Time Acceleration Analysis of the Kijing Terminal Development
Project in Mempawah, West Kalimantan
Ineza N. R. Marpaung, Silvianita, Daniel M. Rosyid and Suntoyo
Department of Ocean Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
Keywords: Precedance Diagramming Method (PDM), Monte Carlo Method, Time Cost Trade off, Project Duration
Acceleration.
Abstract: The cargo port is a port that is planned specifically for the purpose of loading and unloading of goods and is
equipped with a warehouse for storing goods and cranes to move cargo ship. With the construction of the
port, the company needs a good project management design. The mismatch between the schedule design
and the reality on the ground still creates problems. This is a challenge for a project manager who must
carefully look at existing activities to avoid delays in the project. To overcome this problem, it is necessary
to maximize performance by reducing the duration of each activity in the project that still includes safety
time. This paper analyzes the acceleration of the duration of the Kijing terminal construction project in
Mempawah West Kalimantan using the Precedance Diagramming Method (PDM) method, as well as the
Monte Carlo method to find out the project's probability on time, then find the optimal duration with the
Time Cost Trade Off (TCTO) method. From the results of the analysis with the PDM method obtained 12
activities that exist on the critical path. Based on the Monte Carlo simulation, the results show that the
probability of the project to be completed on time is 55% or 45% chance of being late. The optimum
duration and costs on the critical path are obtained at the addition of 1 hour of overtime. The total duration
of the project, which was originally 595 days to 513 days with a difference of 82 days, with a total cost of
Rp2,740,269,901,670 to Rp2,740,775,765,420 with a difference of Rp505,863,750 and also a cost slope of
Rp 6,169,070 per day.
1 INTRODUCTION
The West Kalimantan region is one of the priorities
in economic development announced by the
Government of the Republic of Indonesia. This
region has several potential natural resources such as
palm oil, bauxite, rubber, wood, and other
agricultural products. In addition, there are many
investors (both local and foreign) who are interested
in investing in the industrial sector in West
Kalimantan.
This potential was realized by one of the oil and
gas companiesas a port service provider company is
able to develop the potential of ports in Kijing
Beach, Mempawah, West Kalimantan. The port
development plan is also very likely, given the
existing condition of the Pontianak Port which is the
closest port to Kijing that has overcapacity and the
limited depth of the Kapuas River channel ± 5
meters. It is hoped that the existence of the Kijing
Terminal can later reduce the burden on existing
ports in West Kalimantan, invite ocean going ships
to be able to dock at the Kijing Terminal and reduce
overall logistics costs.
Kijing Terminal is located ± 80 km from the
North of Pontianak Harbor where there is Temajo
Island in front of Kijing Beach with a distance of ± 5
km that can be used to reduce wave energy.Kijing
Terminal will be developed in 3 (three) stages,
namely: Initial Phase, Phase I and Phase II. Kijing
Terminal has offshore and onshore facilities, each of
which has 4 (four) zones, namely: container zones,
liquid bulk zones, dry bulk zones and multipurpose
zones which are expected to accelerate economic
growth in the West Kalimantan region and provide
benefits to all parties involved.Based on the
importance of doing a good scheduling and
acceleration on the Kijing Terminal construction
project, it is necessary to have a system that makes it
easy to analyze the acceleration of the Kijing
Terminal construction project in Pontianak Port,
Mempawah, West Kalimantan.
122
Marpaung, I., Silvianita, ., Rosyid, D. and Suntoyo, .
Time Acceleration Analysis of the Kijing Terminal Development Project in Mempawah, West Kalimantan.
DOI: 10.5220/0010057801220130
In Proceedings of the 7th International Seminar on Ocean and Coastal Engineering, Environmental and Natural Disaster Management (ISOCEEN 2019), pages 122-130
ISBN: 978-989-758-516-6
Copyright
c
 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

Table 1: General Specification.
SPECIFICATION
KIJING TERMINAL PROJECT
INITIAL PHASE
Length 5434 m
Total Length 5434 m
Depth -12 sd 15
Area 32.8 Ha
Capacity (per year) 500.000 TEUs
500.000 tonnes
PHASE I
Length 2441m
Total Length 4415 m
Depth -12 sd 15
Area 49.2 Ha
Capacity (per year) 950.000 TEUs
23.840.000 tonnes
PHASE II
Length 1747 m
Total Length 6162 m
Depth -12 sd 15
Area 37.8 Ha
Capacity (per year)
1.950.00 Us
2 LITERATURE STUDIES
This section explains the theory used in this study.
