Analysis of the Effectiveness of Cashier Service with a Simulation of
the Queue System
Hery Murnawan
Department, Engineering of Faculty, Universitas 17 Agustus 1945 Surabaya, Surabaya, Indonesia
Keywords: Retail, Server, Efficiency, Customer, Arena.
Abstract: The highly competitive nature of the retail industry, especially in the daily household needs segment, is
influenced by various factors that impact consumer behaviour. These factors include product pricing,
availability, discounts, warranties, supporting facilities, and customer service. Trasmart and Superindo are
two major retailers that offer a complete range of products and frequently provide discounts and gifts to their
customers. However, customers experience dissatisfaction due to an average waiting time of 5 to 7 minutes
at their six servers, which may result in cancelled purchases. The Arena software simulation results indicate
that adding one server can reduce waiting time to 3.2 minutes per customer, at an additional cost of IDR
125,000 per day. Meanwhile, adding one server to Trasmart can decrease waiting time to 4.7 minutes per
customer, at an extra cost of IDR 142,000 per day. Alternatively, investing in cashier worker training, without
adding servers, can reduce waiting time to 3.8 minutes per customer in Superindo, with an investment cost of
IDR 3.4 million, and 3.5 minutes per customer, with an investment cost of IDR 4.1 million. In conclusion,
this research highlights the importance of efficient queuing systems and customer service in enhancing
customer satisfaction and retail profitability.
1 INTRODUCTION
We often see queuing problems happening around us,
for example, as queuing for services at Minimarkets,
refueling at POM, queuing when we want to cut hair
at a salon, queuing when making transactions at a
bank, or when we visit a shopping center, many
visitors waiting in line to make payment at the
cashier. Queuing certainly causes a sense of
saturation and boredom, or we must queue when
buying food at the street vendors, even annoyed the
queue, primarily if the column occurs for a long time
(Wei et al., 2017). Services are fast-paced and the
most sought-after economic place in people's lives
today (Keshanchi et al., 2017). However, we find
many queuing problems in the service sector because
the service sector has an irregular/random staff
(Bahadori et al., 2014). We can see that upon arrival,
or the services needed to serve customers in the
service sector.
The best service is to maximize service to
customers/consumers effectively so that there are no
long queues and consumers do not wait long and feel
satisfied with our services (Wei et al., 2017)
(Kierzkowski and Kisiel, 2017). Consumers
complain about our services whenever the service
must evaluate the system because of many problems.
Therefore, the service is updated at any time to make
consumer confidence in the service not disappointing
and will make consumers very happy if the service we
do is high-speed and effective (Tychalas and Karatza,
2020). This is important because those queuing for
services have different ages and fatigue levels. So,
consumers will feel less comfortable if there is always
a reasonably dense queue. Shopping centers for daily
needs are in more than just traditional markets, such
as supermarkets. Supermarkets play an essential role
in selling daily necessities. Supermarkets are ready to
serve consumers who need their daily needs, one of
which is Transmart Supermarket and Superindo in
Surabaya. The two supermarkets are ready to serve
consumers who need certain goods that do not exist
in traditional markets.
2 LITERATURE REVIEW
The waiting line (queue) is the number of queues in
the form of people/goods to be served (Pan et al.,
2015). Queues are a condition where the number of
Murnawan, H.
Analysis of the Effectiveness of Cashier Service with a Simulation of the Queue System.
DOI: 10.5220/0012113300003680
In Proceedings of the 4th International Conference on Advanced Engineer ing and Technology (ICATECH 2023), pages 97-102
ISBN: 978-989-758-663-7; ISSN: 2975-948X
Copyright
c
2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
97
physical units (visitors) of people/goods to get
services from inadequate facilities (servers) causes
people/goods to wait a long time (Hu et al., 2018).
The arrival of visitors or customers is predicted at the
same time as the facility. The form highly depends on
the number of customers/goods available in the
facility (Huihui et al., 2016). The service form is
greatly influenced by the time of service for
customers/goods (Bahadori et al., 2014)
(Tuan,
2020). Many customers/goods are in the service
facility and may be independent during the old state.
The number of services for consumers/goods or
service points in a facility may include one or more
service facilities (Mutingi et al., 2015).
