ANALYSIS OF FACTORS
AFFECTING CUSTOMER SATISFACTION ON PLN MOBILE USERS AT PLN TANJUNGPANDAN
CUSTOMER SERVICE UNIT
Arief Kusuma Aji
Institut Teknologi PLN,
Jakarta, Indonesia
|
KEYWORDS |
ABSTRACT |
|
customer satisfaction, customer service, multiple
linear regression, PLN mobile application. |
The PLN Mobile application is an application that
can be used by smartphone devices that aim to provide services for PLN
customers through digital media. The presence of the PLN mobile application
is expected to increase customer satisfaction. This study aims to determine
customer satisfaction factors, especially for PLN Mobile Application users.
This study uses five variables, namely application reliability, interface
display, complaints menu, and service response speed as independent
variables, and customer satisfaction as the dependent variable, using
multiple linear regression analysis. The method used in the study is using multiple
linear regression. The
results showed that the four independent variables could explain 93.4% of the
dependent variable. In contrast, the remaining 6.6% was explained by other
variables not included in this study. The independent variables X1 and X3
partially affect the dependent variable Y. In contrast, the independent
variables X2 and X4 do not partially affect the dependent variable Y. The
four independent variables together influence customer satisfaction
variables. The empirical results of this study are higher level of
application reliability and complaint menu, the higher the costumer
satisfaction of PLN Mobile users. |
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DOI: 10.58860/ijsh.v2i3.28 |
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Corresponding Author: Arief Kusuma Aji
Email: arief2010015@itpln.ac.id
INTRODUCTION
Human needs are always evolving,
including in terms of technology, and the world of service is no exception (Sitompul,
2017). Real examples that have
been seen are transportation, ordering tickets, ordering food, and so on (Sheikh
& van Ameijde, 2022). This phenomenon is an important concern for various large companies in
Indonesia, and PLN is no exception (Fathoni & Setyowati, 2022). As a company engaged in the electricity sector, PLN
plays a very important role in serving the community in carrying out their
daily lives and must be able to adapt to the needs of these technological
developments (Putri, 2011). On the other hand, PLN must also pay attention to
the level of customer satisfaction so that revenue is maintained. For
example, in the Bangka Belitung Regional Main Unit (UIW) PLN, the SKP scores
for 2018, 2019, and 2020 were 99.22%, 99.25%, and 98.23%, meaning that for the
last three consecutive years, the level of satisfaction PLN UIW Bangka Belitung
subscribers are at a satisfactory rate. These figures will become PLN's
reference for evaluating service quality, including what strategies to prepare
in the future. One of the strategies to improve PLN's service quality is to
present an application called PLN Mobile. This application will make accessing
their needed services easier for PLN customers. In 2021, PLN sets several downloaders
of the PLN Mobile application as a company performance item. This shows PLN's
seriousness in improving services and using digital media as a communication
portal in addition to the plan. Co.id website and pre-existing social media.
The PLN Mobile application is a challenge for PLN, where customer
satisfaction with existing services will also be affected by the presence of
these digital services. Customer satisfaction has the meaning of feeling happy
or disappointed from someone who appears after comparing products or services
from what they think with what they expect (Susanthi, 2011). For some people who follow technological developments, the presence of
this application will be very helpful and means that smartphone users can
accept it to implement the PLN Mobile application (NADHIF, 2018). Several previous studies have measured the
relationship between the level of customer satisfaction and conventional
service factors so that development can still be carried out in more detail by
looking at the various factors that affect customer satisfaction on the
technology side and on the customer trust side (Pambudi & Soliha, 2022). This study will analyze the relationship between
factors on the technology side, in this case, the use of the PLN Mobile
application, about the level of satisfaction felt by PLN customers. This is
useful so that an evaluation can be carried out on the presence of the
application in society in general and PLN customers. The
benefits of this research are to contribute the development of science related
to the level of customer satisfaction on PLN Mobile users. It also useful to
provide recommendation for PLN Management in evaluate their programs on PLN
Mobile application.
From 2021 until December 1, 2021, PLN's Tanjungpandan Customer Service
Unit received 8,773 reports of disturbances and complaints that have been
received and have been followed up on (source: PLN APKT EIS Web application),
of which 5,891 were reported via the PLN Mobile application (source: Web
application PLN Virtual Command Center).
This shows the level of use of PLN Mobile to report disturbances and
complaints at 67.15%. This figure is quite high considering that the PLN Mobile
application has only recently been introduced to the public, and can still grow
in 2022 in line with the increasingly massive marketing of PLN Mobile products.
