ISSN 2087-3336 (Prin.
| 2721-4729 (Onlin.
TEKNOSAINS: Jurnal Sains.
Teknologi dan Informatika Vol.
No.
1, 2025, page.
http://jurnal.
id/index.
php/tekno DOI: 10.
Analysis of service quality on customer satisfaction using the service quality method and analytical hierarchy process Niera Feblidiyanti* *Industrial Engineering.
Universitas Pamulang.
Tengerang.
Surya Kencana No.
Pamulang Baru.
Kec.
Pamulang.
Kota Tangerang Selatan.
Banten 15417 * avasonexv@gmail.
Submitted: 20/07/2024 Revised: 01/08/2024 Accepted: 23/08/2024 ABSTRACT This research aims to analyze service quality and customer satisfaction to find out the factors of consumer/customer complaints so that company performance can be improved and improved.
This research uses the Servqual method, the company can then find out consumers' perceptions and expectations, while the company's AHP method can sort out which criteria are prioritized first to improve service quality so that the hospital becomes better.
The results of the research were conducted with a sample of 100 respondents and 20 question items.
In calculating the weighted servqual the priority for improving the quality of service in the Tangible dimension is the criterion "The company has a clean, comfortable waiting room and air conditioning" with a weighted servqual value of -0.
Reliability is the criterion "doctor's availability according to schedule" with a weighted servqual value of -0.
Responsiveness is the criterion of "officer's thoroughness in providing services" with a weighted servqual value of -0.
Assurance is the criterion of "guaranteeing timeliness of service" with a weighted servqual value of -0.
Empathy is the criterion of "officer's sincerity in handling consumers" with a weighted Servqual value of -0.
The most satisfactory criterion is the Reliability dimension which has the criteria "fast and uncomplicated service procedures" with a weighted servqual value of Keywords: Servqual.
AHP.
customer satisfaction.
INTRODUCTION
Nowadays, health problems have become a basic need for society.
As people's living standards increase, people's demands for quality health also increase.
This requires health service providers such as hospitals to improve the quality of services, not only services that are healing for the disease but also include services that are preventive to improve the quality of life and provide satisfaction for consumers as health service users .
Health service management is not yet fully efficient, with quality still relatively low, especially when compared with the quality of services provided by foreign private hospitals which have advantages and are accustomed to professional management systems.
The presence of foreign private hospitals provides benefits for certain groups of people because for them there will be more choices of quality health services, so national hospitals must undergo accreditation every 3 years and be able to compete with several other hospital services .
SERVQUAL is one of the most popular service quality measurement tools and is widely used as a reference in management and marketing research.
SERVQUAL was created based on the gap analysis This tool was developed by A.
Parasuraman.
SERVQUAL consists of 20 instruments used to measure customer perceptions regarding service quality in service and retail organizations .
Ae.
this research.
Servqual also contains 5 dimensions of Tangibles: physical facilities, equipment, and TEKNOSAINS: Jurnal Sains.
Teknologi dan Informatika is licensed under a Creative Commons Attribution-NonCommercial 4.
0 International License.
ISSN 2087-3336
(Prin.
| 2721-4729 (Onlin.
88 Niera Feblidiyanti Analysis of service quality on customer satisfaction using the service quality method and analytical hierarchy process personal appearance.
Reliability: The ability to provide promised services accurately and reliably.
Responsiveness: Willingness to help customers and provide service quickly.
Assurance: Knowledge and courtesy of employees and their ability to create trust and comfort.
Empathy: Caring, individual attention that a company provides to customers .
Ae.
AHP was developed by Dr.
Thomas L.
Saaty from the Warthoon School of Business in the 1970s was a method for solving a complex and unstructured problem into groups, organizing the groups into a hierarchical arrangement, inserting numerical values as a substitute for human perception in making real comparisons and Finally, using a synthesis, the elements that have the highest priority are determined .
Ae.
Wahid's research shows that AHP can determine indicators related to brand issues, warranties, training, spare part control and stock management, pricing, and service systems, including service centers and service facilities .
These indicators are the basis for evaluating the performance of power tools industry companies.
