Description
In recent years, crisis of oil and global competition have become big problems for industries. Rising of oil prices in global market may affect Pertamina as an Indonesian oil industry to escalate gasoline price for transportation. However, psychologically increment of gasoline price causes customer requesting more attractive and effective service quality at gas station. For improving service performance, customer needs and customer satisfaction is necessary to be identified by conducting a survey.
JURNAL TEKNOLOGI, Edisi No. 3 Tahun XXI, September 2007, 240-246 ISSN 0215-1685
240
Analyzing Service Quality Of Pertamina Gas Station In Jabodetabek
Using Multivariate Analysis
Isti Surjandari
1
and Eric Darmawan
2
.
Industrial Engineering Department, Faculty of Engineering, University of Indonesia
UI Campus, Depok, 16424, Indonesia
E-mail:
1
[email protected]
2
dan [email protected]
Abstrak
Akhir-akhir ini, krisis minyak dunia dan persaingan globalisasi menjadi masalah besar bagi dunia
industri. Kenaikan harga minyak dunia di pasar global memaksa Pertamina sebagai produsen minyak
Indonesia untuk menaikkan harga bahan bakar untuk transportasi. Sebaliknya, kenaikan harga bahan
bakar secara psikologis akan menyebabkan konsumen meminta kualitas pelayanan SPBU (Stasiun
Pengisian Bahan Bakar Umum) yang lebih baik. Untuk meningkatkan pelayanan, maka, survey dilakukan
untuk mengidentifikasi kebutuhan dan kepuasan pelanggan. Survey dapat menjelaskan kebutuhan
konsumen di SPBU yang dapat dianalisa dengan analisis multivariat dan Importance Performance
Analysis. Importance Performance Diagram sebagai hasil dari Importance Performance Analysis
menunjukkan atribut pelayanan dan performa pelayanan yang diperlukan untuk ditingkatkan kualitasnya
agar dapat memnuhi kebutuhan pelanggan. Setelah itu, House of Quality sebagai dasar Quality Function
Deployment didesain untuk memastikan bahwa kebutuhan konsumen yang utama telah diprioritaskan dan
diatur secara akurat. Dalam hal ini, pembuatan House of Quality berdasarkan strategi dan kemampuan
perusahaan. Hasil dari studi ini diharapkan dapat membantu Pertamina untuk meningkatkan performa
pelayanan dan kepuasan pelanggan.
Kata kunci: Kepuasan pelanggan , SPBU, analisa multivariat, peta persepsi dan rumah kualitas.
Abstract
In recent years, crisis of oil and global competition have become big problems for industries. Rising
of oil prices in global market may affect Pertamina as an Indonesian oil industry to escalate gasoline
price for transportation. However, psychologically increment of gasoline price causes customer
requesting more attractive and effective service quality at gas station. For improving service
performance, customer needs and customer satisfaction is necessary to be identified by conducting a
survey. This survey which will describe customer needs of gas station will be analyzed using Multivariate
Analysis and Importance Performance Analysis. Importance Performance Diagram as a result of
Importance Performance Analysis displays the service attributes and service performance that required
to be improved to fulfill customer needs. Afterwards, House of Quality as the basis of Quality Function
Deployment is designed to verify that prominence customer needs have been prioritized and managed
accurately. In this study, the ‘House of Quality’ is based on company strategy and ability. This study is
hopefully able to help Pertamina to enhance its service performance and achieve its customer
satisfaction.
Keywords: Customer satisfaction, gas station, multivariate analysis, perceptual mapping and house of
quality.
1. Introduction
As consequences of globalization era,
many foreign investors invested in Indonesia
and made the competition in Indonesia
became more competitive. They were the
new competitors for local industries.
Anticipating its competition, local
companies developed the new strategists for
its products and services delivered to its
customer in order to win the fight against
their competitors.
Analyzing Service Quality Of Pertamina Gas Station In Jabodetabek Using Multivariate Analysis
JURNAL TEKNOLOGI, Edisi No. 3 Tahun XXI, September 2007, 240-246 241
Now, this situation is also faced by
Pertamina, although in the past Pertamina
controlled the gasoline sales in Indonesia.