From these conditions, it is necessary to know the factors influencing
customer satisfaction with PLN services, including those provided using the PLN
Mobile application. Several factors are used to examine the level of customer
satisfaction with using the PLN Mobile application in this study: application
reliability, interface display, complaints menu, and service response speed. So
the purpose of this research is to analyze the factors that influence customer
satisfaction of mobile PLN users at the PLN Tanjungpandan customer service
unit.
METHODS
Based on the literature review and
the previous research concepts, a research concept was created to develop
hypotheses for each variable related to customer satisfaction.
Figure 1. Research Concept
All variables are measured using a Likert scale. Each
variable is hypothesized based on a literature review in the form of a
theoretical basis or previous research. The hypothesis is made to test the
effect of the independent variable on the dependent variable, considering the
coefficient of influence and the significance level. This study's analysis method
is a multiple linear regression method. This method is often chosen in research that using multiple factors affecting
one dependant variable. It also can predict the value of dependant variable when all the
independent variable has its values. This is done to know the
relationship between two or more independent variables with one dependent
variable (Triyanto et al., 2019).
From the theory of customer satisfaction and consumer
behavior, as well as previous research on factors that can influence customer
satisfaction, five hypotheses are compiled with the following details:
|
H1 |
: |
Application
reliability has a positive and significant effect on customer satisfaction of
PLN Mobile users at the PLN Tanjungpandan customer service unit. |
|
H2 |
: |
The
interface display positively and significantly affects customer satisfaction
using the PLN Mobile Application at the PLN Tanjungpandan customer service
unit. |
|
H3 |
: |
The
complaint menu positively and significantly affects customer satisfaction
using the PLN Mobile Application at the PLN Tanjungpandan customer service
unit. |
|
H4 |
: |
Service
response speed positively and significantly affects customer satisfaction
using the PLN Mobile Application at the PLN Tanjungpandan customer service
unit. |
|
H5 |
: |
Application
reliability, interface display, complaints menu, and service response speed
significantly affect customer satisfaction using the PLN Mobile Application
at the PLN Tanjungpandan customer service unit. |
The research was held in the work environment of PT PLN Tanjungpandan
Service Unit; in the customer segment, all tariff groups were spread out in the
Belitung Regency area. At the same time, the time for research starts from the
preparation stage in the form of submitting titles in May 2022, topic
consultations in early June 2022, and reference collection and data processing
in June - July 2022.
In general,
the steps taken in this study are shown in the following diagram:
Figure 2. Flowchart of the
research process
The method
used to collect data as material for this study was a questionnaire distributed
to PLN customers in Belitung Regency. The expected minimum sample size is 100
respondents. Data processing was performed using SPSS software version 26.
Several series of tests were carried out prior to multiple linear regression
analysis.
RESULTS
AND DISCUSSION
The following data collection results
were obtained from the distribution of the research questionnaire conducted in
July 2022.
Table 1. Results of data collection
|
Information |
Amount |
Percentage |
|
Number of respondents |
100 |
100% |
|
Valid questionnaire |
100 |
100% |
|
Invalid questionnaire |
0 |
0% |
|
Gender |
Frequency |
Percentage |
|
Man |
92 |
92% |
|
Woman |
8 |
8% |
|
Total |
100 |
100% |
|
Age |
Frequency |
Percentage |
|
< 23 years |
6 |
6% |
|
23 29 years |
35 |
35% |
|
30 40 years |
36 |
36% |
|
> 40 years |
23 |
23% |
From
the results of distributing the questionnaires, data were obtained from 100
respondents who were all customers of PT PLN (Persero) ULP Tanjungpandan. The
sexes who filled out the questionnaire had details of 92 males and eight
females. It can be concluded that most of the respondents were male. The age
range of respondents who inputted the questionnaire was spread with details of
under 23 years of age 6%, ages 23-29 years of 35%, ages 30-40 years of 36%, and
ages > 40 years of 23%. It can be concluded that respondents were dominated
by customers aged 30-40.
The distribution of questionnaires
provides quite diverse data. The results obtained are tabulated in the data and
processed more deeply using the SPSS v26 software. Before conducting regression
analysis, it is necessary to carry out a series of tests such as instrument
validity and reliability tests, descriptive analysis, correlation tests, and
classical assumption tests. Furthermore, multiple linear regression analysis
was carried out by paying attention to the partial t-test, simultaneous F test,
and coefficient of determination. SPSS data processing results provide analysis
and conclusions on the variables that have been determined.