Project management for construction have been used
by (Hendrickson, 2003). Project scheduling for gas
transmission pipe by Silvianita et al (2018).
2.1 Presedence Diagram Method
Network planning analysis is to find out the critical
path of the project (Demeulemeester, 2013).
The critical path is a series of activities that
require the overall duration of the project and may
not delay because it will affect the entire project.
There are four constraints in the Presedence
Diagram Method schedulling method, namely finish
to finish, finish to start, start to finish, and start to
start (Taha, 2007).
2.2 Monte Carlo Simulation
The Basics of Monte Carlo Simulation theory, one
of which is the Random Variable. According to Bain
and Engelhardt (1992) A random variable is a
function defined in the sample space 𝑆 that connects
every possible outcome at 𝑒 with a real number,
namely (𝑒) = 𝑥. If the set of possible outcomes of the
random variable 𝑋 is a calculated set, {1, 𝑥2, ..𝑥n},
or, {𝑥1, 𝑥2, ..}, then X is called a discrete random
variable. Random numbers to find the most possible
cost (Most Likely Cos) = ML can be generated using
the RAND function found in Microsoft Excel.
2.3 Time Cost Trade off
Time Cost Trade Off analysis method is a method to
speed up time by making an exchange between time
and cost. In this research, the time acceleration
analysis used on the critical path of the project is the
addition of overtime hours to workers in the field.
The addition of overtime hours is carried out in
several schemes, namely one hour, two hours, and
three houts of additional overtime. Then the
optimum additional overtime hours scheme is sought
by considering crash cost, crash duration, and cost
slope of each scheme.(Hullet & Nosbich, 2012).
3 METHODOLOGY
3.1 Problem Indentification
At the stage of formulating the problem, the
problems that occur in the object of research will be
obtained and become the focus of the research. The
object of this research is multipurpose terminal jetty
in Kuala Tanjung. Then, the researcher will
determine the objectives that refer to the formulation
of the problem that has been set.
3.2 Literature Study
Literatures and references are needed to determine
the appropriate method in this research and to
facilitate the writing of the steps in this paper.
3.3 Data Collection
Data of the Kijing Terminal project is needed for the
completion of this paper. The data needed include:
time schedule, draft budget, and manpower.
3.4 Critical Path Analysis using PDM
Method
The PDM method was used to analyze the critical
path in this study. The use of the PDM method in
this study facilitates the description of network
planning because of the overlapping activities on the
project (Leach, 2000).
Time Acceleration Analysis of the Kijing Terminal Development Project in Mempawah, West Kalimantan
123

3.5 Probability Analysis using Monte
Carlo Simulation
Monte Carlo Simulation is used to find out the
probability of duration of project completion in this
study. The results of using this method are knowing
the smallest, largest, and also probability based on
the actual contract (McCabe, 2003).
3.6 Acceleration Analysis using TCTO
Method
This paper uses the TCTO method to accelerate the
duration of the project. TCTO analysis is done by
compressing activities that are on the critical path.
The alternative used in the TCTO method in this
study is to use a one-hour, two-hour, and three-hour
overtime scheme (Kezner, 1995). TCTO has been
used in many areas such as in loadout process
(Silvianita et al., 2016).
3.7 Optimum Costs Determination
To determine the optimum duration of the project,
cost analysis must be carried out. The optimum
duration of the project is the duration of acceleration
by issuing costs as effectively and efficiently as
possible. If the amount of costs incurred to
accelerate the project is too expensive, then another
acceleration alternative will be sought. (PMI. 2013).
4 RESULT AND DISCUSSION
4.1 Project Time Schedule
Project time schedule data consists of the activity
name, duration, start date, and completion date.
(based on the project)
Table 2: Project Time Schedule.
No Activity Duration Start Finish
A Preparatory Work
1
Site office 14 days
Mon
8/13/18
Sun
8/26/18
2
Mobilization &
Demobilization
35 days
Mon
8/27/18
Sun
9/30/18
3
Stake out dan
Positioning
47 days
Mon
10/8/18
Fri
11/23/18
B Work on Pier
4
Concrete Pile
Work Dia.