Mahmudi's research has found that the service criteria in the servqual dimension have the 10 highest gaps to be fixed immediately, all gaps have negative values which means that the level of service expectations for customers is higher than the perceptions they receive so they need to be fixed .
Afwan's research has found that the service quality criteria that have the largest gaps in PT.
Telkom Bangkalan's services are 15 criteria.
All service quality gap values have negative values, which means that the level of customer expectations for service quality is higher than the level of perception received .
AHP is a method of breaking down complex problems in unstructured situations into parts.
Organize the existing parts or variables into a form of hierarchical arrangement, then assign a numerical value to each variable and synthesize an assessment of which variable has the highest priority which will influence the resolution of the situation.
AHP combines personal considerations and judgments in a logical way, and is influenced by imagination, experience, and knowledge to arrange a hierarchy of problems based on logic, intuition, and also experience to provide considerations .
Ae.
AHP is a process of analyzing decision-making with a systems approach, where decision-making seeks to understand a system condition and provide estimates of overall system interactions in the AHP method.
METHOD
This type of research is quantitative research based on explanatory research.
Explanatory research is research whose aim is to reveal or explain in depth about certain variables .
This research was used to examine in depth the application of the SERVQUAL (Service Servqua.
method and the AHP (Analytical Hierarchy Proces.
method in determining the level of service quality and corrective actions for Bhineka Bhakti Husada Hospital services.
South Tangerang.
The method and data analysis used in this research is a descriptive analysis method using the SERVQUAL (Service Qualit.
method, and the AHP (Analytical Hierarchy Proces.
method and using computer software in the form of SPSS 22 and software in the form of Microsoft Excel 2010, so that you can determine the level of quality of customer service at Rumah Bhineka Bhakti Husada.
South Tangerang.
RESULT AND DISCUSSION
Service quality analysis Service quality analysis is a way to analyze the services and needs of the company so that the condition of the company's after-sales service is known.
The stages of the analysis are as follows:
Data processing perceived customer satisfaction level (X) The design of the service quality questionnaire contains attributes arranged based on the Q-Rater dimensions, namely reliability, assurance, tangible, empathy, and responsiveness which are shown in Table 1.
No Dimension 1 Tangible Table 1.
Questionnaire design attributes Attribute Completeness of medicines Ae A1 ISSN 2087-3336 (Prin.
| 2721-4729 (Onlin.
DOI 10.
37373/tekno.
Dimension Attribute Availability of ATM facilities that are easily accessible Ae A2 Availability of a comfortable prayer room and availability of complete Reliability Responsive Assurance Empaty prayer equipment Ae A3 Availability of a clean, comfortable waiting room .
se of AC) Ae A3 Registration procedures that do not confuse customers Ae B1 Availability of doctors according to schedule Ae B2 Accuracy of doctors in diagnosing diseases Ae B3 Fast and uncomplicated service procedures Ae B4 Accuracy of staff in providing services Ae C1 Doctors provide explanations about the disease Ae C2 Alacrity of staff in responding to customer complaints Ae C3 Employees provide the information needed Ae C4 Guarantee of service personnel having friendliness, expertise, and skills in serving Ae D1 Guarantee of punctuality of service Ae D2 Guarantee of orderly queues Ae D3 Safe environment with security guards Ae D4 Officers' concern for customers Ae E1 Doctors' concern in responding to complaints Ae E2 Doctors and nurses who are quite attentive Ae E3 Officers' sincerity in dealing with customers -E4 The steps for calculating the satisfaction level value are as follows:
Calculate the total value of each service attribute.
The total value is obtained using the formula .
ycNycuycycayco = .
aA1 ) .
aA2 ) .
aA3 ) .
aA4 ) U .
aA35 ) .
Remark:
B1= Number of respondents answering the question results B2= Number of respondents answering the question results B3= Number of respondents answering the question results B4-B35 = Number of respondents answering the results of the Likert Scale questions in Table 2.
The Likert scale uses the highest score for VERY SATISFIED and the lowest is VERY DISSATISFIED.
The Likert scale used is 1-5.
Table 2.