Regression Equation Analysis
Table 2. Regression Equation
|
Variable |
Regression
Coefficient |
T count |
Sig |
|
Constant |
-0.115 |
|
|
|
X 1 |
1,181 |
12,849 |
0.000 |
|
X 2 |
0.106 |
1,497 |
0.138 |
|
X 3 |
0.102 |
2,805 |
0.006 |
|
X 4 |
0.036 |
0.517 |
0.607 |
The regression equation that can be concluded from the table above is:
Y = -0.115 + 1.181 X1 + 0.106X2 + 0.102X3 + 0.036X
4 + e
From the regression equation
obtained, the following conclusions can be drawn:
The constant
-0.115 means that if all X variables, namely application reliability, interface
display, complaints menu, and service response speed, are considered 0 (zero)
or ignored, customer satisfaction will decrease.
Application
Reliability Variable (X1) positively and significantly influences customer
satisfaction with a coefficient of 1.181 and a significance of 0.000. This can
mean customer satisfaction will increase if the interface display variables,
complaints menu, and service response speed are ignored or considered 0 (zero).
The level of significance also indicates that these variable influences
customer satisfaction. This is because the PLN Mobile Application is a
technology that brings PLN together with customers. So that if the application
on a smartphone device runs smoothly, it will increase customer satisfaction.
Conversely,
suppose the application does not work properly and correctly. In that case, it
could reduce the level of customer satisfaction. This is consistent with
previous research that electronic service quality positively and significantly
affects customer satisfaction, with a coefficient of 0.954 and a significance
level of 0.000 (Hidayati,
2018).
This means that the reliability of an application system is needed to increase
customer satisfaction.
Interface
Display Variable (X2) positively influences customer satisfaction with a
regression coefficient of 0.106 and a significance of 0.138. This means that if
the variable application reliability, complaints menu, and service response
speed are ignored or considered 0 (zero), then customer satisfaction will
increase. The regression coefficient value also shows that an attractive and
easy-to-use application appearance contributes to the level of customer
satisfaction of PLN Mobile Application users. Compared to previous research,
the relationship between the implementation of information technology and
customer satisfaction was obtained in the form of a negative effect with a
coefficient of -0.890 and a significance level of 0.081 (Putria,
2018).
Interface display on application is one part of communication system between
companies and customers. Customer relationship management has no significant
effect on corporate image of PLN East Java (Priyatna & Utomo, 2021). The
appearance of the application and implementation of information technology in
the service world does not fully affect customer satisfaction.
Complaint Menu Variable (X3)
positively and significantly influences customer satisfaction with a
coefficient of 0.102 and a significance of 0.006. This means that customer
satisfaction will also increase if other variables, namely application
reliability, interface appearance, and service response speed are ignored or
considered 0 (zero). This variable's regression coefficient and significance
level also show that the Complaints Menu in the PLN Mobile application affects
customer satisfaction. In line with these results, previous research on the
relationship between complaints to customer satisfaction also explains that
there is a positive and significant effect with a coefficient of 0.206 and a
significance of 0.208 (Syahputra
et al., 2020). At PLN
Siborongborong Sibolga, there was a also significant relationship between
service quality and customer satisfaction (Sinaga & Sinaga, 2021). This is because PLN's
services in the electricity sector are always related to the consumption of
electrical energy used by customers. Any complaints, both disturbances and
customer complaints, can be resolved using the PLN Mobile Application.
The service response speed variable
(X4) positively influences customer satisfaction with a regression coefficient
of 0.036 and a significance of 0.607. This means customer satisfaction will
increase if other variables, namely application reliability, interface display,
and complaints menu, are ignored or considered 0 (zero). The regression
coefficient on this variable also shows that the service response speed
influences customer satisfaction. The faster the service is provided through
the PLN Mobile Application; the more customer satisfaction will increase. In
line with these results, previous research on the relationship between service
quality and customer satisfaction also explained a positive and significant
effect with a coefficient of 0.575 and a significance of 0.000 (Ramenusa,
2013). Service
quality also has a significant influence on customer satisfaction in PLN Tais
Seluma District with t-count is greater than t-table (2.227 > 1.677)
(Perianto et. al., 2021). This shows that the quality of service, one of which is the
speed of response, is very important in customer service.
Determinant Coefficient
The
determinant coefficient shows how far or how big a model is in explaining
variations in the dependent variable. The value of the coefficient of
determination is in the range of 0 (zero) and 1 (one). The value of the
determinant coefficient close to one means that the independent variable
increasingly provides the information needed to estimate the dependent
variable.
