Mapping the Physical Properties of Soils and the California Bearing

Ratio (CBR) Value for Different Soil Types: A Case Study in the Bukit

Kemuning and Pugung Tampak Areas

LUSMEILIA AFRIANI1, NURSYIRWAN2, RYZAL PERDANA3, RINA FEBRINA4

YAN JUANSYAH4

Abstract: - It is widely accepted that soil is a mixture of mineral constituents that have accumulated over time.

The physical characteristics of soil vary according to the mineral and organic matter content and the

process of formation. The soil's unique characteristics have been the subject of research in the field of

civil engineering, which has continued to evolve to the present day due to the land's requirement for

civil engineering construction, such as road paving. As a result, the current study sought to determine

the similarity of soil samples based on their physical properties and California Bearing Ratio (CBR)

values, as well as the relationship between the soil's physical properties and CBR values. To our

knowledge, there is hardly little research in the literature investigating the topic under our

investigation. Furthermore, we also mapped the physical characteristics and CBR values of numerous

distinct soil samples using a Geographical Information System (GIS). This study concentrated on the

West Lampung Regency, specifically the area between Bukit Kemuning in Central Lampung and

Liwa in West Lampung, along the lines of Bukit Kemuning, Liwa, and Krui, all the way to the

Lampung – Bengkulu province border. The soil samples from the area were taken for two tests: the

unsoaked CBR test and the soaked CBR test. The results of the tests show that a 31-kilometre distance does

not result in a significant difference in soil properties, which are generally similar except in clay-rich areas.

Furthermore, the results of the laboratory analysis show that the amount of water in the soil sample affects the

Liquid Limit (LL), Plastic Limit (PL), Maximum Dry Density (MDD), and CBR values; the lower the plastic

limit value, and thus the lower the CBR value, the less water in the soil. The implications of the current

findings are also discussed.

Key-Words: - California Bearing Ratio, soil physical properties, soil types, construction, pavement

Received: April 30, 2021. Revised: November 11, 2021. Accepted: December 12, 2021. Published: January 9, 2022.

1 Introduction

It is publicly accepted that soil is a material

composed of a variety of mineral constituents that

have accumulated over time [1]–[3]. It is reported in

the literature that almost no two soil types are

identical in terms of physical and mechanical

characteristics [4], despite the fact that they are

extracted from adjacent areas. Thus, the uniqueness

of this soil's nature necessitates additional research

[5], [6]. Therefore, we aim to be able to map the

state of soil qualities and serve as a model for other

areas in theory, looking for methods to specific soil

structures.

The reason for soil composition differences

begins with the way the soil is formed and the

material content of the soil. Thus, the soil material is

referred to as organic material or organic matter.

Additionally, soil materials can be classified as

cohesive or non-cohesive, depending on the

particle's tendency to stick together [7], [8]. The

physical properties of soil include its structure,

porosity, density, and fertility, all of which have a

1Department of Civil Engineering, Faculty of Engineering, University of Lampung, INDONESIA

2Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Lampung,

INDONESIA

3Department of Educational Sciences, Faculty of Teacher Training and Education, University of

Lampung, INDONESIA

4Department of Civil Engineering, Faculty of Engineering, Universitas Malahayati, INDONESIA

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E-ISSN: 2224-3496

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positive and significant effect on the elements

contained within [9]–[11].

The soil's unique nature has been the subject of

research [6] in the field of civil engineering, which

has continued to develop to the present day because

the land is required to support civil engineering

construction, such as road paving. Physical

characteristics of soil vary according to the amount

of mineral and organic matter present and the

formation process [12]. The spatial variability of

soil physical properties is revealed at a large scale

by capturing its variations using geostatistics from a

few metres to kilometres based on variograms and

variables [13]–[19].

In general, the pavement must be capable of

bearing the weight of the vehicles that pass through

it. The road surface can withstand the friction

generated by the wheels, as well as the effects of

rainwater [11]. If the pavement is not strong enough,

the road will deteriorate and shear, both on the

pavement and on the subgrade. As a result, the road

will suffer damage, specifically in the form of small

holes that will eventually become large holes,

destroying the pavement completely. To deeply

investigate this, a California Bearing Ratio (CBR)

test is one of the subgrade mechanical strength tests.

