Evaluation of the Two Runway Queuing System: Evidence from
Soekarno-Hatta International Airport in Indonesia
PRASADJA RICARDIANTO1, ADRYAN PRAMA PUTRA1,
SUHARTO ABDUL MAJID1, PEPPY FACHRIAL1, JOHAR SAMOSIR1,
ERMAN NOOR ADI1, ADITYA WARDANA2, SALAHUDIN RAFI2,
IMAM OZALI3, ENDRI ENDRI4
1Postgraduate Program, Institute of Transportation and Logistic Trisakti
Jl. Ahmad Yani No.85, Rawasari, Jakarta Timur 13210
INDONESIA
2Faculty of Management and Business, Institute of Transportation and Logistic Trisakti
Jl. IPN No.2, Cipinang Besar Selatan, Jakarta Timur 13410
INDONESIA
3Vocational Program, Institute of Transportation and Logistic Trisakti
Jl. IPN No.2, Cipinang Besar Selatan, Jakarta Timur 13410
INDONESIA
4Faculty of Economics and Business, Universitas Mercu Buana
Jl. Meruya Selatan No. 1, Kembangan, Jakarta Selatan 11650
INDONESIA
Abstract: - This study aims to analyze the queuing system, service performance, and utilization of the two
runways at Soekarno-Hatta Airport, Tangerang, Indonesia. The number of aircraft movements at the airport at
busy hours exceeds capacity, resulting in long queues. This study uses a quantitative approach and queuing
theory with a single server multi-channel queuing system. Discussion of runway service performance at
Soekarno-Hatta Airport, by calculating the Queuing System State Probalilities to determine the probability of n
units (arrivals) in the system. Five equations have been analyzed in order to Evaluation of the Two Runway
Queue System. The findings of this study provide a signal for optimizing airport operator runway utilization by
developing runway capacity and adding infrastructure as well as adding taxiways, aprons, and runways. The
increase in runway capacity will have an impact on more aircraft services, which also means more effective and
efficient runway utilization. To improve the queuing system, it is necessary to improve queuing system services
with regular training of directly related officers so that the queuing system can be more effective and efficient.
To improve the performance of runway services, it is necessary to increase the capacity of the navigation tools
currently owned.
Key-Words: - queue system, service performance, runway capacity, multi-channel single server
Received: April 19, 2021. Revised: January 28, 2022. Accepted: February 21, 2022. Published: April 4, 2022.
1 Introduction
Air transportation has three main components which
are closely related to each other. The three
components are aircraft as a means of air
transportation, airports as infrastructure for
departure, arrival, and Air Traffic Services acting as
a liaison medium between airports and air traffic
controllers. Soekarno-Hatta International Airport
experiences an increase in the number of passengers
every year and the frequency of flights also
increases. In line with the growth of airplane
passengers in Indonesia, the development of users of
Soekarno-Hatta International Airport as the main
airport in Indonesia is also increasing. In a period of
10 years, starting from 2009 to 2019, the number of
passengers arriving and departing from Soekarno-
Hatta International Airport is described as follows:
the highest number was recorded in 2018 with a
total of 65,668,776 passengers, an increase of 4,
21% from the previous year 2017 which amounted
to 63,015,620 passengers. The highest increase of
19.26% occurred in 2010 when the number of
passengers in the previous year was 37,143,719 so it
jumped to 44,296,024 passengers.
In the period from 2014 to 2019, the highest
number of passenger and aircraft movements
occurred in 2018 with a total of 3,181,163
passengers, resulting in an increase in the number of
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Prasadja Ricardianto, Adryan Prama Putra,
Suharto Abdul Majid, Peppy Fachrial,
Johar Samosir, Erman Noor Adi,
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passengers by 3.65%. Meanwhile, the highest
number of aircraft movements occurred in 2017
with a total of 447,390 aircraft movements, resulting
in an increase of 8.12% from the previous year. In
2011 there was the highest increase of 13.08% from
the previous year which amounted to 305,541
aircraft movements, bringing it to 345,508 aircraft
movements. Based on data from Airports Council
International in 2019, Soekarno-Hatta International
Airport, Tangerang, Banten was still ranked in the
top 20 largest airports in the world, surpassing
Singapore's Changi Airport. Soekarno-Hatta
International Airport itself is precisely in the 18th
position. In the ASEAN region, there are only two
airports that are ranked in the top 20, namely
Soekarno-Hatta International Airport in the 18th
position and Changi Airport in the 19th position.