Likert Scale of Perceived Satisfaction Level (X) Score Satisfaction Level Very satisfied Satisfied Normal Dissatisfied Very Dissatisfied Calculating this value with the number of respondentsAo Customer Satisfaction Level Value = Data Processing Customer Satisfaction Level Expectation (Y) The steps for calculating the satisfaction level value are as follows:
Calculate the total value of each service attribute.
The total value is obtained using the formula .
ycNycuycycayco = .
aA1 ) .
aA2 ) .
aA3 ) .
aA4 ) U .
aA35 ) .
90 Niera Feblidiyanti Analysis of service quality on customer satisfaction using the service quality method and analytical hierarchy process Remark:
B1 = Number of respondents answering the question results B2 = Number of respondents answering the question results B3 = Number of respondents answering the question results B4-B35 = Number of respondents answering the results of the Likert Scale questions in Table 1 Calculating this value with the number of respondent customer satisfaction level value = = 4,74 GAP Score calculation Assessment of the service quality using the service quality method includes calculating the difference between the scores given by customers for each pair of questions related to perceptions and Calculation of the gap between customer perceptions and what consumers expect, which includes analysis of 5 gaps (Ga.
that will affect service quality.
Gap calculations can use a formula and can be seen below:
yaycaycy ycIycaycuycyce = ycEyceycycayceycnycyceycc ycOycaycoycyce Oe yaycuycyyceycaycyceycc ycOycaycoycyce yaycaycy ycIycaycuycyce = 4.
43 Oe 4.
74 = Oe0.
Analysis of average gap service quality Based on a population of 25,268, for 6 months the researcher used 100 customers as a sample of respondents, based on proportionate random sampling, namely sampling that takes into consideration the elements in the research population, then the sampling was continued by lottery, namely a sampling technique by drawing lots for each group to be used as a sample.
yaycaycy ycIycaycuycyce = ycEyceycycayceycnycyceycc ycOycaycoycyce Oe yaycuycyyceycaycyceycc ycOycaycoycyce yaycaycy ycIycaycuycyce = 4.
10 Oe 4.
77 = Oe0.
The recapitulation of the average assessment of the service quality gap can be seen in Table 3.
Table 3.
Average assessment of service quality gap Servqual Dimensions Perception Expectation Average Gap Tangible 4,17 4,77 -0,60 Reliability 4,18 4,62 -0,44 Responssive 4,17 4,76 -0,59 Assurance 4,01 4,80 -0,14 Empaty 3,79 4,65 -0,86 Based on how to calculate the gap between the average value of perception and the average value of expectations, it is obtained.
Once the gaps or discrepancies are known, the next stage is to conclude.
According to Wahid and Hasibuan, a negative satisfaction value (<.
indicates a gap between consumer expectations and perceptions.
If the satisfaction value is positive (>.
, then the service quality has exceeded the level of consumer satisfaction.
If the satisfaction value is equal to zero (=.
, it indicates that the service quality is in line with consumer expectations.
The average value of the Service Quality Gap is in Table 2.
In Table 2 it can be seen that the gap is less than zero (<.
, indicating that there is a gap between consumer expectations and perceptions.
There are still some consumers who are not satisfied with the services provided by the Bhineka Bhakti Husada Hospital services.
This dissatisfaction is caused by the consumer's perception that when they enjoy the service it does not meet expectations.
However, this does not mean that the company is considered bad at all.
The company can still improve its customer satisfaction service if it takes points that need to be improved and corrected so that the service becomes better, therefore weighting is carried out using the analytical hierarchy process method and weighted service quality.
Weighting calculation with AHP and weighted servqual This research used the AHP method to determine weight.
The weights obtained from the results of the analytical hierarchy process are carried out by taking data to obtain data based on the Servqual ISSN 2087-3336 (Prin.
| 2721-4729 (Onlin.
DOI 10.
37373/tekno.
Dimension.
The five .
dimensions include tangible, reliability, responsiveness, assurance, and Empathy.
The weighting can be seen in Table 4.
Table 4 explains the comparison between the values of Factor A and Factor B.
This value is used as a weight to analyze the level of importance of the two The value of 9 is the largest and explains that the Factor has a strong relationship.