The CBR is a penetration test that is used to

determine the mechanical strength of subgrades for

new road construction. The California Department

of Transportation developed CBR tools prior to

World War II [20].

CBR testing is conducted in the laboratory and

in the field using CBR test equipment. The CBR test

is also referred to as a penetration test because it is

used to determine the fundamental strength of roads,

parking lots, and sidewalks. The results of this test

are combined with empirical curves to determine the

road's and component layers' thickness. This is the

most frequently used method for designing flexible

pavements [21], [22].

Furthermore, the strength of the subgrade is

dependent on its moisture content. The higher the

water content, the weaker the soil's CBR strength.

There is extensive local experience with a specific

soil type [23]. This does not mean that the subgrade

should be compacted with low moisture content in

order to achieve a high CBR value, as the moisture

content of the soil will soften during compacting

[24]. Following road construction, water will be

able to seep into the subgrade, reducing the CBR

strength until the moisture content reaches a

constant value [25], [26]. The so-called "balanced

water content" refers to this constant water content.

The moisture content and dry bulk density limits can

be determined using laboratory experiments,

specifically compaction and CBR tests. The CBR

experiment can be conducted in two ways: unsoaked

or soaked [27], [28].

Therefore, in the Bukit Kemuning and Pugung

Tampak areas, we sought to determine the similarity

of soil samples based on the physical qualities of the

soil and the CBR value, as well as the relationship

between the physical properties of the soil and the

CBR value. To our knowledge, there is hardly little

research in the literature investigating the topic

under our investigation. We also mapped the

physical characteristics and CBR values of

numerous distinct soil samples using a Geographical

Information System (GIS) [29]–[31]. The CBR

value and the physical parameters of the soil were

utilised to identify the characteristics of a soil

sample. A map was created using the findings of

laboratory test data processing and GIS applications.

Using spatial databases linked to geographic

features in GIS, it is possible to identify places that

can be utilised as road bodies immediately or that

need to be treated before being used [32], [33].

2 Materials and Methods

This study concentrated on the West Lampung

Regency, specifically the area between Bukit

Kemuning in Central Lampung and Liwa in West

Lampung, along the lines of Bukit Kemuning, Liwa,

and Krui, all the way to the Lampung – Bengkulu

province border (see Figure 1). Because this area is

prone to minor earthquakes and is hilly, it receives a

lot of rain. The soil sample taken served as a

reference for the road repair plan because road

improvement work was going on in the area at the

time of the investigation.

Fig. 1: Research Site

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The soil samples from the area were taken for

two tests: the unsoaked CBR test and the soaked

CBR test. Soaked CBR values were obtained by

immersing soil samples in water for four days.

Fig. 2: CBR Test Equipment

Source: [34]

The basic premise of CBR testing is to propel a

plunger cylinder with a diameter of 50 mm into the

soil or pavement component material to be tested at

a velocity of 1.25 mm per minute. The weights

necessary to cause plunger penetration of 2.5 mm

and 5.0 mm in the soil/material under test are

recorded [35]. The CBR test is primarily used to

determine the modulus and shear strength of

subgrades. The ductile modulus of the subgrade,

which has been connected with the CBR in the

American Association of State Highway and

Transportation Officials (AASHTO) design code,

determines the pavement layer thickness [36].

To obtain particles smaller than No. 4, the soil

was drained and sieved. The filter's output could be

used to display the physical characteristics of the

soil, such as its plastic properties at various moisture

levels. The compaction value was determined in the

first experiment. The optimum moisture content and

maximum dry density were obtained using a

standard proctor.

Each test parameter was run three times, with

the averaged result. Soil samples were taken in two

ways: undisturbed and disturbed. As needed, the

sample quantity was used. The soaked CBR test was

required to anticipate when rainwater puddled and

soaked into the soil, causing the soil's strength to

deteriorate. The lowest score was used as the

benchmark by the planner. The results of the soil

physical properties experiment, such as moisture

content, density, volume weight, plasticity index,

compaction, and CBR, were presented in the form

of figures and graphs depicting the relationship

between the two.