327 days
Mon
11/26/18
Fri
10/18/19
No Activity Duration Start Finish
1000 mm Bottom
Type C0
5
Concrete Pile
Work Dia.
600 mm (Wave
Screen)
145 days
Mon
2/25/19
Fri
7/19/19
6
Concrete Pile
Work Dia. 800
mm (PMA)
327 days
Mon
11/26/18
Fri
10/18/19
7
Concrete Pier
Work and PMA
271 days
Mon
2/25/19
Fri
11/22/19
8
PMA Support
Buildings
91 days
Mon
11/25/19
Sun
2/23/20
34
Electrical Work 91 days
Sun
11/24/19
Sat
2/22/20
35
Testing and
Commissioning
127 days
Sun
11/24/19
Sun
3/29/20
4.2 Activity’s Constraint
Activity”s constrain data is to find out which
activities can be started earlier than other activities.
In this study, the consraint and time schedule data
obtained were inputted into Microsoft Project
software to obtain the expected network planning.
Table 3: Activity's Constraint.
No Activity Duration Predecessors Successors
A
Preparatory Work
1
Site office
14 days START 4
2
Mobilization &
Demobilization
35 days 3 5
3
Stake out dan
Positioning
47 days 4
7FS+2 days,
16FS+2 days,
18FS+2 days,
17FS+62 days,
22FS+142 days,
26SS+14 days
B Work on Pier
4
Concrete Pile
Work Dia. 1000
mm Bottom
Type C0
327
days
5FS+2 days
8SS+90 days,
9SS,11FS+37
days,
14FS+37 days
5
Concrete Pile
Work Dia. 600
mm (Wave
Screen)
145
days
7SS+90 days 10SS
34
Electrical Work
91
days
43FF 42SS
35
Testing and
Commissioning
127
days
44SS FINISH
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4.3 Critical Path Analysis
The critical path is a path that has a series of
activities with the longest total amount of time and
shows the fastest project completion time period. In
addition to using software, the determination of the
critical path was also done by manual calculation by
calculating the earliest start, earliest finish, latest
start, latest finish and float. Activities that have total
float = 0 are activities included in the project's
critical path. The formula of float is LS-ES or LF-
EF.
Table 4: Critical Path Manual Calculation.
Activity
Activity
ID
ES EF LS LF Float
Preparatory Work
Site office
A1 1 582 8 575 7
Mobilization &
Demobilization
A2 15 547 22 540 7
Stake out dan
Positioning
A3 57 493 57 493 0
Work on Pier
Concrete Pile
Work Dia.
1000 mm
Bottom Type
C0
B1 106 164 135 135 29
Concrete Pile
Work Dia. 600
mm (Wave
Screen)
B2 197 255 225 227 28
Hoist Crane
Work
H3 532 37 532 37 0
Electrical
Work
H4 469 37 469 37 0
Testing and
Commissioning
H5 469 1 469 1 0
4.4 Critical Path Determination
After determining the total float on the project,
activities that are on the critical path can be
identified. An activity is said to be critical if the
Total Float value is equal to 0. The total float is
obtained from LF minus EF or LS minus ES.
Table 5: Critical Path.
No Activity Activity ID Float
1
Stake Out & Positioning A3 0
2
Land Plant Work E1 0
3
Rigid Concrete Work E2 0
4
Rigid Work F1 0
5
Paving Block Work F2 0
6
Structure G1 0
7
Building Support G2 0
8
Mechanical Work H1 0
9
Plumbing Work H2 0
10
Hoist Crane Work H3 0
11
Electrical Work H4 0
12
Testing and Commissioning H5 0
4.5 Project Completion Probability
Analysis
The analysis carried out in this study is about the
probabilities of the duration of project completion
using the Monte Carlo method. There are several
steps in using the Monte Carlo method (Hullet &
Nosbich, 2012), including:
A. Optimistic Time and Pessimistic Time Data
Other data used for the Monte Carlo simulation are
pessimistic time and optimistic time for each
activity. This data was obtained from interviews
with contractors and staff at one of the oil and gas
companies. The following are the results of the
interviews summarized in the table below.