2.1 Queue System
Server capability depends on the number of
customers/goods who queue and are served by the
server (Monteiro et al., 2021). There is a facility with
a server that can accommodate any number of
consumers/goods, arguably has no limit, or frees the
number of customers to queue (Banerjee and Hecker,
2016). On the other hand, there is also a facility with
a server that can only accommodate a few
consumers/goods because it has a minimal capacity.
Queue waiting time highly depends on a service being
available and operating at the facility (Pan et al.,
2015) (McCormack and Coates, 2015). The more
effective service in a second level or facility is that
the waiting time will be shorter and shorter. If there is
service, then the waiting time for the sangha takes
quite a long time. In essence, the creation of queues
is due to the service or service needing to be more
effective at work and the crowds of consumers and
customers (Alodhaibi et al., 2018).
Therefore, the effectiveness of a queue is very
dependent on the facilities provided. In addition, the
support facilities will be excellent because
consumers/goods do not experience long queues. A
queuing system with facilities must pay full attention
to when a crowd of consumers/goods comes so there
is no buildup. Queue structure has two components
(Sudtachat et al., 2016): (1) waiting line, (2) facility
service, and (3) facility services are facilities that
provide good or bad facilities because they can affect
the time of servicing customers/goods.
Figure 1. General Structure of the Queuing Model (Huihui
et al., 2016)
The queuing method model makes it easy to
balance service costs by using queuing costs
(Tychalas
and Karatza, 2020) (Monteiro et al., 2021)
: (1) the Time or
Hours of Consumers when queuing
(McCormack and
Coates, 2015)
; (2) The number of queues made by
consumers; (3) The time required by consumers in
queuing
(Hu et al., 2018) (Gani et al., 2018)
; (4) How many
customers are waiting in line?
Queuing discipline shows that the first
person/customer who arrives must be served first.
There are four disciplines in the queue
(Tuan, 2020)
(Banerjee and Hecker, 2016)
:
FIFO means the service must serve the first
visitor
(Pan et al., 2015)
. So, for example, in
Pharmacy counters, Cinemas, Gas Stations,
etc., in FIFO, the first visitor to come or enter
must be the first visitor to be served or
finished.
LIFO means visitors or people who come and
arrive last first out
(Alodhaibi et al., 2018)
. For
example, the queuing system in the elevator
for the same floor.
SIRO means that the service is carried out
randomly and does not necessarily mean that
the first person to come must be served
(Fang et
al., 2016)
.
PS means that services are focused or
prioritized on visitors who have specific
problems and must have top priority over
customers who do not have health problems,
even if the customer or consumer comes at the
beginning or is the first to arrive
(Alodhaibi et al.,
2018)
. Like the elderly 65 and over than others
at a puskesmas or other health service.
2.2 Queue Formulation
Some of the formulations used in this study are as
follows (Bahadori et al., 2014):
The average time between arrivals
(1)
Average Processing Time
(2)
Average Waiting Time (Queue Time)
(3)
Average Processing Delay Time (Delay Time)
(4)
Average Queue Length
(5)
Entering System Queue
Service Facility
Out System
ICATECH 2023 - International Conference on Advanced Engineering and Technology
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Average Time in the System
(6)
Probability of customers waiting in the queue
(7)
System utility 1
(8)
3 RESEARCH METHODS
This study conducted direct observation at the
Transmart and Superindo supermarkets in the
Surabaya area. In observing supermarket cashier
services, two samples or servers were taken each to
represent the number of cashiers in the supermarket.
Then the data is processed using Ms. Excel before
proceeding with modelling using Arena. Finally, the
observation data results are processed using the Arena
Software approach to determine the effectiveness of
the two supermarkets, Transmart and Superindo.
Problem Determination
Each research must determine what problems
are obtained; with problems, the research will be
successful.
Data Collection and Model
Data collection was obtained from direct
observation (Transmart and Superindo), and
random data was used for the model.
Validation
Validation is essential when conducting
simulation studies because of the validity of the
data we examine.
Program the computer
Model builder to be used for simulation studies.
Running the program
Run the program to find out the output/input for
validation purposes.
Validation
The second validation is used to test the validity
of the input and output models.
Figure 2. Flowchart.
