Eduvest � Journal
of Universal Studies Volume 1 Number 8, August 2021 p- ISSN
2775-3735 e-ISSN 2775-3727 |
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DETERMINATION OF TRANSPORT ROUTES USING THE SAVING MATRIX METHOD AT PT
XYZ |
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Anisa
Natasari, Hilal Ali Azzim, Fahrul Arifin and Muchammad Fauzi Widyatama University Bandung E-mail: [email protected],
[email protected], [email protected] and [email protected] |
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ARTICLE
INFO������� ABSTRACT |
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Received: July,
24th 2021 Revised: August,
16th 2021 Approved: August,
18th 2021 |
PT
XYZ is a company engaged in manufacturing that produces electronic components
and installation services for these components. In this study, the company
will send components and help install them in nine locations in Sumatra. The
analysis of determining distribution routes uses the saving matrix method.
The results of the analysis using the saving matrix method show that the
original distribution distance of 9926 kilometers can be reduced to 2937.7
kilometers, which means that the distance can be shortened and more efficient
by 70% or around 6988.3 kilometers. The original cost was Rp.
54,386 .000 down to Rp. 16,716,000 Thus there is a
distribution channel savings of Rp. 37,670,000 or
about 69.2%. |
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KEYWORDS |
Saving Matrix Method,
Efficiency, Transportation Costs. |
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This
work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International
License |
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INTRODUCTION
Consumer demands for quality, product, price, better
service, delivery accuracy (Adianto,
2018) and product
availability on the market are currently getting higher (Santoso,
Mustaniroh, & Pranowo, 2018) and proper
distribution is needed (Karundeng,
Mandey, & Sumarauw, 2018). Effectiveness in
choosing the right destination route will reduce waste in terms of cost, time
and power (Trisna,
Fatimah, & Nasution, 2019).
Product allocation and determining the route of
delivery of goods are important in an industry (Ardhyani,
2017), both small and large
scale industries (Musita,
2018). Errors in determining
distribution channels (Sibarani,
2013) and delays in product
delivery can hinder the distribution of products from producers to consumers (Karundeng
et al., 2018), which can result in
reducing company profits and can also have the potential for losses to the
company (Marchelia,
2014).
In an effort to minimize product distribution
transportation costs (Huda,
2018), companies must pay
attention to the existing transportation network system (Trisna
et al., 2019). The transportation
network system can be seen in terms of effectiveness (Wulandari & Sudiana, 2018), in terms of safety,
high accessibility, integrated, sufficient capacity, orderly, smooth, fast,
easy to reach, timely, comfortable, affordable, orderly, safe (Razi
& SUMBERDAYA, 2014), and low in pollution
as well as in terms of efficiency in transportation (Sitorus,
Hidayat, & Prasetya, 2014). the meaning of having
a high utility in a unified transportation system network (Amin,
Hamidi, & Ekwarso, 2017).
To anticipate this problem, we need a method that can
provide minimal product distribution costs (Putra
& Handayani, 2018). The Savings Matrix
method is a method used to determine product distribution routes (Supriyadi,
Mawardi, & Nalhadi, 2017) to marketing areas by
determining the distribution routes that must be passed (Bimantara,
2018) and the number of
vehicles based on vehicle capacity in order (Muziansyah,
2015) to obtain the shortest
route and minimal transportation costs (Huda,
2018). The Savings Matrix
method is also one of the techniques (Ikfan
& Masudin, 2014) used to schedule a
limited number of vehicles from facilities that have a maximum capacity (Suparjo,
2017).
By using the Savings Matrix Method, it is hoped that it can help overcome the problems above, so
that the company is able to plan well for each installation item that will be
sent.
RESEARCH METHODS
The Savings Matrix method is a method used to
determine product distribution routes to marketing areas by determining the
distribution routes that must be passed and the number
of vehicles based on vehicle capacity in order to obtain the shortest route and
minimal transportation costs. The Savings Matrix method is also one of the
techniques used to schedule a limited number of vehicles from facilities that
have a maximum capacity. By using the Savings Matrix method, it is expected to be able to answer research problems, and the
company is able to make plans for each installation that will be sent. The data
used in this study are as follows:
1. Primary data is data that is
specifically taken for the sole purpose of research, which is obtained
from the results of interviews.
2. Secondary Data is data obtained from references
originating from sources such as companies, namely PT XYZ Project Cost Data.