Table 6: Optimistic Time and Pessimistic Time Data.
Activity a m b
Days
Site office
7 14 20
Mobilization &
Demobilization
26 35 42
Stake out dan Positioning
39 47 54
Work Pile Pile Dia. 1000
mm Bottom Type C0
316 327 334
Work Pile Dia 600 mm
(Wave Screen)
137 145 154
Work Pile Pile Dia 800 mm
(PMA)
316 327 337
Work PMA
262 271 283
Work Mechanical
146 154 162
Work Plumbing
146 154 162
Work Hoist Crane
23 28 45
Work Electrical
84 91 99
Testing And Commissioning
116 127 138
Time Acceleration Analysis of the Kijing Terminal Development Project in Mempawah, West Kalimantan
125

B. Calculate the Standard Deviation
Standard deviation is used as input normal
distribution in generating random numbers.
Calculation of standard deviation is done using the
following formula:
(1)
Where:
𝜎 = standard deviation
a = optimistic time
b = pessimistic time
The following table is the result of calculating
the value of the standard deviation and the new
duration of the project.
Table 7: Calculation of the standard deviation and new
duration.
Activity sd New Duration
Days
Site office
0.8 14
Mobilization & Demobilzation
1.3 35
Stake out dan Positioning
1.2 47
Work Pile Pile Dia. 1000 mm
Bottom Type C0
1.8 323
Work Pile Pile Dia 600 mm
(Wave Screen)
1.5 146
Work Pile Pile Dia 800 mm
(PMA)
2.2 325
Work PMA
2.3 273
Work Mechanical
1.5 153
Work Plumbing
1.5 154
Work Hoist Crane
2.8 21
Work Electrical
1.2 92
Testing And Commissioning
2.3 129
C. Determine the Number of Iterations
It is carried out by means of gradual iteration, until
there is little or no change in the outcome. In this
study iteration is carried out in stages, namely from
a range of 10 to 1000 times iteration. We can choose
how many time we will do the iteration base on the
graph of the standart deviation change and the graph
of parameter avarage change (until stable).
Following is a graph of the statistical parameters
taken to see the difference in results from adding
iterations.
Figure 4: Graph of changes in the standard deviation of the
number of iterations.
Figure 5: Graph of changes in the results of the parameters
Average with the Number of Iterations.
From the graph above it can be concluded that by
doing 1000 times the iteration of statistical
parameters in the form of standard deviations, the
median and the average are already in the stable
results. Unstable results occur in iterations carried
out between 10 to 500 times. After iterating 1000
times, the results obtained with statistical parameters
such as in table 8.
Table 8: Statistical Parameters of Iteration Results.
No Parameter Quantity
1
Standart Deviation 4.17
2
Median 595
3
Kurtosis 0.2
4
Skewness 0.023
5
Average 595
6
Maximum 610
7
Minimum 610
8
Varian 17.4011
9
Mode 596
D. Calculate PDF and CDF
Calculating Probability Density Function (PDF) and
Cumulative Distribution Function (CDF) is useful to
find out the opportunities of project completion.A
PDF is specifies the probability, CDF is a direct
measure of probability.
The steps in calculating pdf and cfd are as follows:
Table 9: Monte Carlo Simulation Results in 1000 Times
Iteration.
Duration Cum %cum Prob %prob
587
41 4% 41 4%
588
56 6% 15 2%
589
99 10% 43 4%
590
141 14% 42 4%
591
206 21% 65 7%
592
279 28% 73 7%
593
354 36% 75 8%
594
468 47% 114 11%
595
563 56% 95 10%
596
659 66% 96 10%
597
731 73% 72 7%
σ =
𝒃−𝒂
𝟔
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Table 9: Monte Carlo Simulation Results in 1000 Times
Iteration (cont.).
Duration Cum %cum Prob %prob
598
796 80% 65 7%
599
855 86% 59 6%
600
909 91% 54 5%
601
936 94% 27 3%
602
964 97% 28 3%
603
979 98% 15 2%
604
985 99% 6 1%
605
992 99% 7 1%
606
997 100% 5 1%
Next is to plot the results of pdf and cdf in the
table into graphical form, where the cdf results are
drawn in scatter form, while the pdf results are in the
form of a histogram as shown in Figure 6.