Many flight services can be done at this airport
every day, which can serve more than 1,000 flights
per day. Throughout 2019, the total movement of
aircraft at Soekarno-Hatta International Airport
reached 390,648 take-offs and landing.
The overcapacity of the airport can result in long
queues. In 2019, the number of movements of 42
per hour has exceeded the Declared Runway
Capacity of only 39 movements per hour. The
capability of the capacity of two runways for air
side services for aircraft movements at Soekarno-
Hatta International Airport based on the Declared
Runway Capacity (Table 1).
Tabel 1. Declared Runway Capacity
Soekarno-Hatta International Airport
Time/Slot
(UTC)
00.00-
13.59
14.00-
14.59
16.00-
16.59
17.00-
17.59
Reguler
Flight
80
76
34
24
Irreguler
Flight
1
1
2
2
Time/Slot
(UTC)
18.00-
18.59
19.00-
21.59
23.00-
23.59
Reguler
Flight
22
34
76
Irreguler
Flight
2
2
2
Based on Table 1 air side services, aircraft
movements at Soekarno-Hatta International Airport
based on the Declared Runway Capacity of Airnav
Indonesia are 80 movements per hour for regular
flights and 1 movement for irregular flights at
00.00-13.59/07.00-20-59. The lowest runway
capacity is 22 movements per hour for regular
flights and 2 movements for irregular flights at
18.00-18.59/ 01.00-01.59.
A large number of aircraft taking off and landing
at Soekarno-Hatta International Airport causes long
queues for departing and landing aircraft. This
causes aircraft to queue up to use the runway. From
observations, airports are still often seen queuing
airplanes on taxiways that want to take off when the
flight frequency is high, especially during feast
days.
Based on the background of the problem, several
problems have been identified: (1) Soekarno-Hatta
International Airport experiences an increase in the
number of passengers every year and the frequency
of flights also increases, the number of taking off
and landing movements at Soekarno-Hatta
International Airport is very busy, resulting in
aircraft queues on taxiways that want to take-off
when flight frequency is high, especially during
Lebaran is a bid day for Moslem, (2) long queues
can increase the cost of Avtur fuel for Air Transport
Business Entities, (3) long queues cause delays so
that it can be detrimental passengers and the Air
Transportation Business Entity itself, and (4) The
number of aircraft movements has exceeded the
maximum capacity, resulting in long queues. Based
on the identification of the problem, the research
problem is limited to what queuing system is used
on the Soekarno-Hatta International Airport runway,
service performance, and the utilization of two
runways on Lebaran Transport in 2019 at Soekarno-
Hatta International Airport.
As a comparison for the discussion of two
runways, Mascio et al. [1] explain that airports in
Italy with high traffic volumes were considered to
analyze two layouts and namely new runways and
modified operating conditions were considered.
Based on the test results at the Hong Kong airport,
Lancia and Lulli [2] explained that dynamic runway
configuration planning and semi-mixed runway
design can utilize runway capacity more efficiently.
Air Traffic Control operators will be able to
optimize runway capacity by operating dynamic
runway configurations on the runway based on air
and airport traffic conditions. In research using
several models, the results of Stephens and Ayo
Agunbiade [3] study show that London Heathrow
Airport (LHR) and Munich International Airport
(MUC) are efficient in utilizing runways and can be
an important reference for airport operators to
evaluate and compare various types of runway
configurations. During this pandemic, Lai et al. [4]
explained that the simulation results show that the
overall flight optimization effect is 48 percent and
flight delay times are reduced by 50 percent, so it is
considered an acceptable scheduling optimization
result. Meanwhile, the purpose of the study was to
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determine and analyze the level of runway
utilization at Soekarno-Hatta International Airport.
Meanwhile, the purpose of the study was to
determine and analyze the level of runway
utilization at Soekarno-Hatta International Airport.
2 Literature Review
2.1 Runway
The definition of a runway according to [5] is a
rectangular area above the airfield used for landing
and taking off of aircraft. The length and width of
the runway at each airport are different, according to
the needs, conditions of obstacles around the airport.