RESULTS AND DISCUSSION
A.
Consumer Demand Data
Table 1 is data on consumer demand for product
shipments and installations in January 2021.
Table 1.
Data on Demand for Delivery of Goods and Installation
No |
Location
Code |
Installation
Request |
1 |
A |
2 |
2 |
B |
2 |
3 |
C |
1 |
4 |
D |
2 |
5 |
E |
1 |
6 |
F |
2 |
7 |
G |
2 |
8 |
H |
2 |
9 |
I |
2 |
Source: Data Cost Project PT XYZ |
B.
Initial Route
The
company divides the distribution and installation into 2 groups due to limited
material for that month. Each group is able to serve a maximum of 8 sites in 9 different locations. The company's initial
routes amounted to 9 routes with a total distance
generated on this initial route of 9926 kilometers. The distance on the initial
route is considered too long and must be trimmed so as
not to incur transportation costs and long delivery times.
C.
Installation Distance Data
Data on the distance between the company and the
installation location and the distance between locations are
shown in Table 2 and Table 3.
Table
2. Initial Route and Distance
No |
�Location |
Distance
(km) |
1 |
P-A-P |
606 |
2 |
P-B-P |
996 |
3 |
P-C-P |
1612 |
4 |
P-D-P |
600 |
5 |
P-E-P |
858 |
6 |
P-F-P |
996 |
7 |
P-G-P |
1600 |
8 |
P-H-P |
1038 |
9 |
P-I-P |
1620 |
Source: Data Cost Project PT XYZ |
Table
3. Distance between Locations
|
P |
A
|
B |
C |
D |
E |
F |
G |
H |
I |
P |
0 |
303 |
498 |
806 |
300 |
429 |
498 |
800 |
519 |
810 |
A |
|
0 |
264 |
527 |
13 |
165 |
264 |
566 |
288 |
576 |
B |
|
|
0 |
342 |
255 |
165 |
0 |
336 |
215 |
346 |
C |
|
|
|
0 |
560 |
370 |
342 |
16.6 |
485 |
4,9 |
D |
|
|
|
|
0 |
156 |
254 |
555 |
284 |
567 |
E |
|
|
|
|
|
0 |
168 |
470 |
234 |
481 |
F |
|
|
|
|
|
|
0 |
336 |
215 |
346 |
G |
|
|
|
|
|
|
|
0 |
481 |
9,8 |
H |
|
|
|
|
|
|
|
|
0 |
487 |
�I |
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|
|
|
|
|
|
|
|
0 |
Source:
data processing |
D.
Initial Transportation Fee
Initial transportation costs are
taken based on company data. Initial transportation costs are listed in Table 4.
Table
4. Initial Transportation Cost
No |
Location |
Distance (km) |
Labor Costs |
Transportation and BBM |
Shipping Costs |
1 |
A |
303 |
Rp.
2.958.000 |
Rp. 500.000 |
Rp.
3.400.000 |
2 |
B |
498 |
Rp.
2.069.000 |
Rp. 550.000 |
Rp.
3.400.000 |
3 |
C |
806 |
Rp.
1.770.000 |
Rp. 275.000 |
Rp.
3.400.000 |
4 |
D |
300 |
Rp.
1.770.000 |
Rp. 0 |
Rp.
3.400.000 |
5 |
E |
429 |
Rp.
1.770.000 |
Rp. 350.000 |
Rp.
3.400.000 |
6 |
F |
498 |
Rp.
2.069.000 |
Rp. 550.000 |
Rp.
3.400.000 |
7 |
G |
800 |
Rp.
2.950.000 |
Rp. 1.300.000 |
Rp.
3.400.000 |
8 |
H |
519 |
Rp.
1.170.000 |
Rp. 375.000 |
Rp.
3.400.000 |
9 |
I |
810 |
Rp.
2.360.000 |
Rp. 1.000.000 |
Rp.
3.400.000 |
Total |
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Rp.
54.386.000 |
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Source: PT XYZ project cost data |
E.
Identify the Savings Matrix
Saving Matrix is
obtained by combining two or more location routes
simultaneously. The merger is adjusted to the number
of consumer requests and the number of combinations is not allowed to exceed
the capacity of the transportation means. The table of the savings matrix can be seen in Table 5.