The results of the Determinant
Coefficient test are shown in the following table.
Table 3. The coefficient of determination
|
R Square |
Adjust R Square |
std. The error in the Estimate |
|
0937 |
0.934 |
0.18910 |
In the results of the Determinant Coefficient
test above, R2 (R Square) is 0.934. This explains the percentage of information
provided by the variable Application Reliability, Interface Display, Complaints
Menu, and Service Response Speed is 93.4%. In other words, the variation of the
independent variables used in the model can explain the dependent variable by
93.4%. In comparison, the remaining 6.6% is influenced by other variables not
present in this study.
Partial Test and Simultaneous Test
Hypothesis
testing consists of two types: Partial Test (Test statistic t) and Simultaneous
Test (Test statistic F). The t-statistical test shows how much the independent
variables affect the dependent variable individually.
Table 4. Statistical test t
|
Variable |
Sig. |
conclusion |
|
Application Reliability (X1) |
0.000 |
H1 is accepted; there is a partial effect of
X1 on Y |
|
Interface Display (X2) |
0.138 |
H1 is rejected; there is no partial effect of
X2 on Y |
|
Complaint Menu (X3) |
0.006 |
H1 is accepted; there is a partial effect of
X3 on Y |
|
Service Response Speed (X4) |
0.607 |
H1 is rejected; there is no partial effect of
X4 on Y |
The basis for
the decision to test the t statistic is that if the significance is <alpha
(0.05), the hypothesis is accepted, or in other words, there is a partial
influence between the two variables (Assagaf,
2020).
From the
results of the t-statistical test above, it can be concluded that the
Application Reliability Variable has a t value of 12,849 (> t table 1.988)
and a significance of 0.000 (<0.05). This means that the hypothesis is
accepted, and the Application Reliability variable (X1) has a partial influence
on Customer Satisfaction using PLN Mobile (Y). The Interface Display variable
has a t value of 1.497 (< t table 1.988) and a significance of 0.138 (>
0.05). This means that the hypothesis is rejected, and there is no effect of
the Interface Display variable (X2) on Customer Satisfaction using PLN Mobile
(Y) partially. The Interface Display variable has a t value of 2.805 (> t
table 1.988) and a significance of 0.006 (<0.05). This means that the
hypothesis is accepted, and the Complaint Menu variable (X3) has a partial
influence on Customer Satisfaction using PLN Mobile (Y). The service Response Speed
variable has a t value of 0.517 (<t table 1.988) and a significance of 0.607
(> 0.05). This means that the hypothesis is rejected, and there is no effect
of the Service Response Speed variable (X4) on Customer Satisfaction using PLN
Mobile (Y) partially.
Of the four
independent variables, only two (X1 and X3) individually influence the
dependent variable (Y). The other two independent variables (X2 and X4) do not
affect the dependent variable (Y). The F
statistic test shows how much the independent variables jointly affect the
dependent variable.
Table 5. Statistical Test F
|
Significance |
Alpha |
Conclusion |
|
0.000 |
0.005 |
The hypothesis is accepted, X1 - X4 simultaneously
affect Y |
The basis for the decision to test the F
statistic is that if the significance is <alpha (0.05), the hypothesis is
accepted, or in other words, there is an influence between the variables
together (Assagaf,
2020)
From the
results of the F statistical test above, the calculated F value is 352,719
(> F table 3.92). A significance level of 0.000 (<0.05), so it can be
concluded that the hypothesis is accepted, where the independent variables are
application reliability and performance. The interface, Complaint Menu, and
Service Response Speed Influence Customer Satisfaction with PLN Mobile users. All of this factor can lead the companies to achieve
profits. Higher companies profits could be achived by high customers
satisfaction (Wahyuningsih, 2021).
CONCLUSION
The Variables of Application
Reliability and Complaints Menu each partially influence Customer Satisfaction
using the PLN Mobile Application. The interface displays variable and Service
Response Speed do not partially affect Customer Satisfaction using the PLN
Mobile Application. The Variables of Application Reliability, Interface
Display, Complaints Menu, and Service Response Speed simultaneously influence
Customer Satisfaction using the PLN Mobile Application. The Application
Reliability Variable significantly influences Customer Satisfaction because
customer service applications installed on smartphones must be able to work
properly and smoothly. Meanwhile, the Complaints Menu variable significantly
influences customer satisfaction because customers really need media for both
disturbances and complaints that are fast and precise. The Interface Display
Variable has no significant effect on Customer Satisfaction because the
application's appearance is only limited to making the application look
attractive. The form of the service itself influences the rest. Meanwhile, the
Service Response Speed variable does not significantly affect Customer
Satisfaction because customers only expect disturbance reports or complaints
submitted to get an appropriate solution. At the same time, the service
response speed is not the main factor.