In general, the configuration used is the basic
configuration, namely; (1) Single Runway, This
configuration is the simplest; (2) Parallel Runway,
The capacity of this parallel runway configuration
depends on the number of runways and the
separation of distances between runways. The
number of parallel runways commonly used is two
parallel runways, three, and four parallel runways.
The distance between runways is divided into three
and depends on the centerline dividing the two
runways, (a) Close (b) Intermediate, and (c) Far, (3)
Intersecting Runway, an airport having two or more
runways with different directions that are mutually
exclusive. cross each other, this configuration is
called an intersecting runway and (4) Open-V
Runway, which is several runways placed in
different directions, which do not cross each other.
Similar to an intersecting runway, the Open-V
Runway uses a single runway when strong winds
are blowing only to one side.
According to Avery and Balakrishnan [6],
weather conditions, traffic demand, air traffic
controller workload, and coordination flow with the
nearest airport affect the choice of runway
configuration. Mesgarpour [7] argues that aircraft
takeoff scheduling is formulated to maximize
runway departure throughput and minimize total
waiting time. Several models for evaluating arrival
and departure capacities and ways of calculating
runway capacity under various conditions have been
designed in several countries previously [8, 9, 10].
The results of the study Tascón and Olariaga [11] at
Bogota Airport, Colombia indicate the need for an
expansion of airport case studies on the runway
system, where the current capacity utilization factor
for the number of runways required is set to three
until the last simulation period in 2023.
The mixed Mode Parallel Operations approach at
Zurich, Switzerland airport expected runway
efficiency with a ratio of more than 83.8% [12].
Also in Indonesia, an evaluation of runway capacity
has been carried out through the configuration and
maximum runway capacity, runway crosswind, and
tailwind potential that has been carried out by
Andarani et al. [13], Eviane et al. [14], Firdiyan and
Muntini [15], Majid et al. [16], and Sardjono et al.
[17]. Specifically, the use of several runways
through a simulation program at Soekarno-Hatta
airport has been previously studied by Ongkowijoyo
and Ruseno [18], Sampurno et al. [19], and Saragih
et al. [20]. In general, research on parallel runways
with mixed-mode or multiple runways will consider
the problem of ordering and scheduling aircraft in
the uncertainty of arrival and departure delays [21].
The addition of a runway so that it can be operated
in parallel, but require twenty years of negotiation,
planning and construction [22]. Strategically in the
long term, the productivity of runway capacity at
airports is also determined by the available
infrastructure.
2.2 Queuing Theory
Queues occur when the number of customers to be
served exceeds the existing facilities, resulting in the
Air Transport Business Entity waiting or queueing
to get service. Queuing theory is one of the
statistical methods that can be used to overcome
these problems. Queuing theory is used to determine
the characteristics, models, and performance
measures of aircraft queuing systems at airports,
namely the time between aircraft arrivals, aircraft
service times, and waiting times for aircraft to take
off. The use of queuing theory applications is
expected to improve the quality of airport services.
Theoretically, in transportation, Teodorovic and
Nedeljkovic [23] explain that there are many
fluctuations in the queuing system in arrival rates
and service times, which create queues and reduce
the level of service offered to passengers. Based on
queuing theory, aircraft tracking data and flight
schedules are also used as inputs to characterize the
national air traffic network [24]. The queuing-based
modeling approach according to Itoh and Mitici [25]
suggests that one potential solution is to expand the
realization of time-based operations, efficiently
shifting from traffic flow control to time-based
arrival management.