Table
5. Matrix for Savings
|
A |
B |
C |
D |
E |
F |
G |
H |
I |
|
A |
- |
573 |
528 |
590 |
537 |
537 |
537 |
534 |
537 |
|
B |
|
- |
962 |
543 |
762 |
996 |
962 |
802 |
962 |
|
C |
|
|
- |
546 |
865 |
962 |
1590 |
840 |
1611 |
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D |
|
|
|
- |
573 |
544 |
545 |
535 |
543 |
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E |
|
|
|
|
- |
759 |
759 |
714 |
758 |
|
F |
|
|
|
|
|
- |
96.2 |
802 |
962 |
|
G |
|
|
|
|
|
|
- |
838 |
1600 |
|
H |
|
|
|
|
|
|
|
- |
842 |
|
I |
|
|
|
|
|
|
|
|
- |
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Source:
data processing |
F.
Installation Request Allocation
Allocation
of consumer demand can be started by looking at the
value of the greatest savings. The allocation of each different location can be combined up to the limit of the carrying capacity.
The results of the merging of routes can be explained
in Table 6. The number of routes originally was 9.
After combining, the number of routes became 2. The
total load transported was still below the maximum capacity of the
transportation equipment, which was 8 pieces. Thus, both routes can be used.
Table 6.
Allocation of consumer demand
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No |
Route |
Consumer |
Total Transport |
Information |
Transport Capacity |
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1 |
Route 1 |
0
� C �I � G � F � C - 0 |
8 |
OK |
8 |
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2 |
Route 2 |
0
� H � B � D � A � 0 |
8 |
OK |
8 |
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Source: data processing Table 7 Nearest method |
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No |
Route |
Consumer
|
Total
Distance |
Fuel
Transportation |
Labor |
Cost
Shipping |
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1 |
Rute 1 |
0 � C �I � G � F � C - 0 |
1632.7 |
Rp. 2.000.000 |
Rp. 2.958.000 |
Rp. 3.400.000 |
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2 |
Rute 2 |
0 � H � B � D � A � 0 |
1305 |
Rp. 2.000.000 |
Rp. 2.958.000 |
Rp. 3.400.000 |
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Total |
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2937.7 |
Rp. 16.716.000 |
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Source: data processing |
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G.
Routing
Determination
of the product distribution route starts from the process of identifying the
distance matrix. This process requires data on the distance between the
warehouse to each location and the distance between locations. The next step is
to identify the savings matrix. (Suparjo, 2017)
Saving matrix is realized by combining 6
or more locations into one route.
The
company still implements product delivery using one line, namely from
warehouse-location1 - warehouse and warehouse - location 2-warehouse and so on.
These conditions can make the product distribution process take longer, longer
distances, and more distribution costs. Therefore, a route change is needed
that can combine several locations into one route.
Merging
these routes can save the number of routes, distance, and distribution costs.
By referring to the savings matrix table, the allocation process can be carried out. The allocation of each location into one
route can be combined up to the capacity limit of the
company's transportation equipment (Suparjo, 2017).
The merger starts with the largest savings value. Starting from the saving value
of 1611 which is the savings from combining location C
and location I. The number of installation requests at both locations is 2 sites while the maximum total is 8 sites. The total is
still below the maximum capacity limit of 8 sites.
Thus, the merger is feasible, location C and location I are
merged into route 1, and so on. Next is to sort the locations in a predefined
route.
H.
Route Comparison and Initial Transportation Costs
The
comparison of product distribution routes before the saving matrix method is
applied and after is very clear. Initially, the company had 9
routes for delivery and installation at a site. The total distance traveled by
the company during the process of shipping goods and installation at 9 locations is 9926 kilometers. This makes the cost to the
company is also not small, namely Rp. 54,386,000.
After applying the saving matrix method, the number of routes, total distance,
and product distribution costs in the company experienced a significant
decrease with the assumption that labor costs and transportation costs were the
highest from the initial 9 routes. The company can
reduce the mileage by 6988.3 kilometers or about 70%. Product distribution
costs also experienced savings of IDR 37,670,000 or 69.2%.
CONCLUSION
The most appropriate shipping route to minimize
transportation/distribution costs at PT XYZ can be reduced to a total of 9 routes from 2 routes. The initial distance to
send goods must be covered as far as 9926 kilometers
with a transportation cost of Rp. 54,386,000. Thus,
the company can save about 70% or 6988.3 kilometers of distance and can reduce product delivery distribution costs up to 69.2% or Rp. 37,670,000.
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