Table 4.
Comparison of main criteria
Factor A Factor B
9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9
Tangible Reliability Tangible Responsiveness Tangible Assurance Tangible Empathy Reliability Responsiveness Reliability Assurance Reliability Empathy Responsiveness Assurance Responsiveness Empathy Assurance Empathy The description of the values above is as follows:
1 = Equally important 3 = Slightly more important .
5 = Strongly more important 7 = More important in a very strong way .
ery stron.
9 = More important in an extreme way .
Besides from the values above, other values can also be used, namely 2, 4, 6, and 8.
These values describe the relationship of importance between the odd values mentioned above.
Filling in the column to the left of number 1 indicates that the option on the left has a more important weight than the option on the right.
On the other hand, filling in the column to the right of number 1 indicates that the option on the right has a more important weight than the option on the left.
In determining the final weight, the (IR) random consistency index is used which can be seen in Table 4.
To determine the level of consistency, the results of using the AHP method will be measured by the consistency index.
If the ratio with the Random Index standard >0.
10 then it is concluded that the degree of consistency is satisfactory, meaning that the AHP method produces an optimal solution.
However, if <0.
10 then there is an inconsistency in determining the comparison that allows the AHP method not to produce a meaningful solution.
Table 5.
(IR) random consistency index
Ukuran Matriks Nilai IR
0,00
0,58
0,90
1,12
1,24
1,32
1,41
1,45
1,49
The comparison results from Table 5 above will be converted into a comparison matrix like Table 6.
Table 6.
Paired comparison matrix of the main criteria
Tangible Reliability Responsiveness Assurance 0,25 Tangible Reliability Empathy 0,25 92 Niera Feblidiyanti Analysis of service quality on customer satisfaction using the service quality method and analytical hierarchy process
Responsiveness Assurance Empathy Total
0,33
4,53
3,25
0,33
4,08
Tangible sub-criteria weight value Calculating the weight values of the Tangible sub-criteria, the first thing to do is create a comparison matrix for the Tangible sub-criteria.
The comparison matrix can be seen in Table 7 Table 7.
Pairwise comparison matrix of tangible subcriteria
Sub criteria
0,25
/////
After getting the sub-criteria values, then calculate the normalization matrix by dividing the value of each column by the number of related columns in Table 8.
The normalization of this pairwise comparison matrix aims to make all values equal.
The normalization data can be seen in Table 8 Table 8.
Normalization of the Tangible sub-criteria matrix
Sub criteria
0,235
0,444
0,200
0,222
0,059
0,111
0,200
0,111
0,471
0,222
0,400
0,444
0,235
0,222
0,200
0,222
Total Because the CR value = 0.
075 < 0.
1, the preference for the Tangible sub-criteria value is To determine the weight for the Tangible sub-criteria is obtained by dividing the WSM column value by the total of the WSM column values, so the weight value for each Tangible subcriteria can be seen in Table 9.
Table 9.
Tangible sub-criteria weights Sub criteria Tangible WSM
Sub Criteria Weight
1,171
0,293
1,082
0,271
0,961
0,240
0,990
0,247
4,204
1,051
Total Reliability sub-criteria weight value The reliability sub-criteria comparison matrix is shown in Table 10 Table 10.
Pairwise comparison matrix of reliability sub-criteria
Sub criteria
0,33
Calculating the weight values of the reliability sub-criteria.
The first thing to do is create a comparison matrix for the reliability sub-criteria in Table 10.
Then calculate the normalization matrix by dividing the value of each column by the number of related columns in Table 11.
The normalization ISSN 2087-3336 (Prin.
| 2721-4729 (Onlin.
DOI 10.
37373/tekno.
of this pairwise comparison matrix aims to make all values equal.
The normalization data can be seen in Table 11.
Table 11.
Normalization of Reliability Subcriteria Matrix
Sub criteria
0,167
0,100
0,167
0,214
0,333
0,200
0,333
0,143
0,167
0,100
0,167
0,214
0,333
0,600
0,333
0,429
Total Because the CR value = 0.
072 < 0.