By the oil and gas act number 22/2001, the
government of Indonesia opened the
downstream business of gasoline for private.
Its business related to manufacture,
transport, and deposit the gasoline in retail
market [1]. As a result, Pertamina has to
compete with private companies, especially
foreign companies in procurement of
gasoline in retail. It consists of
transportation sector and household sector.
Following the economic growth, the
gasoline consumption was increase.
Although in 2005 the gasoline price was
escalated significantly, demand of gasoline
is inelastic, means that the increment does
not decrease the gasoline consumption [2],
indeed the gasoline consumption in that year
still increase.
Growth of gasoline consumption will
enlarge the amount of gas station in
Indonesia. As there are big opportunities in
gas station business, many foreign investors
surely will crowd the competition. So that,
Pertamina must start to improve its gas
station in order to win the market. It is a big
challenge for Pertamina as it never has
experience in business competition of gas
station. Gas station is a service industry;
therefore the service quality for customer is
important. Customers are main assets for
companies [3]; consequently customer
satisfaction is a focus to be achieved by
Pertamina.
Customer satisfaction is feeling of
comfortable or disappointed that was
appeared after comparing the perception
with the expectation of product performance
[4]. The achievement of high customer
satisfaction awards the competitive
advantage for companies to win the
competition and elevate the market share.
Companies focus on high customer
satisfaction, because a customer who is very
satisfied hardly changes its decision [5].
Moreover, he will promote the product and
its services to his relatives mouth to mouth
and disinterest with competitors.
For achieving the customer satisfaction,
Pertamina has to synchronize the customer
expectation with service performance
delivered by the product. However, many
companies created the value gap as they
failed to match the brand value and customer
value [6]. There are two steps which can be
operated by Pertamina to improve the
customer satisfaction. The first step is
identifying the customer characteristics,
which is can be described by multivariate
data analysis consisting of factor analysis,
discriminant analysis, and multiple
regression analysis. Survey has to be
conducted to obtain the information of
customer perception.
The second step, Pertamina do the
measurement of customer satisfaction with
importance-performance analysis. With
those steps, the company is able to evaluate
the customer satisfaction compared with its
service performance. Suited with its ability
and put side by side with other companies,
Quality Function Deployment (QFD)
analysis and House of Quality (HOQ) can be
performed. After that, Pertamina is able to
decide the next step to improve its customer
satisfaction by matching the service with the
customer needs.
2. Methods
For knowing the service quality and
customers’ satisfaction of Pertamina Gas
Station, questionnaire was designed and
distributed as a media to collect primary
data.
From the data processing phase, it was
collected data about customers’
characteristics, customers’ importance level
and customers’ satisfaction of Pertamina
Gas Station. There were 15 customers’
characteristics of Pertamina which were
consisted of customers’ demographic and
customers’ knowledge. On the other hand,
there are 26 service attributes that
questioned to the respondents.
The data that had been collected was
processed by multivariate data analysis.
Multivariate data analysis is a statistical
method to process several measurements
related individual or several objects
simultaneously [7]. Discriminant analysis is
I. Surjandari and E. Darmawan
242 JURNAL TEKNOLOGI, Edisi No. 3 Tahun XXI, September 2007, 240-246
a statistical technique for grouping
dependent variable based on independent
variables. The main purpose of discriminant
analysis is classified the customers of
Pertamina Gas Station based on theirs
satisfaction with the Pertamina service
quality. As a result, the characteristic of
customers and expectation of customers can
be identified.
Factor analysis is a statistical procedure
used to simplify data by classifying a large
number of data into some factors based on
its correlation. The main purpose of factor
analysis was simplifying data about
customers’ satisfaction by grouping of
service attributes into some factors. In this
research, factor analysis was used to classify
26 service attributes into 6 service factors
based on customers’ satisfaction. After 6
service factors was recognized, multiple
regression analysis was executed. This
analysis purpose was identifying the
correlation each service factors with the
service performance of Pertamina Gas
Station. With the regression analysis, the
weight of service factors related with
customers’ satisfaction could be identified.