4 RESULT AND DISCUSSION
Through data processing using Software Arena 14.0,
the following results are obtained:
Figure 3. Model Transmart System
Figure 4. Model Superindo
The results of the data processing method of the
Transmart Rungkut Surabaya system based on the
Analysis of the Effectiveness of Cashier Service with a Simulation of the Queue System
99
approach with the Arena software obtained results
such as:
(a) (b)
Figure 5. (a) and (b) Output Category Overview Arena Software of Queue for Transmart.
Based on the expenditure of the data obtained as
shown above and obtained the following information:
In the case of waiting time, queues at the
Transmart Rungkut Surabaya cashier service
have a minimum waiting time of 0.00 minutes,
and then the maximum waiting time is
60.8274 minutes. The average waiting time is
2.7030 minutes at the Cashier 1 service at
Transmart Rungkut Surabaya.
In the case of waiting time for the queue at the
Transmart Rungkut Surabaya cashier service,
the minimum waiting time is 0.00 minutes.
Then the maximum waiting time is 0.7530
minutes, and the average waiting time is
0.0188 minutes at the Cashier 2 service at
Transmart Rungkut. Surabaya
(a) (b)
Figure 6. (a) and (b) Output Category Overview Arena Software of Resources for Transmart.
Based on the expenditure of the data obtained as
shown above and obtained the following information:
In processing the Transmart Arena, the
average waiting time is 2.7030 on the server or
cashier 1 and 0.0188 on the server or cashier
2. From these results, Transmart has an
effective cashier service performance in the
queuing system, so it does not cause long
queues. in service at the cashier.
From these three conclusions, the top service
at Super Indo Surabaya was obtained because
Overview of Queue for Superindo
the waiting time was 0.0188 minutes. It was
obtained at cashier service two at Transmart
Surabaya
ICATECH 2023 - International Conference on Advanced Engineering and Technology
100
(a) (b)
Figure 7. (a) and (b) Output Arena Software Category.
Based on the expenditure of the data obtained as
shown above and obtained the following information:
In the case of waiting time for the queue at the
Super Indo Surabaya cashier service, the
minimum waiting time is 0.00 minutes, and
then the maximum waiting time is 1.0000
minutes. The average waiting time is 0.6601
minutes at the Cashier 1 service at Super Indo.
Surabaya
In the case of waiting time for the queue at the
Superindo Surabaya cashier service, the
minimum waiting time is 0.00 minutes. Then
the maximum waiting time is 1.0000 minutes.
Then the average waiting time is 1.5321
minutes at the Cashier 2 service at Super Indo
Surabaya
Figure 8. (a) and (b) Output Arena Software Category Overview of Resources for Superindo
Based on the expenditure of the data obtained as
shown above and obtained the following information:
In the processing of Arena Superindo, the
average waiting time is 0.6601 on the server or
cashier 1 and 2.5321 on the server or cashier
2. From these results, Transmart has an
effective cashier service performance in the
queuing system, so it does not cause long
queues. in service at the cashier.
From these three conclusions, the top service
at Super Indo Surabaya was obtained because
the waiting time was 0.6601 minutes. It was
obtained at cashier service one at Super Indo
Surabaya.
A comparison of Transmart and Superindo Average
Time can be seen in the table below:
Table 1: Comparison of Transmart and Superindo Average
Time
Waiting Time Transmart Superindo
Server 1 2,7030 0,6601
Server 2 0,0188 2,5321
Average 1,3609 1,5961
The entity waiting time at Transmart and
Superindo in Surabaya obtained an average waiting
time for Transmart Rungkut Surabaya at cashier one
and cashier two services 1.3609. For Superindo
Surabaya, the average time obtained was 1.5961.
Analysis of the Effectiveness of Cashier Service with a Simulation of the Queue System
101
5 CONCLUSIONS
After direct observations and data processing using
Arena software, the results showed that cashier
services at Transmart supermarkets were more
effective than at Superindo supermarkets. This
happens in the Transmart queuing system is better
because the service provided is high-speed, so it does
not cause buildup in an extensive system, and there is
no delay in the Transmart queuing system. The
average waiting time for the two Transmart cashier
samples of 1.3609; this value is smaller than the
Superindo supermarket with a value of 1.5961.
Because of this, the queuing system and service at
Superindo cashiers must be improved to achieve a
better level of effectiveness.
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