Figure 6: PDF and CDF Graph Results 1000 Times
Iteration.
From the graph above shows the results of the
Monte Carlo simulation in the form of PDF and
CDF graphics, where CDF is the blue line, while the
PDF is an orange-colored histogram. The x-axis in
the graph above shows the duration of the project
completion in days. The y-axis on the graph shows
the probability. Percentile is the division of 100 data
positions sorted in a distribution. From the graph
above it is found that for percentiles / 50%
probability, the project can be completed in 594 days
or less. Whereas for 80% percentile / probability, the
project can be completed in 598 days or less.
After calculating, it is found that completion of
the project for less than 595 days has a 56% chance
of success, or that the project 44% has a chance to
be late. And a 100% chance of success of the project
is estimated within 606 days.
4.6 Analysis using the Time Cost Trade
off Method
Analysis of the Time Cost Trade Off method is an
analysis by exchanging time and costs so that it can
speed up the project completion time but result in an
increase in costs. In this research, the project time is
accelerated in activities that are on the critical path
by increasing the worker's overtime hours. In adding
workers' melting hours there are government
regulations that must be followed by the contractor.
A. Crash Duration Calculation
The following is an example of the calculation of the
duration of the crash carried out in this project on
Dia Concrete Pile Work. 1000 mm Bottom Type C0
for additional one hour of work:
Normal duration = 316 days
Job Weight = 5.108%
Productivity per hour = 0.00202057% per hour
Daily productivity crashes=0.01798307% per day
Overtime hours will result in a decrease in daily
productivity experienced by workers from normal
productivity. This is caused by several factors, such
as worker fatigue, limited visibility, and cooler
temperatures at night.
Table 10: Productivity Coefficient of Overtime Worker.
Extra
time
Productivity
Decrease
Index
Decreased
Work
Performance
(per hour)
Percentage o
f
Decreased
Job
Performance
(%)
Productivity
Coefficient
a B c = a x b d = c x 100 E = 100%-d
1
0,1 0,1 10 0,9
2
0,1 0,2 20 0,8
3
0,1 0,3 30 0,7
After getting the productivity coefficient, the
next step is to calculate the crash duration of each
activity. The following tables are the results of crash
duration calculations for each activity.
Crash Duration = (work weight) / (Daily
productivity after crash)
(2)
Table 11: Crash Duration of One Hour Overtime.
Activity
Duration Quality
Crash Duration
(Days)
Days % 1 Hour
Stake out dan
Positioning
47 0.0580 42
Work Dump Soil
124 4.1640 111
Work Pile Rigid
28 2.0250 25
Work Rigid
35 0.8560 31
Work Paving Block
35 0.3790 31
Structure
91 2.4610 82
Work Building Support
126 2.6146 113
Work Mechanical
154 0.5201 138
Work Plumbing
154 0.3050 138
Work Hoist Crane
28 0.0290 25
Work Electrical
91 5.2886 82
Testing And
Commissioning
127 0.1076 114
Time Acceleration Analysis of the Kijing Terminal Development Project in Mempawah, West Kalimantan
127

Table 12: Crash Duration of Two Hours Overtime.
Activity
Duration Quality
Crash Duration
(Days)
Days % 2Hour
Stake out & Positioning
47 0.0580 39
Work Dump Soil
124 4.1640 103
Work Pile Rigid
28 2.0250 23
Work Rigid
35 0.8560 29
Work Paving Block
35 0.3790 29
Structure
91 2.4610 76
Work Building Support
126 2.6146 105
Work Mechanical
154 0.5201 128
Work Plumbing
154 0.3050 128
Work Hoist Crane
28 0.0290 23
Work Electrical
91 5.2886 76
Testing And
Commissioning
127 0.1076 106
Table 13: Crash Duration of Three Hours Overtime.