Afterward, importance-performance
diagram was designed to show the position
of each service factors and also the position
of each service attributes by comparing the
importance level and performance level. The
factors were the service factors formed by
the analysis factor. Then perceptual mapping
was also made and could be made with
many analyses such as factor analysis,
discriminant analysis, or correspond
analysis. In this research, perceptual
mapping was made by factor analysis. With
importance performance diagram and
perceptual mapping, the service attributes
that were very important to the customers
could be identified.
Quality Function Deployment or QFD is
a structured process for planning the design
of a new product or service or for
redesigning an existing one [8]. QFD first
emphasizes thoroughly understanding what
the customers’ wants or needs. Then those
customers’ wants are translated into
characteristics of the product or service [9].
The benefit of QFD process was QFD
shortens the design time and reduces the
costs of achieving product or service
introduction [10]. With QFD, characteristic
quality that is important and service level
that is needed to satisfy customers could be
identified. The main methods and tools from
QFD is House of Quality (HOQ). Building
the house of quality starts with analyzing
information about what the customer wants
explained in voice of customer table then
related with the characteristics of product
quality. HOQ diagram is able to develop the
suggestion to improve service quality of
Pertamina Gas Station appropriate with the
customers’ requirements.
3. Result and Discussion
After all of the information has been
collected by the questionnaire and the data
collection is enough, reliable, and valid, then
multivariate data analysis can be processed.
In this research, the data processing used
SAS 9.1 software. Table 1 and table 2 are
the result of the discriminant analysis data
processing.
From the result of discriminant analysis
in table 1, type of gas station, age, and
residents of customers significantly affected
the customers’ satisfaction. Type of gas
station that had the highest discriminant
coefficients was able to discriminate the
customers’ satisfaction. Customers of
Pertamina Gas Station that had tried the
product of Non Pertamina Gas Station felt
less satisfied than the customers that had
never experienced with Shell or Petronas
services. Customers of Pertamina Gas
Station that had never tried Shell or Petronas
felt satisfied with the Pertamina services.
And from table 2, the reasons of customer
used Shell Gas Station or Petronas Gas
Station were because they wanted faster
service time, better accuracy of change and
octane quality contained in gasoline.
Data processing with factor analysis
produces six service factors that simplified
26 service attributes. The simplification into
six factors was based on the highest score of
factor loadings among the attributes. Table 3
shows the six service factors affected the
Analyzing Service Quality Of Pertamina Gas Station In Jabodetabek Using Multivariate Analysis
JURNAL TEKNOLOGI, Edisi No. 3 Tahun XXI, September 2007, 240-246 243
customers’ satisfaction of Pertamina Gas
Station. Afterward, the regression
coefficients that is generated by multiple
regression analysis in table 4, explained the
affection of service factors. The regression
equation is:
Satisfaction =2,78 +0,15×factor1 +
0,34×factor2 +0,32×factor3 +0,37×factor4
+0,26×factor5 – 0,01×factor6
Table 1.
Discriminant Analysis of Customer
Characteristics
Variable p-value
Discriminant
Coefficient 1
Discriminant
Coefficient 2
Type of Gas
Station
0.0103 -1,400695246 1,51283657
Age 0.0059 0,520158789 0,478845579
Residents 0.0026 0,365142637 0,223624007
Table 2.
Discriminant Analysis of Gas Station Types
Variable p-value
Discriminant
Coefficient
Service Time 0.0450 0,869521675
Precise Change 0.0402 -0,842906929
Accuracy of
Gasoline Octane
0.0242 1,066804221
Table 3.
Service Factors of Pertamina Gas Station
Variable Factors Name
Factor1 Supporting Facility of Gas Station
Factor2 Product Service of Gas Station
Factor3 Appearance of Gas Station
Factor4 Service Time of Gas Station
Factor5 Main Facility of Gas Station
Factor6 Location of Gas Station
Table 4.
