Almana : Jurnal Manajemen dan Bisnis Volume 9 No.
2/ August 2025: 307-315 p-ISSN: 2579-4892/ e-ISSN: 2655-8327 DOI: 10.
36555/almana.
The Effect of Hospital Service Quality.
Perceived Value, and Perceived Price on Patient Loyalty and Patient Satisfaction Weni Miftachul Jannah Universitas Hayam Wuruk Perbanas.
Indonesia *Corresponding Email: wenimj3@gmail.
Abstract: Public health centers play a strategic role in shaping positive patient experiences that influence satisfaction and loyalty.
This study aims to analyze the influence of service quality, perceived value, and perceived price on patient satisfaction and loyalty.
Using a quantitative explanatory approach, data were collected from 397 respondents selected through purposive sampling from the 2023 patient population.
The analysis was conducted using Partial Least SquaresAeStructural Equation Modeling (PLSSEM).
The results show that service quality and perceived value have a positive and significant effect on patient satisfaction, while perceived price has a moderate influence.
Patient satisfaction significantly mediates the relationship between the three independent variables and patient loyalty.
These findings highlight the importance of improving service quality and enhancing perceptions of value and pricing to create a satisfying healthcare experience and foster longterm loyalty.
The study provides practical insights for healthcare managers to strengthen service delivery and offer transparent pricing information, as well as empirical evidence for developing strategies to improve primary healthcare services based on patient satisfaction and loyalty.
Article History:
Submitted: July 03, 2025 Revised: August 11, 2025 Accepted: August 14, 2025 Published: 27 August, 2025 Keywords:
Loyalty Patient Satisfaction Perceived Price Perceived Value Service Quality Jannah.
The Effect of Hospital Service Quality.
Perceived Value, and Perceived Price on Patient Loyalty and Patient Satisfaction.
Almana : Jurnal Manajemen dan Bisnis, 9.
, https://doi.
org/10.
36555/almana.
INTRODUCTION
Puskesmas as the spearhead of first-level health services have an important role in supporting public health programs in Indonesia (Yustina & Yohanes Budisarwo, 2.
a public service institution.
Puskesmas is required not only to provide adequate medical services, but also to pay attention to service quality, perceived patient value, and perceptions of the price of services charged (Susmiati & Mustofa, 2.
These three factors are important determinants in shaping patient satisfaction and loyalty.
The quality of health services is a key factor that influences people's perceptions of the effectiveness and efficiency of Puskesmas services.
Responsive, friendly, and professional services will foster a sense of satisfaction in patients and encourage the desire to return to utilize these services.
Conversely, if the services provided do not meet expectations, patients tend to look for alternative health facilities (Flaviana et al.
, 2023.
Imran et al.
, 2021.
Wulandari et al.
, 2.
In addition to service quality, the perceived value or benefit that patient feel for the services received also plays an important role (Nguyen et al.
, 2.
Patients tend to be loyal when they feel that the services provided are worth the time, effort, and costs incurred.
This work is licensed under a Creative Commons Attribution-NonCommercialNoDerivatives 4.
0 International License.
https://creativecommons.
org/licenses/by-nc-nd/4.
Almana : Jurnal Manajemen dan Bisnis p-ISSN: 2579-4892 e-ISSN: 2655-8327 This perceived value reflects the comparison between expectations and reality experienced during the service process (Eris, 2022.
Tuncer et al.
, 2.
Price perception is also a determining factor in shaping patient satisfaction.
In the context of public services such as health centers, where prices are often determined by government policies, perceptions of fairness and affordability of prices are important Prices that are considered fair and in accordance with service quality can increase patient satisfaction and loyalty (Febriani & Cipta, 2023.
Pertiwi et al.
, 2022.
Rahman et al.
, 2.
The phenomenon that occurs in some Puskesmas shows fluctuations in patient visits that can be an indication of decreased satisfaction or loyalty.
One example can be seen in the trend of visits at Puskesmas Benowo, which has decreased in certain months despite a general increase in the number of annual patients.
This suggests the need to evaluate the factors that influence patient satisfaction and loyalty.
Seeing the important role of service quality, perceived value, and perceived price in influencing patient loyalty and satisfaction, this study was conducted to examine the relationship between these three variables in the context of services at Puskesmas.