In addition, Gabriel introduced a bi-plot

analysis, which was used to map soil characteristics,

in 1971. Essentially, by superimposing vectors in a

low-dimensional space, this analysis attempts to

provide a graphical display of the X data matrix in a

plot [37]. A set of objects was positioned and

perceptually mapped using this analysis (rows from

the X data matrix). The bi-plot analysis process

necessitates data from a variety of objects with

attributes (columns from the data matrix X) that are

measured using interval and ratio scales. The

analysis' final results are displayed in the form of a

two-dimensional image display that includes

information about (1) the object's relative position.

Two objects with the closest distance are said to

have a high level of similarity based on the observed

attributes based on this information; and (2). the

relationship between attributes. Based on this data,

the linear relationship (correlation) between

attributes and the level of importance of an attribute

based on its variants can be determined. A bi-plot is

a graph that combines information (1) and (2). The

observed attributes were used to determine the

characteristics of each object.

3 Results and Discussion

Because the soil is made up of boulders of various

shapes and sizes, the behaviour of the subgrade is

determined by the natural conditions in which the

soil is formed [38]–[40]. This is demonstrated by

the fact that the rock mineral content is nearly

identical to that of the soil. Rocks of the Tuff type,

such as Tuff Pasiran, are commonly found in West

Lampung province [32]. Sandy tuff has a fresh grey

to brownish grey colour, a medium to coarse

texture, a round to very round grain shape, is well

sorted, has good permeability, can be kneaded, and

contains mica and pumice [33].

The main road to several areas in West Sumatra

was used for the research. This route begins in the

Bukit Kemuning area, which is administratively part

of the North Lampung Regency. Given that the

western route of Liwa – Bukit Kemuning is

currently used as a feeder road, its function is

critical. Every day, various types of large tonnage

vehicles and even vehicles between provinces travel

this route. Surprisingly, this path has the same rock

diversity as the previous one, but part of the route is

an earthquake path. It is a route that passes through

a hilly topographic area with a steep slope to a very

steep slope in the West Lampung area. The

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occurrence of landslides on the slopes along this

route is common, resulting in access loss.

In Lampung Province, which faces a high risk

of geo-disasters, the West Lampung area is one of

the most vulnerable areas. This area is formed by

young volcanic rocks that have not been properly

consolidated in terms of geology [41]. The

morphology consists of steep, wavy hills with deep

valleys that are traversed by rivers with a very low-

density level and are located between 500 and 1200

metres above sea level [32], [42]. It contains grains

of rock ranging in size from fine to large. Because

this location feels as though it has been exposed to

altitude and is a part of the plain with an average

elevation of 800 – 1,400 metres above sea level, it

experiences high rainfall.

From this intriguing case, a study was

conducted in which a sample was taken in a

disturbed manner and placed in a sack as research

material. The soil's physical properties and

unsoaked CBR values were determined in this

study. The CBR value can serve as a reference point

for planning road construction, parking lots, and

other infrastructure projects. The soil density and

CBR values were determined from the subgrade to

the pavement's top layer [38], [40], [43]. If the CBR

value is less than 6%, the land cannot be used as a

road body, or it can be used for trafficking purposes

to increase the CBR value above 6%. One of them is

compaction or soil replacement.

The soil properties, compaction, and CBR

values (see Table 1) obtained during the research

were statistically plotted using the Bi-plot method.

The Bi-plot method's output allows for easy

mapping of the study area's soil type. According to

laboratory analysis, the clay soils that comprise the

study area are generally classified as heavy clay

(CH) and heavy silt (MH) soil types, referring to the

Unified Soil Classification System (USCS), with a

high degree of plasticity; this classification is based

on the AASHTO classification system [5], [39].

Table 1. CBR Values and Physical Properties

Fig. 3: Soil Sample Analysis at KM 293 + 500

As illustrated in Figure 2, the KM 293 + 500

soil sample has high values for the Atterberg Limits

PL, LL, and Water Content (w). While soil samples

from the KM 294 + 500 and KM 295 + 500 areas

exhibit identical physical properties, according to

the data, the percentage of data that passed the No.

200 indicates that the Percent Lose filter 200 has a

high content. This indicates that the area's soil

contains a high concentration of clay. Physical

properties of the soil, such as the Water Content

(W), correlate positively with the Atterberg Limits

of Plastic Limit (PL), Liquid Limit (LL). This

means that increasing the amount of water in a soil

sample increases the value of soil plasticity,

specifically the Plasticity Index (PI) and LL.