Ignaccolo [26] states that the results of traditional
queuing theory can be used to analyze airport
runway systems, analytical approaches and show
how to build simulation procedures, and be able to
measure the performance of airport runways that are
only used for arrivals. According to Thiagaraj and
Seshaiah [27] that the results of queuing theory can
be used to analyze the runway system, but when the
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Johar Samosir, Erman Noor Adi,
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airport is too crowded is realistically required, a
simulation approach to be able to measure the
performance of airport runways that are only used
for arrivals, with different mixtures of traffic and
variables. operational. Several researchers have
proposed solutions to the runway balancing problem
using simulation-based techniques to calculate
aircraft delay. The findings Lancia and Lulli [28]
with Poisson and Pre-Scheduled Random Arrivals
queues have important implications for incoming
traffic simulation-based modeling and analysis and
can increase the use of available capacity, thereby
reducing air traffic delays. Sekine et al. [29] explain
that implementing the application of new wake
turbulence categories will contribute to reducing air
traffic congestion near airports, and to reducing
delays in overall arrival traffic while increasing
runway throughput. Meanwhile, Jain et al. [30], also
explained that with the queuing model simulation,
the number of checkpoints at the airport can be
increased so that waiting planes can be distributed
effectively. Several queuing systems at several
international airports in Indonesia studied were
stated to be quite good and runway and taxiway
capacities were still able to serve air traffic during
peak hours [31, 32, 33, 34] add with the queuing
theory, Juanda International Airport, Surabaya, is
only allowed to make nine flights per day maintain
effective service performance. The findings of
Stephens [35] on airports in Nigeria with queuing
theory shows that the flow of domestic flights will
be more than international flights. In the USA,
especially at John Fitzgerald Kennedy, New York
Airport, research results Lai et al. [36] show that
congestion during taxi-outs, waiting for take-off,
therefore the optimization method is used to
minimize flight delays. At Tokyo International
airport, Japan's arrival delay time can be minimized
by implementing the proposed arrival traffic
strategy along with automation support for air traffic
controllers [37, 38].
3 Methodology
The research uses a quantitative method approach
and queuing theory with a single server multi-
channel queuing system. Queuing conditions often
occur for goods that are in the process of going to an
area to be served, but then face delays due to the
service mechanism being busy. The characteristics
of service facilities can be seen from three things,
namely the physical layout of the queuing system,
queue discipline, and service time. The testing
procedure in this research starts with making
observations related to the implementation of
aircraft movements (taking off and landing) during
the 2019 Eid transportation period at Soekarno-
Hatta International Airport. Especially, related to
what queuing system will be used, then paying
attention and observing the phenomena that occur
through participatory observation of the movement
of the aircraft. Discussion of runway service
performance at Soekarno-Hatta Airport, by
calculating the Queuing System State Probalilities to
determine the probability of n units (arrivals) in the
system (P). Queuing Formulas calculation is
continued to find out the average number of aircraft
in the queue, the average waiting time in the queue,
the average number of aircraft in the system and the
average time in the system.
The calculation of the queuing system uses
mathematical formulas with the help of Qm
software for windows. Calculation with Multiple
Channel Single Server Queue system and
calculation of runway utilization encompasses
several stages and formula as follows;
(1) The probability that n units (arrivals) in the
system,
 󰇱󰇯󰇛
󰇜


 󰇰󰇛
󰇜󰥢
󰇭
󰇮󰇲
This service performance calculation formula is to
get the probability number of n units of arrival in the
system (P) through the Queuing System State
Probalilities calculation method.
(2) The average number of units in the queue,
 󰇛󰇜󰇛
󰇜
󰇛
󰇜
This Lq formula is to calculate the average number
of aircraft queuing during takeoff on the air side of
the aircraft movement.
(3) The average waiting time in the queue,
Wq 
This Wq formula is to calculate the average waiting
time in the queue when the plane is waiting to take
off.
(4) The average waiting time in the system,
Ws 
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This Ws formula is to calculate the average waiting
time for aircraft services on the runway until they
are finished being served.
(5) The average number of units in the system.
Ls
This Ls formula is to calculate the average number
of aircraft queuing and being served for air side
services for aircraft movements.
4 Results and Discussion
4.1 Queue System and Runway Usage
Concept
The queuing system on the runway at Soekarno-
Hatta Airport is a queuing system with multi-
channel single server is a type of service with more
than one service provider. Both runways operate
using Mixed Mode Parallel Operations with the
following conditions; (1) Each runway is used for
departures and arrivals, (2) For aircraft departing for
traffic departing from another runway, it is
independent as long as both follow the existing
Standard Instrument Departure (SID), and (3) For
aircraft carrying out an Instrument Landing System
(ILS) Approach to an aircraft that is conducting ILS
Approach on another runway is the independent
parallel approach.