It is expected that the results of this study can contribute to efforts to improve the quality of basic health services, especially in health centres as the frontline of public services.
The purpose of this study is to analyse and explain the effect of service quality, perceived value, and perceived price on patient satisfaction and loyalty at Puskesmas Benowo Surabaya.
This study specifically aims to identify the extent to which the three independent variables affect patient satisfaction, as well as how patient satisfaction acts as a mediator in shaping loyalty to the health services provided.
By understanding the relationship between these variables, this study is expected to provide an empirical contribution to the development of strategies to improve the quality of health services at the Puskesmas, so as to create a satisfying experience and encourage long-term patient Based on the above background, the hypothesis of this study is as follows:
H1 : Health Service Quality Affects Patient Satisfaction H2 : Perceived Value Affects Patient Satisfaction H3 : Price Perception Affects Patient Satisfaction H4 : Quality of Health Services Affects Patient Loyalty H5 : Perceived Value Affects Patient Loyalty H6 : Price Perception Affects Patient Loyalty H7 : Patient Satisfaction Affects Patient Loyalty.
METHODS
This study used a quantitative approach with an explanatory type of research that aims to explain the causal relationship between the independent variables, namely health service quality, perceived value, and perceived price, on the dependent variables of patient satisfaction and patient loyalty.
This research design aimed to test hypotheses through data collection from respondents and analysed using statistical methods.
The population in this study were patients who received services at the Benowo Surabaya Health Center in 2023, namely 60,760 people, with sampling using purposive sampling technique, which is a sampling technique based on certain criteria so that the data obtained is relevant to the research objectives.
The sample criteria used in this study include respondents who are patients who seek treatment at the Benowo Health Center at least 2x visits in the last 1 year, male and female respondents, and respondents aged from 20 years to 59 years.
The number of respondents in this study was 397 people, which is considered to represent the population adequately.
The value was obtained through the use of the Slovin formula as follows:
The Effect of Hospital Service Quality.
Perceived Value, and Perceived Price on Patient Loyalty and Patient Satisfaction Weni Miftachul Jannah Almana : Jurnal Manajemen dan Bisnis Volume 9 No.
2/ August 2025: 307-315 n= N 1 N .
2 Description:
A n = number of samples A N = total population A e = maximum tolerable error limit .
argin of erro.
By using a margin of error of 0.
%), the number of samples that can be taken n= 607601 60760 .
2 n= 396,4=397 Based on the results of the above calculations, the number of samples used is at least 397 respondents.
The data collection instrument used a Likert scale-based closed questionnaire, which has been tested for validity and reliability.
Instrument validity was tested using outer loading, and reliability was tested with composite reliability and Cronbach's alpha, in accordance with the provisions in the Partial Least Square - Structural Equation Modelling (PLS-SEM) method using SmartPLS software.
This technique was chosen because it is able to analyse complex relationships between variables, including mediation effects and indirect relationships, as was done in this study.
RESULTS AND DISCUSSION
This research uses data analysis techniques with the product moment correlation method from Pearson correlation using SPSS software version 26.
Validity Test The validity test is used to assess whether a questionnaire is valid or not.
questionnaire is said to be valid if the questionnaire questions are able to reveal something that is measured by the questionnaire.
Based on the results of the validity test of the product moment correlation technique from Pearson correlation on the variable scale of Health Service Quality (X.
Value Perception (X.
Price Perception (X.
Patient Satisfaction (Z) on Patient Loyalty (Y).
The questionnaire was distributed to 30 respondents who were patients who sought treatment at the Benowo Health Center in the last 1 year which was tested and declared all items were valid.
On the basis of calculations where n = 30, the r table value is 0.
To prove that the item score is valid, the calculated r value must be greater than the r table value.
To clarify this assumption, it can be known as follows:
Table 1.
Validity Test Results No.
Variables Quality of Health Services (X.
Item
KLK1
KLK2
KLK3
KLK4
KLK5
KLK6
KLK7
KLK8
KLK9
KLK10
KLK11
KLK12
R Table 0,361 0,361 0,361 0,361 0,361 0,361 0,361 0,361 0,361 0,361 0,361 0,361 R Count
0,435
0,413
0,723
0,710
0,792
0,628
0,743
0,853
0,772
0,893
0,800
0,645
Description Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Website: http://journalfeb.