Activity
Duration Quality
Crash Duration
(Days)
Days % 3Hour
Stake out dan
Positioning
47 0.0580 37
Work Dump Soil
124 4.1640 98
Work Pile Rigid
28 2.0250 22
Work Rigid
35 0.8560 28
Work Paving Block
35 0.3790 28
Structure
91 2.4610 72
Work Building
Support
126 2.6146 100
Work Mechanical
154 0.5201 122
Work Plumbing
154 0.3050 122
Work Hoist Crane
28 0.0290 22
Work Electrical
91 5.2886 72
Testing And
Commissioning
127 0.1076 101
B. Crash Cost Calculation
Addition to the cost of acceleration (crash cost)
made on the crash program carried out at the direct
cost (direct cost), which is done in addition to labor
costs due to overtime. Indirect costs can be assumed
to be the same as the budget plan (RAB) obtained.
The wages for workers on the Kijing terminal
construction project in Mempawah, West
Kalimantan are as follows:
Salary per day (normal) = Rp140,000.00
Hourly salary (normal) = Rp. 17,500.00
Salary per day (1 hour crash) = Rp166,250.00
Salary per day (2 hour crash) `= Rp.201,250.00
Salary per day (3 hour crash) = Rp236,250.00
After calculating workers' salaries by adding
overtime hours, we can find the total cost of
manpower due to the addition of overtime hours
with the following calculation: Total crash cost =
Subcontract & material costs + total manpower
wages. Here is a table of the results of the
calculation of the crash cost for each activity on the
critical path with each additional overtime hours.
Table 14, 15, and 16 show the crash cost
calculation results for each activity on the critical
path with each additional overtime.
C. Cost Slope Calculation
In accelerating using the time cost trade off method,
it is necessary to find the lowest cost slope to find
out the optimum overtime clock scheme. The
following is a cost slope calculation performed on
the acceleration of the critical path with the addition
of overtime hours.
Cost slope = (Crash Cost-Normal Cost) /
(Normal Duration-Crash Duration)
(3)
After calculating the cost slope for each scheme
to add overtime hours, a cost slope of Rp 6,169,070
per day is obtained for the addition of 1hour
overtime, Rp 6,822,825 per day for the addition of 2
hours overtime, and Rp 8,587,193 per day for
addition of 3 hours overtime. So, the addition of 1
hour overtime is the most optimum scheme obtained
in this study. A comparison can be seen in the table
17 and figure 7.
Figure 7: Cost Slope graph for each additional overtime
hours.
5 CONCLUSION
From the results of the analysis of the acceleration of
the duration of the Kijing sea terminal development
project in Mempawah, West Kalimantan using the
PDM method, Monte Carlo and the Time Cost Trade
Off method, the following conclusions are obtained:
1. Activities that are on the critical path are activities
that have a total float = 0. And activities that have
a total float = 0 are as follows: Stake Out And
Positioning (A3) - Landfill Work (E1) - Rigid
Concrete Work (E2) - Rigid (F1) Work - Paving
Block (F2) Work - Structure (G1) –
2. Supporting Buildings (G2) - Mechanical Work
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128

(H1) - Plumbing Work (H2) - Hoist Crane Work
(H3) - Electrical Work (H4) - Testing and
Commissioning (H5).
3. The probability of the Kijing sea terminal
development project in Mempawah, West
Kalimantan being completed on time with a
duration of 595 days based on the project contract
is 55%, or the project has a 45% chance of being
late. Based on the results of the Monte Carlo
method, the Kijing sea terminal development
project in Mempawah, West Kalimantan can be
completed on time with a duration of 606 days.
4. The optimum duration and costs on the critical
path are obtained by adding 1 hour of overtime.
The total duration of the project which was
originally 595 days to 513 days with a difference
of 82 days, with a minimum total cost of
Rp2,740,269,901,670 to Rp 2,740,775,765,420
with a difference of Rp505,863,750 and also The
smallest cost slope of the other overtime hours
scheme is IDR 6,169,070 per day.
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APPENDIX
Table 14: Crash Cost of One Hour Overtime.