Soekarno-Hatta International Airport has two
parallel runways separated by two taxiways of 2,402
m long, namely North Runway (07L/25R) and
South Runway (07R/25L) (Figure 1).
Fig. 1: Two runways, namely RWY 07L/25R (North
Runway) and RWY 07R/25L (South Runway)
Technically, several concepts of balancing the
use of the Soekarno-Hatta Airport runway have
been applied, namely; (1) The number of aircraft
queues that will depart and land is attempted to be
the same on each runway, (2) If there is a queue at
the holding point of runway 07L, the departure of
aircraft on Apron D and E is diverted to runway
07R., (3) In the event of a queue at the holding point
of runway 25R, the departure of aircraft on Apron F,
G and H is diverted to runway 25L and (4) This
concept is implemented based on coordination
between the Supervisor Tower and Approach
Control at the airport.
At the time of this study the length of the two
Soekarno-Hatta Airport runways had the
configuration; The length of runway I ( 07R/25L) is
3660 meters and the length of runway II ( 07L/25R)
is 3600 meters; and the distance between the center
lines of runway I and II is 2402 meters (Table 2).
Table 2. Take Off Run Available (TORA) and
Intersection Length
RUNWAY
Intersection
Taxiway
Angle from
RUNWAY
Centreline
TORA (M)
07/L
N7
30◦
2625
N8
36◦
3048
07/R
S7
30◦
213
S8
30◦
3541
25/L
S2
30◦
3516
S3
30◦
2714
25/R
N2
90◦
3488
N3
30◦
2655
Each runway is used for departures and arrivals.
The number of aircraft queues that will depart and
land is attempted on each runway is the same. The
use of the runway must be by the wind direction and
wind speed. If there is a change in wind conditions
so that the runway used is not suitable, then the
Tower Supervisor is obliged to change the runway.
The process of changing the runway must be
coordinated with the Jakarta Approach Control unit
according to traffic conditions.
4.2 Queue System at Soekarno-Hatta Airport
Runway
Soekarno-Hatta International Airport is one of the
international standard airports in Indonesia, which
can be visited by various types of aircraft both from
within and outside the country. Soekarno-Hatta
International Airport experiences an increase in the
number of passengers every year and the frequency
of flights also increases. In line with the growth of
airplane passengers in Indonesia, the development
of users of Soekarno-Hatta International Airport as
the main airport in Indonesia is also increasing.
Passenger statistical data from 2009 to 2019 shows a
tendency to increase the number of activities with a
total of 54,496,625 passengers and total aircraft
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movements reaching 390,648 aircraft movements
taking-off and landing in 2019.
4.3 Soekarno-Hatta Airport Runway Service
Performance
Some of the Queuing System State Probalilities
calculations in measuring Runway Service
Performance with the number of runways (S) as
much as two units are as follows; (1) Aircraft
movement capacity is 54 aircraft/hour per two
runways or 27 aircraft/hour per 1 runway, (2)
Service performance in the airside service queue
system for aircraft movements shows the arrival rate
(λ) is 30,810 aircraft/month or 1,027 aircraft/day or
42.82 aircraft/hour, and (3) Service Level (µ): 1/ µ
is 2.22 minutes/aircraft or to 27 aircraft/hour.
With the probability of n units (arrival) in the
system (P) and two runways in the aircraft
movement service, it can be interpreted that the
probability of 0 units (arrival) in the system from
both runways is 0.115.
 󰇩󰇛
 󰇜
 󰇛
 󰇜
 󰇛
 󰇜
 󰇧

 󰇨󰇪 =
0,115
The result of the calculation of P above based on
the number of two runways in the airside service of
aircraft movement is a probability of 0 units
(arrival) in the system from the two runways of
0.115.
After calculating P which is the probability of n
units (arrivals) in the system and the average
number of aircraft in the queue, where the average
number of aircraft in the queue is three aircraft, the
next calculation is in the queue will be known
average waiting time.
󰇛󰇜󰇡
 󰇢
󰇡
 󰇢󰇛󰇜2,69 aircraft
~ 3 aircraft
The average number of aircraft in the queue is three
aircraft queuing for takeoff in the airside service of
aircraft movements.