Additionally, as shown in Table 1, soil samples

containing the Percent Lose filter value exhibit a

positive correlation with the optimum water content

value (W Opt), implying that the higher the Percent

Lose filter value content in the soil sample, the

higher the W Opt. The values of the Atterberg

Limits PL, LL, W Opt, Water Content (W), and PI

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are inversely related to CBR. This means that as the

CBR value in the soil sample increases or decreases,

the moisture content of W Opt, the Atterberg Limits

PL, LL, W Opt, W, and PI decreases.

The area surrounding the sampling location

exhibits similar soil conditions based on the

sampling location's five points. The formed line

indicates that the soil conditions are at node O. This

indicates that the soil conditions in these locations

are similar, implying that the soil parameters are

uniformly similar. This minor variation is reflected

in the circles created. Soil parameters are relatively

uniform. It is simply that the difference in the

condition of the per cent passed through the 200

sieves indicates that there are two locations with

varying clay contents, namely those with high clay

content. This is also illustrated in Table 1 and Figure

The CBR value, on the other hand, remains

high. This frequently occurs because the soil

sampled has a high clay content but also contains

sand and gravel. As a result, the CBR value is quite

high. However, in this case, the CBR value is nearly

uniform when compared to soil samples from other

locations, despite the fact that the clay content of the

soil varies.

The physical characteristics of the other area,

which is 4 kilometres long with sampling at seven

test locations, are discussed in Figure 4.

Fig. 4: Soil Sample Analyses at KM 297 + 500, 299

+ 000, 298 + 000, 303 + 000, 296 + 000, KM 299 +

500 and 301 + 000

In Figure 4 above, soil samples are classified

into two groups based on their physical properties

and CBR values: group 1 (KM 297 + 500, 299 +

000, 298 + 000, 303 + 000, and 296 + 000) and

group 2 (KM 299 + 500 and 301 + 000). Group 1

soil samples (circle on the left) contain a high CBR

value, unlike Group 2 soil samples, which contain

high Percent Lose filter values of 200, the Atterberg

Limit PL, LL, PI, W, and W Opt.

As shown in Figure 3, the physical properties of

the soil, specifically the water content, w, have a

positive correlation with the Atterberg Limits PL,

LL, W Opt, and PI. This means that as the water

content of the soil sample increases, the Atterberg

limit, PL, LL, W Opt, and PI values increase

proportionately. Meanwhile, the CBR value is

inversely proportional to W Opt, the Atterberg Limit

PL, LL, W Opt, and W. This means that the CBR

value increases as the W Opt, the Atterberg Limit

PL, LL, W Opt, W, and PI values decrease.

The classification of soil data varies by region,

or there may be an area with extremely dominant

physical characteristics. This is illustrated in Figure

Fig. 5: Soil Sample Analysis of KM 306 + 500 and

305 + 500

As illustrated in Figure 5, the KM 306 + 500

and 305 + 500 soil samples contain high values for

the Atterberg Limit PL, LL, per cent pass 200, and

W Opt. Meanwhile, the water content, w, correlates

positively with the Atterberg Limits PL, LL, PI, and

W Opt. This means that the more water in the soil,

the higher the concentrations of Atterberg Pl, LL,

PI, and W Opt. CBR values are inversely

proportional to W Opt, Atterberg Limit PL, LL, W

Opt, and W. This means that the higher the CBR

value in a soil sample, the lower the concentrations

of W Opt, the Atterberg Limit PL, LL, W Opt, W,

and PI. As a result, it can be concluded that the

moisture content of the soil has an effect on all soil

parameters. Indeed, the water content of the soil is

required, specifically as a lubricant. This frequently

occurs during compaction work in the field.

However, excessive water content results in a

reduced capacity of the soil to bear weight [5], [40],

[43]. The area around Bukit Kemuning - PD

Tambak is depicted in Figure 6, specifically, from

KM 155 + 500 to KM 166 + 500.