REFERENCES
Assagaf, A.
(2020). 29 model regresi aminullah assagaf.
Fathoni, H. S., & Setyowati, A. B. (2022). Energy
justice for whom? Territorial (re)production and everyday state-making in
electrifying rural Indonesia. Geoforum, 135, 4960.
https://doi.org/https://doi.org/10.1016/j.geoforum.2022.07.012
Hidayati, I. R. (2018). Pengaruh
Kepercayaan Pelanggan, Kualitas Pelayanan Elektronik, dan Promosi pada Aplikasi
PLN Mobile terhadap Kepuasan Pelanggan PT. PLN Distribusi Jawa Timur di
Surabaya. Universitas 17 Agustus 1945.
Nadhif, A. Z. (2018). Inovasi
Layanan Pln Mobile Di Pt. Pln (Persero) Area Surabaya Selatan. Publika, 6
(2). https://doi.org/10.26740/publika.v6n2.p%25p.
Pambudi, T., & Soliha, E. (2022). Pengaruh
Kualitas Layanan, Citra Bank, Dan Kepercayaan Terhadap Kepuasan Nasabah Bank. Fair
Value: Jurnal Ilmiah Akuntansi Dan Keuangan, 4 (Spesial Issue 3),
12671287.
Priyatna, N. M., & Utomo, A. (2021). Pengaruh
Supply Chain Management bagi Pelanggan Pasang Baru PT. PLN Surabaya Barat, Jawa
Timur. Seminar Keinsinyuran Program Studi Program Profesi Insinyur, 2
(1). https://doi.org/10.22219/skpsppi.v2i1.4429.
Putri, E. (2011). Strategi Peningkatan Kinerja
Karyawan Pt Pln Ranting Perawang Melalui Pendidikan Dan Pelatihan Ditinjau Dari
Persfektif Ekonomi Islam. Universitas
Islam Negeri Sultan Syarif Kasim Riau.
Putria, N. E. (2018). Pengaruh
Implementasi Teknologi Informasi Dan Kualitas Pelayanan Jasa Terhadap Kepuasan
Pelanggan Pada Pt. Pln Batam. Cbis, 1, 7796.
Ramenusa, O. (2013). Kualitas
Layanan Dan Kepuasan Pelanggan Pengaruhnya Terhadap Loyalitas Pelanggan Pada PT.
DGS Manado. Emba, 1 (3), 11931202.
https://doi.org/10.35794/emba.1.3.2013.2526
Sheikh, W. T., & van Ameijde,
J. (2022). Promoting livability through urban planning: A
comprehensive framework based on the theory of human needs. Cities, 131,
103972. https://doi.org/https://doi.org/10.1016/j.cities.2022.103972
Sinaga, R. L. D., & Sinaga, L. R. (2021). Effect
of Service Quality on Customer Satisfaction at PT. PLN (Persero) Rayon Siborong
Borong Sibolga Area. Jurnal Mantik, 4 (4), 25122516. https://doi.org/10.35335/mantik.Vol4.2021.1201.pp2512-2516
Sitompul, R. (2017). Pelayanan
Pemuda di Era Teknologi Digital. Jurnal Antusias, 5 (1), 116.
Susanthi, R. (2011). Analisis
Pengaruh Kualitas Pelayanan dan Nilai Pelanggan Terhadap Kepuasan Pelanggan.
Syahputra, D., Nawangsih, N.,
& Irwanto, J. (2020). Pengaruh Kepercayaan dan Komplain
terhadap Kepuasan Pelanggan di J&T Express Lumajang. Jobman
, 1724.
Triyanto, E., Sismoro, H., &
Laksito, A. D. (2019). Implementasi Algoritma Regresi Linear Berganda Untuk
Memprediksi Produksi Padi Di Kabupaten Bantul. Rabit: Jurnal Teknologi Dan
Sistem Informasi Univrab, 4 (2), 7386. https://doi.org/10.36341/rabit.v4i2.666
Wahyuningsih, S. (2021). Gaya Kepemimpinan &
Kinerja Organisasi. Penerbit NEM.
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