Queue calculation to find out the average waiting
time which is denoted by Wq, based on the formula,
is 3.76 minutes, which is the average time airplanes
wait for take-off.

 = 0,06 hour = 3,76 minutes
The average waiting time in the queue is 3.76
minutes, which is the average time airplanes wait
for take-off.
The next calculation is the average time needed to
wait for the runway service to finish being served in
the system. With the formula is 27 planes/hour, the
results of the Ws calculation show several 5.99
minutes.

 hour = 5,99 minutes
The calculation result of this Ws formula is 5.99
minutes, meaning that the average waiting time for
the runway service is until the plane is finished
being served.
The average number of aircraft in the system, which
is denoted by Ls, means that the average number of
aircraft queuing and being served for airside
services is four aircraft.
Ls 
 = 4,27 ~ 4 aircraft
While the results of Ls are four aircraft. This means
that the average number of aircraft queuing and
being served for air side services is aircraft
movement.
4.4 Runway Service Performance Evaluation
Calculation of queuing system service performance,
starting from calculating the Queuing system state
probabilities to the calculation of Queuing
Formulas, namely calculating the average number of
aircraft in the queue, the average time aircraft
waiting for landing or take off, the average number
of queuing and being served and the average waiting
time for runway services to finish being served. The
results of the calculation of the Single Server Multi-
Channel Queuing System are summarized as
Runway Service Performance (Table 3).
Table 3. Summary of Runway Service Performance
Multiple Channel Single
Server Queue system
Results
The probability that n units
(arrivals) in the system (Po)
0,115
The average number of
aircraft in the queue (Lq)
3 aircraft
The average waiting time in
the queue (Wq)
3,76 minutes
The average waiting time in
the system (Ls)
4 aircraft
The average number of units
5,99 minutes
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in the system (Ws)
Source: Data Processed
Based on the results of calculations with an average
of six aircraft per hour, the average aircraft served is
seven aircraft per hour, concerning the analysis of
the service performance of the queuing system for
aircraft movements in the 2019 Lebaran
Transportation period and previous relevant
research, it can be concluded that the queuing
system service at Soekarno-Hatta International
Airport can still be not optimal and can be improved
again to be more effective and efficient.
4.5 Runway Utilization Evaluation
Runway utilization is calculated based on aircraft
movement data during Lebaran transportation in
2019. The weight is calculated on each runway even
though at the end of the calculation it will be
combined into one runway value.
Table 4. Runway Utilization Percentage (UP)
Soekarno-Hatta International Airport
Runway
Movement
%
25L
12.986
79,9%
07R
3.267
20,1%
Total
16.253
100%
Source: [1]
Table 4 explains that the runway utilization rate at
Soekarno-Hatta International Airport is 79.9% for
Runway 25L and 20.1% for Runway 07R. Based on
the calculation results, more aircraft movements are
on Runway 25L compared to Runway 07R. Runway
utilization also depends on the configuration of the
taxiway and parking stand, and the distance between
the parking stand and the taxiway. The more
taxiways and parking stands, the shorter the
separation time, which means the runway capacity
to serve aircraft is increasing.
4.6 Discussion
Theoretically and practically, Messaoud [39] has
researched aircraft landing operations on several
runways. The results of this study support several
other researchers such as Bauerle et al. [40], and
Bennell et al. [41] with queuing theory simulations
comparing two or three runways. The calculation of
queuing theory on airport runways with the Multiple
Channel Single Server Queue system is also in line
with research by Farida et al [31], Kim et al. [42],
and Zaki et al. [43]. In conclusion, one of them is
the addition of the right terminal building to reduce
queuing time and improve more effective services.
Research related to the queuing method in research
at Soekarno-Hatta Airport is also in line with several
other studies such as that conducted by
Rachmansyah and Nahdalina [44], who found that
aircraft movement optimization, which was carried
out by balancing movements, both on international
and domestic routes will reduce the number of
existing aircraft movements. This research with two
runways also supports the proposed addition of a
runway at Soekarno-Hatta Airport, that the addition
of a new runway and hourly slot time exceeds the
total capacity with queuing theory is one method to
overcome current traffic growth [45, 46, 47]. This
study is also in line with other findings by Shone et
al. [48], with strategic and tactical methods in
queuing theory to manage congestion at airports,
including the use of slot control, ground holding
programs, runway configuration changes, and
aircraft sequencing policies.