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php/almana/article/view /2877 Almana : Jurnal Manajemen dan Bisnis p-ISSN: 2579-4892
e-ISSN: 2655-8327
KLK13
0,361
KLK14
0,361
KLK15
0,361
PN1
0,361
PN2
0,361
PN3
0,361
Perceived Value (X.
PN4
0,361
PN5
0,361
PH1
0,361
PH2
0,361
PH3
0,361
PH4
0,361
Price Perception (X.
PH5
0,361
PH6
0,361
PH7
0,361
KP1
0,361
KP2
0,361
Patient Satisfaction (Z) KP3
0,361
LP1
0,361
LP2
0,361
Patient Loyalty (Y) LP3
0,361
Source: SPSS output .
0,526 0,717 0,784 0,807 0,694 0,786 0,637 0,806 0,295 0,328
0,261
0,967
0,984
0,961
0,845
0,890
0,789
0,792
0,680
0,835
0,835
Valid Valid Valid Valid Valid Valid Valid Valid Invalid Invalid Invalid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Based on the results of the initial validity test conducted on 30 respondents, it is known that all items on the research variables have a calculated r value greater than r table (>0.
so that all items are declared valid.
However, there is a Price Perception variable (X.
on items PH1.
PH2 and PH3 showing the value of r count less than r table (<0.
so the three items are declared invalid or cannot be used for research analysis.
Reliability Test Reliability test is conducted to prove the accuracy, consistency and accuracy of the instrument in measuring constructs (Ghozali, 2.
From the results of the reliability test of all variables to 30 respondents who are patients who seek treatment at the Benowo Health Center in the last 1 year, using the Cronbach's Alpha statistical test formula using SPSS, the reliability test results of all variables are obtained, as follows:
Table 2.
Reliability Test Results No.
Variables Quality of Health Services (X.
Perceived Value (X.
Price Perception (X.
Patient Satisfaction (Z) Patient Loyalty (Y) Standard Cronbach's Alpha Cronbach's Alpha Description 0,60 0,922 Reliable 0,60 0,60 0,60 0,60 Source: SPSS output .
0,786 0,855 0,762 0,690 Reliable Reliable Reliable Reliable The results of the reliability test conducted on all variables in this study show a good level of consistency, with the Cronbach's Alpha value for each variable exceeding the recommended minimum limit .
The Health Service Quality variable (X.
has the highest Cronbach's Alpha value of 0.
922, which indicates excellent reliability, followed by The Effect of Hospital Service Quality.
Perceived Value, and Perceived Price on Patient Loyalty and Patient Satisfaction Weni Miftachul Jannah Almana : Jurnal Manajemen dan Bisnis Volume 9 No.
2/ August 2025: 307-315 the perceived value variable (X.
with a value of 0.
786, perceived price (X.
855, and patient satisfaction (Z) which reaches 0.
762, all of which show strong reliability.
Although the Patient Loyalty (Y) variable has a slightly lower Cronbach's Alpha value of 0.
690, this value still meets accepted reliability standards, indicating that all instruments used in this study can be relied upon to consistently measure the variables in question.
The approach to analysing second order factors is to use the repeated indicators approach or also known as the hierarchical component model.
Although this approach repeats the number of manifest variables or indicators, this approach has the advantage that this model can be estimated with the standard PLS algorithm (Ghozali, 2.
PLS-SEM analysis usually consists of two sub models, namely the measurement model or often called the outer model and the structural model or often called the inner The measurement model shows how manifest or observed variables represent latent variables to be measured.
Meanwhile, the structural model shows the strength of the estimate between latent variables or constructs (Ghozali, 2.
Based on the above definition, the PLS analysis model can be said to be the development of a path model which has several advantages such as data does not have to be normally distributed, the model does not have to be based on theory and also the sample used is small.
According to Ghasemy et al.
, there are several terms related to SEM, including: .
Latent Construct, is a process or event in an observation that is formulated conceptually and requires indicators to clarify it.
Manifest variable, is the value of observations in the specific part asked either from respondents who answer questions or observations made by researchers.
In this study, manifest variables are question items / statements of each hypothesized variable or can be interpreted as indicators in each .
Exogenous Variables and Endogenous Variables, are causal variables that are not influenced by other variables but have an effect on other variables, while endogenous variables are variables that are explained by exogenous variables.