Result of Multiple Regression Analysis
Variable
Parameter
Estimate
p-value
Intercept
2,77586
In recent years, crisis of oil and global competition have become big problems for industries. Rising of oil prices in global market may affect Pertamina as an Indonesian oil industry to escalate gasoline price for transportation. However, psychologically increment of gasoline price causes customer requesting more attractive and effective service quality at gas station. For improving service performance, customer needs and customer satisfaction is necessary to be identified by conducting a survey.
JURNAL TEKNOLOGI, Edisi No. 3 Tahun XXI, September 2007, 240-246 ISSN 0215-1685
240
Analyzing Service Quality Of Pertamina Gas Station In Jabodetabek
Using Multivariate Analysis
Isti Surjandari
1
and Eric Darmawan
2
.
Industrial Engineering Department, Faculty of Engineering, University of Indonesia
UI Campus, Depok, 16424, Indonesia
E-mail:
1
[email protected]
2
dan [email protected]
Abstrak
Akhir-akhir ini, krisis minyak dunia dan persaingan globalisasi menjadi masalah besar bagi dunia
industri. Kenaikan harga minyak dunia di pasar global memaksa Pertamina sebagai produsen minyak
Indonesia untuk menaikkan harga bahan bakar untuk transportasi. Sebaliknya, kenaikan harga bahan
bakar secara psikologis akan menyebabkan konsumen meminta kualitas pelayanan SPBU (Stasiun
Pengisian Bahan Bakar Umum) yang lebih baik. Untuk meningkatkan pelayanan, maka, survey dilakukan
untuk mengidentifikasi kebutuhan dan kepuasan pelanggan. Survey dapat menjelaskan kebutuhan
konsumen di SPBU yang dapat dianalisa dengan analisis multivariat dan Importance Performance
Analysis. Importance Performance Diagram sebagai hasil dari Importance Performance Analysis
menunjukkan atribut pelayanan dan performa pelayanan yang diperlukan untuk ditingkatkan kualitasnya
agar dapat memnuhi kebutuhan pelanggan. Setelah itu, House of Quality sebagai dasar Quality Function
Deployment didesain untuk memastikan bahwa kebutuhan konsumen yang utama telah diprioritaskan dan
diatur secara akurat. Dalam hal ini, pembuatan House of Quality berdasarkan strategi dan kemampuan
perusahaan. Hasil dari studi ini diharapkan dapat membantu Pertamina untuk meningkatkan performa
pelayanan dan kepuasan pelanggan.
Kata kunci: Kepuasan pelanggan , SPBU, analisa multivariat, peta persepsi dan rumah kualitas.
Abstract
In recent years, crisis of oil and global competition have become big problems for industries. Rising
of oil prices in global market may affect Pertamina as an Indonesian oil industry to escalate gasoline
price for transportation. However, psychologically increment of gasoline price causes customer
requesting more attractive and effective service quality at gas station. For improving service
performance, customer needs and customer satisfaction is necessary to be identified by conducting a
survey. This survey which will describe customer needs of gas station will be analyzed using Multivariate
Analysis and Importance Performance Analysis. Importance Performance Diagram as a result of
Importance Performance Analysis displays the service attributes and service performance that required
to be improved to fulfill customer needs. Afterwards, House of Quality as the basis of Quality Function
Deployment is designed to verify that prominence customer needs have been prioritized and managed
accurately. In this study, the ‘House of Quality’ is based on company strategy and ability. This study is
hopefully able to help Pertamina to enhance its service performance and achieve its customer
satisfaction.
Keywords: Customer satisfaction, gas station, multivariate analysis, perceptual mapping and house of
quality.
1. Introduction
As consequences of globalization era,
many foreign investors invested in Indonesia
and made the competition in Indonesia
became more competitive. They were the
new competitors for local industries.
Anticipating its competition, local
companies developed the new strategists for
its products and services delivered to its
customer in order to win the fight against
their competitors.
Analyzing Service Quality Of Pertamina Gas Station In Jabodetabek Using Multivariate Analysis
JURNAL TEKNOLOGI, Edisi No. 3 Tahun XXI, September 2007, 240-246 241
Now, this situation is also faced by
Pertamina, although in the past Pertamina
controlled the gasoline sales in Indonesia.