At Adi Sutjipto airport, Yogyakarta, the average
waiting time under normal conditions is 4.57
minutes/aircraft, while during peak hours it reaches
16 minutes/airplane [49, 50]. the average time in the
system under normal conditions is 8.57
minutes/aircraft, while during peak hours it is 20
minutes/airplane. Meanwhile, at Ahmad Yani
international airport, Semarang, the queue principle
applied is first come first served, with the number of
capacities for incoming aircraft and unlimited
calling sources [51]. Calculations with the queuing
theory in the study Samosir et al. [52] are also in
line with the findings at I Gusti Ngurah Rai
International Airport, Bali as one of the busiest
airports in Indonesia which have the potential as a
tourist destination for international tourists.
5 Conclusion
To improve the queuing system, it is necessary to
improve queuing system services and conduct
regular training of officers who are directly related
to the queuing system so that the queuing system
can be more effective and efficient. To improve the
performance of runway services, it is necessary to
improve the navigation tools currently owned. The
navigation tool plays a role in regulating the
movement of the aircraft. With more sophisticated
navigation tools, the separation distance between
aircraft can be enforced following the separation
standards, or at least it can be smaller than currently
enforced. The magnitude of the separation distance
greatly affects the runway capacity. If the
rejuvenation of the navigation equipment can be
WSEAS TRANSACTIONS on SYSTEMS and CONTROL
DOI: 10.37394/23203.2022.17.16
Prasadja Ricardianto, Adryan Prama Putra,
Suharto Abdul Majid, Peppy Fachrial,
Johar Samosir, Erman Noor Adi,
Aditya Wardana, Salahudin Rafi, Imam Ozali, Endri Endri
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carried out, it is hoped that the runway capacity can
increase, so that the runway can serve more requests
for existing aircraft movements.
To optimize the utilization of the runway, it is
necessary to design runway capacity development
and infrastructures such as the addition of taxiways
and aircraft parking runways, as well as runways so
that the runway capacity to serve aircraft increases,
which also means more effective and effective
runway utilization. efficient. Runway utilization is
not optimal and can still be improved to be more
effective and efficient. More aircraft movement is
on Runway 25L compared to Runway 07R. If there
is no significant improvement to the runway
utilization, there will be a potential for long queues
and long delays. The increase in runway utilization
can be carried out by designing runway capacity
development and adding related infrastructure such
as adding taxiways and aircraft parking runways, as
well as runways as well as technology development
by involving all aviation stakeholders.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
Conceptualization: Prasadja Ricardianto, Adryan
Prama Putra. Data curation: Imam Ozali, Erman
Noor Adi. Formal analysis: Adryan Prama Putra,
Endri Endri. Funding acquisition: Imam Ozali,
WSEAS TRANSACTIONS on SYSTEMS and CONTROL
DOI: 10.37394/23203.2022.17.16
Prasadja Ricardianto, Adryan Prama Putra,
Suharto Abdul Majid, Peppy Fachrial,
Johar Samosir, Erman Noor Adi,
Aditya Wardana, Salahudin Rafi, Imam Ozali, Endri Endri
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Salahudin Rafi. Investigation: Endri Endri, Erman
Noor Adi. Methodology: Prasadja Ricardianto,
Endri Endri, Aditya Wardana. Project
administration: Imam Ozali, Peppy Fachrial.
Resources: Suharto Abdul Majid, Salahudin Rafi.
Software: Endri Endri, Aditya Wardana.
Supervision: Endri Endri, Salahudin Rafi.
Validation: Prasadja Ricardianto, Johar Samosir,
Suharto Abdul Majid. Visualization: Johar Samosir,
Salahudin Rafi. Writing original draft: Prasadja
Ricardianto, Adryan Prama Putra. Writing review
& editing: Endri Endri, Peppy Fachrial
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DOI: 10.37394/23203.2022.17.16
Prasadja Ricardianto, Adryan Prama Putra,
Suharto Abdul Majid, Peppy Fachrial,
Johar Samosir, Erman Noor Adi,
Aditya Wardana, Salahudin Rafi, Imam Ozali, Endri Endri
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