Intervening variables, are variables that theoretically affect the relationship between exogenous and endogenous variables, but cannot be measured and observed.
According to (Ghozali, 2.
, in using the Partial Least Square (PLS) method, several steps that can be carried out in PLS analysis are as follows: .
Designing the Measurement Model: The measurement model .
uter mode.
is a model that connects latent variables with manifest variables.
For latent variables hospital service quality, perceived value, perceived price (X), patient satisfaction (Z), and patient loyalty (Y) consists of 19 manifest variables.
Designing the Structural Model: The structural model .
nner mode.
in this study consists of one exogenous latent variable, namely hospital service quality, perceived value, perceived price (X).
Building a Path Diagram.
The relationship between variables in a flowchart can help in framing the causal relationship between constructs from the previous theoretical model.
Furthermore, the model fit measurement is carried out (Ghozali, 2.
Model Measurement (Outer Mode.
The outer model is often called .
uter relation or measurement mode.
which defines how each indicator block relates to its latent variable.
The measurement model .
uter mode.
is used to assess the validity and reliability of the model.
The validity test is carried out to determine the ability of the research instrument to measure what should be measured.
Meanwhile, the reliability test is used to measure the consistency of the measuring instrument in measuring a concept or it can also be used to measure the consistency of respondents in answering statement items in a questionnaire or research instrument.
Convergent validity Convergent validity tests in PLS with reflective indicators are assessed based on the loading factor .
orrelation between item scores / component scores and construct score.
of the indicators that measure the construct.
(Ghozali, 2.
suggests that the rule of thumb Website: http://journalfeb.
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php/almana/article/view /2877 Almana : Jurnal Manajemen dan Bisnis p-ISSN: 2579-4892 e-ISSN: 2655-8327 that is usually used to make an initial examination of the factor matrix is A 30 is considered to have met the minimum level, for loading A 40 is considered better, and for loading A 50 is considered practically significant.
Thus, the higher the factor loading value, the more important the loading is in interpreting the factor matrix.
The rule of thumb used for convergent validity is outer loading> 0.
6, communality> 0.
5 and average variance extracted (AVE)> 0.
5 (Ghozali, 2.
Discriminant Validity Discriminant validity tests are assessed based on the cross loading of measurements with their constructs.
Another method used to assess discriminant validity is to compare the AVE root for each construct with the correlation between constructs and other constructs in the model.
The model has sufficient discriminant validity if the AVE root for each construct is greater than the correlation between constructs and other constructs in the model (Ghozali, 2.
Composite Reliability To determine composite reliability, if the composite reliability value Ac> 0.
8, it can be said that the construct has high reliability or reliability and Ac> 0.
6 is said to be quite reliable (Ghozali, 2.
Cronbach's Alpha In PLS, the reliability test is strengthened by the presence of Cronbach alpha where the consistency of each answer is tested.
Cronbach's Alpha is said to be good if > 0.
5 and is said to be sufficient if > 0.
3 (Ghozali, 2.
Table 3.
Outer Model Evaluation Rule of Thumbs Parameters Outer Model Evaluation Convergent validity Discriminant Validity Composite Reliability Cronbach's Alpha Parameters Loading factor Average variance extracted (AVE) Composite Reliability Cronbach's Alpha Source: Ghozali .
Rule Of Thumbs More than 0.
More than 0.
More than 0.
More than 0.
Structural Model Evaluation (Inner Mode.
The structural model .
nner mode.
is a structural model to predict the causal relationship between latent variables.
Through the bootstrapping process.
T-statistic test parameters are obtained to predict the existence of causal relationships.
The structural model .
nner mode.
is evaluated by looking at the percentage of variance explained by the R2 value for the dependent variable using the Stone-Geiser Q-square test (Ghozali, 2.
and also looking at the magnitude of the structural path coefficient.
Because PLS is designed for recursive models, the relationship between latent variables, each dependent latent variable, or often called the causal system of latent variables.
R-Square (R.
R-square is seen from the value of endogenous variables as the predictive power of the structural model.
Changes in the R2 value can be used to explain the effect of certain exogenous latent variables on endogenous latent variables whether they have a substantive R-square values of 0.
75, 0.
50, and 0.
25 can be concluded that the model is strong, moderate and weak (Ghozali, 2.