By the oil and gas act number 22/2001, the
government of Indonesia opened the
downstream business of gasoline for private.
Its business related to manufacture,
transport, and deposit the gasoline in retail
market [1]. As a result, Pertamina has to
compete with private companies, especially
foreign companies in procurement of
gasoline in retail. It consists of
transportation sector and household sector.
Following the economic growth, the
gasoline consumption was increase.
Although in 2005 the gasoline price was
escalated significantly, demand of gasoline
is inelastic, means that the increment does
not decrease the gasoline consumption [2],
indeed the gasoline consumption in that year
still increase.
Growth of gasoline consumption will
enlarge the amount of gas station in
Indonesia. As there are big opportunities in
gas station business, many foreign investors
surely will crowd the competition. So that,
Pertamina must start to improve its gas
station in order to win the market. It is a big
challenge for Pertamina as it never has
experience in business competition of gas
station. Gas station is a service industry;
therefore the service quality for customer is
important. Customers are main assets for
companies [3]; consequently customer
satisfaction is a focus to be achieved by
Pertamina.
Customer satisfaction is feeling of
comfortable or disappointed that was
appeared after comparing the perception
with the expectation of product performance
[4]. The achievement of high customer
satisfaction awards the competitive
advantage for companies to win the
competition and elevate the market share.
Companies focus on high customer
satisfaction, because a customer who is very
satisfied hardly changes its decision [5].
Moreover, he will promote the product and
its services to his relatives mouth to mouth
and disinterest with competitors.
For achieving the customer satisfaction,
Pertamina has to synchronize the customer
expectation with service performance
delivered by the product. However, many
companies created the value gap as they
failed to match the brand value and customer
value [6]. There are two steps which can be
operated by Pertamina to improve the
customer satisfaction. The first step is
identifying the customer characteristics,
which is can be described by multivariate
data analysis consisting of factor analysis,
discriminant analysis, and multiple
regression analysis. Survey has to be
conducted to obtain the information of
customer perception.
The second step, Pertamina do the
measurement of customer satisfaction with
importance-performance analysis. With
those steps, the company is able to evaluate
the customer satisfaction compared with its
service performance. Suited with its ability
and put side by side with other companies,
Quality Function Deployment (QFD)
analysis and House of Quality (HOQ) can be
performed. After that, Pertamina is able to
decide the next step to improve its customer
satisfaction by matching the service with the
customer needs.
2. Methods
For knowing the service quality and
customers’ satisfaction of Pertamina Gas
Station, questionnaire was designed and
distributed as a media to collect primary
data.
From the data processing phase, it was
collected data about customers’
characteristics, customers’ importance level
and customers’ satisfaction of Pertamina
Gas Station. There were 15 customers’
characteristics of Pertamina which were
consisted of customers’ demographic and
customers’ knowledge. On the other hand,
there are 26 service attributes that
questioned to the respondents.
The data that had been collected was
processed by multivariate data analysis.
Multivariate data analysis is a statistical
method to process several measurements
related individual or several objects
simultaneously [7]. Discriminant analysis is
I. Surjandari and E. Darmawan
242 JURNAL TEKNOLOGI, Edisi No. 3 Tahun XXI, September 2007, 240-246
a statistical technique for grouping
dependent variable based on independent
variables. The main purpose of discriminant
analysis is classified the customers of
Pertamina Gas Station based on theirs
satisfaction with the Pertamina service
quality. As a result, the characteristic of
customers and expectation of customers can
be identified.
Factor analysis is a statistical procedure
used to simplify data by classifying a large
number of data into some factors based on
its correlation. The main purpose of factor
analysis was simplifying data about
customers’ satisfaction by grouping of
service attributes into some factors. In this
research, factor analysis was used to classify
26 service attributes into 6 service factors
based on customers’ satisfaction. After 6
service factors was recognized, multiple
regression analysis was executed. This
analysis purpose was identifying the
correlation each service factors with the
service performance of Pertamina Gas
Station. With the regression analysis, the
weight of service factors related with
customers’ satisfaction could be identified.