Activity
Sub-cont&material cost
Man power
Manpower
Total (Crash)
Total Crash Cost
Rp Rp Rp
Stake out & Positioning
1.530.136.543 9 70.323.750 1.589.356.543
Work Dump Soil
113.740.278.706 21 432.915.000 114.104.838.706
Work Pile Rigid
55.470.865.509 5 23.275.000 55.490.465.509
Work Rigid
23.422.410.358 7 40.731.250 23.456.710.358
Work Paving Block
10.351.322.927 7 40.731.250 10.385.622.927
Structure
67.234.202.280 16 242.060.000 67.438.042.280
Work Building Support
71.329.576.849 18 377.055.000 71.647.096.849
Work Mechanical
13.691.583.759 26 665.665.000 14.252.143.759
Work Plumbing
7.797.263.200 26 665.665.000 8.357.823.200
Work Hoist Crane
775.078.271 5 23.275.000 794.678.271
Work Electrical
144.718.074.020 16 242.060.000 144.921.914.020
Testing And Commissioning
2.628.490.414 18 380.047.500 2.948.530.414
Time Acceleration Analysis of the Kijing Terminal Development Project in Mempawah, West Kalimantan
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Table 15: Crash Cost of Two Hours Overtime.
Activity
Sub-cont&material cost
Manpower
Manpower
Total (Crash)
Total Crash Cost
Rp Rp Rp
Stake out & Positioning
1.530.136.543 9 85,128,750 1,615,265,293
Work Dump Soil
113.740.278.706 21 524,055,000 114,264,333,706
Work Pile Rigid
55.470.865.509 5 28,175,000 55,499,040,509
Work Rigid
23.422.410.358 7 49,306,250 23,471,716,608
Work Paving Block
10.351.322.927 7 49,306,250 10,400,629,177
Structure
67.234.202.280 16 293,020,000 67,527,222,280
Work Building Support
71.329.576.849 18 456,435,000 71,786,011,849
Work Mechanical
13.691.583.759 26 805,805,000 14,497,388,759
Work Plumbing
7.797.263.200 26 805,805,000 8,603,068,200
Work Hoist Crane
775.078.271 5 28,175,000 803,253,271
Work Electrical
144.718.074.020 16 293,020,000 145,011,094,020
Testing And Commissioning
2.628.490.414 18 460,057,500 3,088,547,914
Table 16: Crash Cost of Three Hours Overtime.
Activity
Sub-cont&material cos
t
Manpower
Manpower
Total (Crash)
Total Crash Cost
Rp Rp Rp
Stake out & Positioning
1.530.136.543 9 99,933,750 1,630,070,293
Work Dump Soil
113.740.278.706 21 615,195,000 114,355,473,706
Work Pile Rigid
55.470.865.509 5 33,075,000 55,503,940,509
Work Rigid
23.422.410.358 7 57,881,250 23,480,291,608
Work Paving Block
10.351.322.927 7 57,881,250 10,409,204,177
Structure
67.234.202.280 16 343,980,000 67,578,182,280
Work Building Support
71.329.576.849 18 535,815,000 71,865,391,849
Work Mechanical
13.691.583.759 26 945,945,000 14,637,528,759
Work Plumbing
7.797.263.200 26 945,945,000 8,743,208,200
Work Hoist Crane
775.078.271 5 33,075,000 808,153,271
Work Electrical
144.718.074.020 16 343,980,000 145,062,054,020
Testing And Commissioning
2.628.490.414 18 540,067,500 3,168,557,914
Table 17: Calculation of Cost Slope.
Activity
Sub-cont&material cos
t
Manpower
Manpower
Total (Crash)
Total Crash Cost
Rp Rp Rp
Stake out & Positioning
1.530.136.543 9 85,128,750 1,615,265,293
Work Dump Soil
113.740.278.706 21 524,055,000 114,264,333,706
Work Pile Rigid
55.470.865.509 5 28,175,000 55,499,040,509
Work Rigid
23.422.410.358 7 49,306,250 23,471,716,608
Work Paving Block
10.351.322.927 7 49,306,250 10,400,629,177
Structure
67.234.202.280 16 293,020,000 67,527,222,280
Work Building Support
71.329.576.849 18 456,435,000 71,786,011,849
Work Mechanical
13.691.583.759 26 805,805,000 14,497,388,759
Work Plumbing
7.797.263.200 26 805,805,000 8,603,068,200
Work Hoist Crane
775.078.271 5 28,175,000 803,253,271
Work Electrical
144.718.074.020 16 293,020,000 145,011,094,020
Testing And Commissioning
2.628.490.414 18 460,057,500 3,088,547,914
ISOCEEN 2019 - The 7th International Seminar on Ocean and Coastal Engineering, Environmental and Natural Disaster Management
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