This means that the higher the R2 value, the better the prediction model and the proposed research model.
The Effect of Hospital Service Quality.
Perceived Value, and Perceived Price on Patient Loyalty and Patient Satisfaction Weni Miftachul Jannah Almana : Jurnal Manajemen dan Bisnis Volume 9 No.
2/ August 2025: 307-315 Q2 Predictive Relevance According to Samartha .
to measure how well the observation value produced by the model and also the parameter estimate can use Q2 predictive relevance or the coefficient of total determination in path analysis .
imilar to R2 in regressio.
A value of Q2> 0 indicates that the model has predictive relevance, while a value of Q2 <0 indicates that the model lacks predictive relevance (Ghozali, 2.
This is very important to ensure that the model used is not only statistically significant but also relevant.
Goodness Of Fit (GoF) Index PLS path modelling can identify global optimization criteria to determine goodness of fit with the Gof index.
Goodness of fit or Gof index is used to evaluate the overall fit of the measurement model and structural model while providing a simple measurement for the overall predictability of the model.
The GoF value criteria are 0.
10 (GoF smal.
, 0.
25 (GoF mediu.
36 (GoF larg.
(Ghozali, 2.
Using QA and GoF, to ensure that the relationships between variables in the model not only exist but are also significant and relevant.
Parametric Statistical Tests and Hypothesis Testing According to Sugiyono .
, the hypothesis is a temporary answer to the formulation of research problems, where the research formulation has been stated in the form of a statement sentence.
It is said to be temporary, because the answers are given to empirical facts obtained through data collection.
So, the hypothesis is also stated as a theoretical answer to the formulation of research problems, not yet an empirical answer.
Test decision:
If t-count > t-table, and the significance p-value is smaller than 0.
05 or < 5% then H1 is accepted and H0 is rejected, meaning the relationship between variables is significant.
Hypothesis conclusion: "There is a significant relationship between the independent variable and the dependent variable.
This means that the hypothesis is accepted".
If t-count < t-table, and the significance p-value is greater than 0.
05 or > 5% then Ho is accepted and H1 is rejected, meaning that the relationship between variables is not Hypothesis conclusion: "There is no significant relationship between the independent variable and the dependent variable.
This means that the hypothesis is Effect size Effect size is a measure used to assess the strength of the relationship between predictor variables and response variables.
It is interpreted whether the predictor variable has a strong, moderate, or small influence at the structural level.
The effect size value is strong .
, moderate .
, small .
Table 4.
Inner Model Evaluation Rule of Thumbs Parameters Inner Model Evaluation R-Square (R.
Parameters Change in R2value Q2 Value Rule Of Thumbs R-square values of 0.
75=strong, 50=moderate, and 0.
25=weak Q2 Predictive Relevance Q2 > 0= has predictive relevance Q2 < 0= has less predictive relevance Goodness Of Fit (GoF) Index GoF Value 10 (GoF smal.
, 0.
25 (GoF mediu.
36 (GoF larg.
Significancy test .
ypothesis testin.
P-value < 0,05 Effect size Effect size Weak effect size= 0.
Moderate effect size = 0.
Strong effect size = 0.
Source: Ghozali .
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e-ISSN: 2655-8327
CONCLUSION
This study concludes that service quality, perceived value, and perceived price have a significant influence on patient satisfaction, which in turn affects patient loyalty at Puskesmas Benowo Surabaya.
Service quality proved to be a dominant factor in shaping patient satisfaction because responsive, friendly, and professional services are able to create a positive experience during the treatment process.
Perceived value also contributes greatly to satisfaction, as patients feel that the service received is worth the cost, time, and effort they spend.
Meanwhile, perceived price has a more moderate influence, but is still relevant in creating a sense of fairness and affordability.
Furthermore, patient satisfaction acts as a mediating variable that strengthens the relationship between the three independent variables and patient loyalty.
This suggests that to increase loyalty, it is not enough to provide good service, but also to ensure that patients are thoroughly satisfied with the services received.
Therefore.
Puskesmas managers need to design service quality improvement strategies that touch all aspects of the patient experience, from the administrative process, interactions with medical personnel, to the transparent delivery of price information.
This holistic approach will strengthen satisfaction while fostering sustainable loyalty.
REFERENCES