1, the preference for the Reliability sub-criteria value is To determine the weight for the Reliability subcriteria, is obtained by dividing the WSM column value by the total WSM column values, so the weight value for each Reliability subcriteria can be seen in Table 12.
Table 12.
Reliability sub-criteria weights Sub criteria Reliability WSM
Sub Criteria Weight
0,971
0,243
1,262
0,315
0,971
0,243
0,989
0,247
4,194
1,048
Jumlah Responsiveness sub-criteria weight value Calculating the weight value of the Responsiveness sub-criteria.
The first thing to do is create a comparison matrix for the Responsiveness sub-criteria in Table 13.
Table 13.
Responsiveness Subcriteria comparison matrix.
Sub criteria
0,25
0,333
Then calculate the normalization matrix by dividing the value of each column by the number of related columns in Table 14.
The normalization of this pairwise comparison matrix aims to make all values equal.
The normalization data can be seen in Table 14.
Table 14.
Normalization matrix of responsiveness subcriteria
Subcriteria
0,154
0,120
0,222
0,250
0,615
0,480
0,444
0,375
0,154
0,240
0,222
0,250
0,077
0,160
0,111
0,125
Jumlah Calculating the total weight matrix using the sum formula for each criterion in the normalization The results of the total weight matrix calculation can be seen in Table 15.
Table 15.
Responsiveness sub-criteria weights Sub criteria Responsiveness WSM
Sub Criteria Weight
1,212
0,303
0,997
0,249
0,974
0,244
94 Niera Feblidiyanti Analysis of service quality on customer satisfaction using the service quality method and analytical hierarchy process
Total
0,946
4,130
0,237
1,033
Assurance sub-criteria weight value The Assurance subcriteria comparison matrix is shown in Table 16.
Table 16.
Pairwise comparison matrix of Assurance subcriteria Subcriteria Calculating the weight values for the assurance sub-criteria.
The first thing to do is create a comparison matrix for the Assurance sub-criteria in Table 16.
Then calculate the normalization matrix by dividing the value of each column by the number of related columns in Table 17.
The normalization of this pairwise comparison matrix aims to make all values equal.
The normalization data can be seen in Table 17.
Table 17.
Normalization of the assurance subcriteria matrix
Subcriteria
0,143
0,154
0,130
0,125
0,429
0,462
0,522
0,375
0,286
0,231
0,261
0,375
0,143
0,154
0,087
0,125
Total Empathy sub-criteria weight value Calculating the weight value of the Responsiveness sub-criteria.
The first thing to do is create a comparison matrix for the Responsiveness sub-criteria in Table 18.
Table 18.
Paired comparison matrix for Empathy sub-criteria
Sub criteria
0,333
0,25
Calculating the weight value of the empathy sub-criteria.
The first thing to do is create a comparison matrix for the empathy sub-criteria in Table 18.
Then calculate the normalization matrix by dividing the value of each column by the number of related columns in Table 19.
Normalization is used for the process of changing data into a standard or 'normal' form to facilitate data processing and Table 19 shows that each variable has selected sub-criteria.
These selected criteria are based on the largest serqual weight value in each variable.
Sub-criteria A4 represents Tangible.
B2 represents Reability.
C1 represents Responsive.
D1 represents Assurance, and E3 for empathy.
NO.
Code Table 19.
Normalization of the empathy sub-criteria matrix
Main
Sub
Final
ServQual
ServQual
Criteria
Criteria
Weight
TerBobot Weight
Weight
Criteria
0,190
0,293
0,056
-0,31
-0,017
0,190
0,271
0,052
-0,32
-0,016
0,190
0,240
0,046
-0,32
-0,015
0,190
0,247
0,047
-0,43
-0,020
(%) Ranking ISSN 2087-3336 (Prin.
| 2721-4729 (Onlin.
DOI 10.
37373/tekno.
