in this study was 100 people, and the multiple linear regression equation obtained was Y = -4.
553X1 0.
535X2.
The correlation coefficient (R) of 0.
331 indicates a weak relationship between the variables Service Quality (X.
and Price (X.
with Customer Satisfaction (Y).
Meanwhile, the coefficient of determination (RA) is 0.
997, which indicates that 99.
7% of the variation in Customer Satisfaction can be explained by Service Quality and Price, while the remaining 0.
3% is influenced by other factors not examined in this study.
The simultaneous influence test (F-tes.
shows that the calculated F value of 7256.
355 is greater than the F table value of 3.
94, meaning that Service Quality and Price simultaneously have a significant effect on Customer Satisfaction.
The partial influence test .
-tes.
shows that the t-value for Service Quality is 26.
440 and for Price is 29.
both of which are greater than the t-table value of 1.
Thus, it can be concluded that both Service Quality and Price have a significant partial influence on Customer Satisfaction.
Based on these findings, it is recommended that Hotel Rajawali continuously improve the quality of its services.
This can be achieved through regular training programs for all staff to enhance their skills, friendliness, and professionalism, as well as implementing a responsive and structured service system.
Additionally, improving supporting facilities is essential to ensure maximum guest comfort.
On the other hand, considering that Price also has a significant influence.
Hotel Rajawali should design a competitive pricing strategy by taking into account market segmentation and service positioning.
Transparent pricing and attractive package offers can serve as added value that enhances customer appeal without compromising service quality.
Furthermore, even though other factors only 3% to customer satisfaction, it is still advisable for the hotel to develop other supporting aspects such as additional facilities, the use of information technology, and building a strong brand image as strategic steps to enhance overall customer satisfaction.
For future researchers, it is recommended to explore and include additional variables such as hotel facilities, location, customer loyalty, food and beverage quality, and the use of information technology in services, in order to obtain a more comprehensive understanding of the factors that influence customer satisfaction in the hospitality REFERENCES