Afterward, importance-performance
diagram was designed to show the position
of each service factors and also the position
of each service attributes by comparing the
importance level and performance level. The
factors were the service factors formed by
the analysis factor. Then perceptual mapping
was also made and could be made with
many analyses such as factor analysis,
discriminant analysis, or correspond
analysis. In this research, perceptual
mapping was made by factor analysis. With
importance performance diagram and
perceptual mapping, the service attributes
that were very important to the customers
could be identified.
Quality Function Deployment or QFD is
a structured process for planning the design
of a new product or service or for
redesigning an existing one [8]. QFD first
emphasizes thoroughly understanding what
the customers’ wants or needs. Then those
customers’ wants are translated into
characteristics of the product or service [9].
The benefit of QFD process was QFD
shortens the design time and reduces the
costs of achieving product or service
introduction [10]. With QFD, characteristic
quality that is important and service level
that is needed to satisfy customers could be
identified. The main methods and tools from
QFD is House of Quality (HOQ). Building
the house of quality starts with analyzing
information about what the customer wants
explained in voice of customer table then
related with the characteristics of product
quality. HOQ diagram is able to develop the
suggestion to improve service quality of
Pertamina Gas Station appropriate with the
customers’ requirements.
3. Result and Discussion
After all of the information has been
collected by the questionnaire and the data
collection is enough, reliable, and valid, then
multivariate data analysis can be processed.
In this research, the data processing used
SAS 9.1 software. Table 1 and table 2 are
the result of the discriminant analysis data
processing.
From the result of discriminant analysis
in table 1, type of gas station, age, and
residents of customers significantly affected
the customers’ satisfaction. Type of gas
station that had the highest discriminant
coefficients was able to discriminate the
customers’ satisfaction. Customers of
Pertamina Gas Station that had tried the
product of Non Pertamina Gas Station felt
less satisfied than the customers that had
never experienced with Shell or Petronas
services. Customers of Pertamina Gas
Station that had never tried Shell or Petronas
felt satisfied with the Pertamina services.
And from table 2, the reasons of customer
used Shell Gas Station or Petronas Gas
Station were because they wanted faster
service time, better accuracy of change and
octane quality contained in gasoline.
Data processing with factor analysis
produces six service factors that simplified
26 service attributes. The simplification into
six factors was based on the highest score of
factor loadings among the attributes. Table 3
shows the six service factors affected the
Analyzing Service Quality Of Pertamina Gas Station In Jabodetabek Using Multivariate Analysis
JURNAL TEKNOLOGI, Edisi No. 3 Tahun XXI, September 2007, 240-246 243
customers’ satisfaction of Pertamina Gas
Station. Afterward, the regression
coefficients that is generated by multiple
regression analysis in table 4, explained the
affection of service factors. The regression
equation is:
Satisfaction =2,78 +0,15×factor1 +
0,34×factor2 +0,32×factor3 +0,37×factor4
+0,26×factor5 – 0,01×factor6
Table 1.
Discriminant Analysis of Customer
Characteristics
Variable p-value
Discriminant
Coefficient 1
Discriminant
Coefficient 2
Type of Gas
Station
0.0103 -1,400695246 1,51283657
Age 0.0059 0,520158789 0,478845579
Residents 0.0026 0,365142637 0,223624007
Table 2.
Discriminant Analysis of Gas Station Types
Variable p-value
Discriminant
Coefficient
Service Time 0.0450 0,869521675
Precise Change 0.0402 -0,842906929
Accuracy of
Gasoline Octane
0.0242 1,066804221
Table 3.
Service Factors of Pertamina Gas Station
Variable Factors Name
Factor1 Supporting Facility of Gas Station
Factor2 Product Service of Gas Station
Factor3 Appearance of Gas Station
Factor4 Service Time of Gas Station
Factor5 Main Facility of Gas Station
Factor6 Location of Gas Station
Table 4.
Result of Multiple Regression Analysis
Variable
Parameter
Estimate
p-value
Intercept
2,77586