Total
0,232
0,232
0,232
0,232
0,192
0,192
0,192
0,192
0,204
0,204
0,204
0,204
0,229
0,229
0,229
0,229
0,243
0,315
0,243
0,247
0,303
0,249
0,244
0,237
0,242
0,242
0,276
0,254
0,279
0,253
0,263
0,238
0,056
0,073
0,056
0,057
0,058
0,048
0,047
0,045
0,049
0,049
0,056
0,052
0,064
0,058
0,060
0,055
1,086
-0,44
-0,79
-0,39
-0,17
-1,17
-0,53
-0,38
-0,28
-1,95
-0,37
-0,21
-0,41
-0,38
-0,26
-1,42
-1,38
-0,025
-0,058
-0,022
-0,010
-0,068
-0,025
-0,018
-0,013
-0,096
-0,018
-0,012
-0,021
-0,024
-0,015
-0,086
-0,076
-0,655
Calculation of weighted servqual values.
This Servqual value is the GAP obtained from the difference between the respondent's perception of the quality of service received and the respondent's expectation of the quality of the existing service, then multiplied by the final weight so that a value will be obtained which will then be chosen, whichever is smallest first, which is prioritized for improving service quality.
The results of calculating the weighted servqual value can be seen in Table 20.
Table 20 shows that each variable has selected sub-criteria.
These selected criteria are based on the largest servqual Weight value in each Sub-criteria A4 represents Tangible.
B2 represents Reability.
C1 represents Responsive.
D1 represents Assurance, and E3 for Empathy.
NO.
Table 20.
Calculation results of weighted servqual and ranking values Main
Sub
Final
ServQual
Code Criteria
Criteria
Weight
ServQual
(%) Ranking TerBobot Weight
Weight
Criteria
0,190
0,293
0,056
-0,31
-0,017
0,190
0,271
0,052
-0,32
-0,016
0,190
0,240
0,046
-0,32
-0,015
0,190
0,247
0,047
-0,43
-0,020
0,232
0,243
0,056
-0,44
-0,025
0,232
0,315
0,073
-0,79
-0,058
0,232
0,243
0,056
-0,39
-0,022
0,232
0,247
0,057
-0,17
-0,010
0,192
0,303
0,058
-1,17
-0,068
0,192
0,249
0,048
-0,53
-0,025
0,192
0,244
0,047
-0,38
-0,018
0,192
0,237
0,045
-0,28
-0,013
0,204
0,242
0,049
-1,95
-0,096
0,204
0,242
0,049
-0,37
-0,018
0,204
0,276
0,056
-0,21
-0,012
0,204
0,254
0,052
-0,41
-0,021
0,229
0,279
0,064
-0,38
-0,024
0,229
0,253
0,058
-0,26
-0,015
0,229
0,263
0,060
-1,42
-0,086
0,229
0,238
0,055
-1,38
-0,076
Total
1,086
-0,655
Discussion 96 Niera Feblidiyanti Analysis of service quality on customer satisfaction using the service quality method and analytical hierarchy process The results of this study by study Wahid and Hasibuan .
, that with AHP significant criteria can be found that need to be improved.
This research has obtained priority criteria from each variable.
Each criterion can be said to be the cause of many customer complaints and requires corrective action.
The strategy to improve performance and maintain quality is to develop top priorities so that the basic elements of service that have been successfully implemented are maintained and focused on customer CONCLUSION Based on the results of research conducted using the Servqual and AHP methods, it can be concluded that the following are the factors for the level of analysis of service quality and the suitability between patient/customer expectations of the quality of health services.
Which causes many customer complaints.
Several factors the level of customer expectations.
From the Tangible criteria, the Weighted Servqual Value is -0.
From the Reliability criteria, the Weighted Servqual Value is 0.
From the Responsiveness criteria, the Weighted Servqual Value is -0.
From the Assurance criteria, the Weighted Servqual Value is -0.
From the Emphaty criteria, the Weighted Servqual Value is -0.
Service quality influences the satisfaction of outpatients and inpatients.
to increase customer satisfaction, based on calculations .
espondents, validity tests, reliability tests.
Servqual weight tests, and AHP sub-criteri.
, from the results of the analysis, namely by providing clear information, improving performance, and maintaining quality, to be further developed as a main priority so that The basic elements of service that have been successfully implemented are maintained and focused on customer desires.
REFERENCES