Figure 6 demonstrates that soil samples up to a

distance of 6 kilometres are similar, and the CBR

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value is also quite good. However, due to the

distance from Bukit Kemuning, the soil conditions

are quite harsh, as indicated by the increasing CBR

value and the increasing value of Maximum Dry

Density. The maximum dry density value is

determined through Proctor Standard, DAS, and

other experiments designed to determine the density

of soil. In this case, soil density becomes critical for

changes in CBR values.

The soil conditions at KM 157 + 000 are

slightly different in that the soil contains a high

proportion of clay, as evidenced by the higher

percentage of clay that passes through filter No. 200

when compared to other soil locations. As a result, it

will have an effect on the water content value, the

optimum moisture content, and the Atterberg Limit.

Among other physical properties, per cent loss No.

200 exhibits a great deal of variation. The Atterberg

Limit experiment results, which yielded LL and PL

values, revealed a positive or positive correlation

between soil physical properties and the Optimum

Moisture Content (OMC) (see Figure 5). This

means that as the LL value in the soil sample

increases, the PL and OMC values increase as well.

However, the CBR value is inversely proportional to

the LL, PL, and OMC values. This means that as the

Atterberg Limit LL, PL, and OMC values decrease,

the CBR value decreases as well. The percentage of

material passing through sieve No. 200 is

determined through sieve analysis experiments.

Fig. 6: Analysis of Soil Sample from KM 155 + 100

to 160 + 000

As illustrated in Figure 6, the soil samples at

KM 155 + 100 and 160 + 000 have a high CBR

value and a low density, Maximum Dry Density

(MDD). In contrast, the soil samples at KM 157 +

000 have a high water content, affecting the LL, PL

parameters. Among other physical properties, per

cent loss No. 200 exhibits a great deal of variation.

The Atterberg Limit LL soil physical properties are

positively correlated with PL, W, and W Opt. This

means that as the water content increases, the LL,

PL, and W Opt values increase as well. The CBR

value is inversely proportional to the content of the

Atterberg Limit LL, PL, W, and W Opt. This means

that the greater the CBR value, the lower the LL,

PL, W, and W Opt values will be.

The local soil conditions provide insight into the

conditions that resulted in the formation of the

rocks. This condition cannot be maintained

indefinitely, as environmental factors such as

earthquakes, heavy rainfall, chemical, biological,

and other factors all affect the rock formation (Bell;

Das), as illustrated in Figure 7 below.

Fig. 7: Soil Sample Analysis from KM 162 + 000 -

167 + 500

As illustrated in Figure 7, the KM 162 + 000

and 166 + 500 soil samples contain the Atterberg

Limit values, PL and LL. Meanwhile, the soil

sample KM 167 + 500 contains a high Percent Lose

value. Physical properties of the soil, such as water

content (WC), correlate positively with the

percentage of particles passing through filter No.

200. The higher the water content in the soil sample,

the greater the percentage of water content that

passes through filter No. 200. This means that a soil

sample with a high clay content will have higher PL

and LL values.

As illustrated in Figures 7 and 8, after

experimenting with the Atterbeg Limit method and

obtaining the LL and PL values, it is possible to

determine the soil properties, conditions, and types.

Civil engineers determine the soil type through a

series of experiments on the soil's physical

properties, including moisture content, density, the

Atterberg Limit, and filter analysis. This series of

experiments is to ensure that the condition and type

of soil are accurately determined, as this parameter

will be used in subsequent civil engineering work.

The novelty of this article is to provide

information and scientific developments for civil

engineering regarding how statistics, specifically the

Bi-plot, can assist civil engineering scientists in

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determining soil type classifications, which can then

be used to forecast the condition of soil density

values. If the soil type and condition of the soil are

known, the land can be used to construct roads,

parking lots, and embankments, among other things.

Because if the land does not meet geotechnical

requirements, it cannot be used; however, if

circumstances require the use of local soil, certain

chemicals or other substances are added to it and

mixed with the soil to increase soil stability.

Figure 6 depicts a condition that is distinct from

that depicted in Figure 6. The figure indicates that

the soil sample contains the Atterberg Limit LL, PL,

and OMC values that are positively correlated with

the content of CBR values. This means that

increasing the value of the Atterberg Limits LL, PL,

and W Opt can result in an increase in the density of

the soil and its CBR value.

Fig. 8: Test Pit Data (Bengkulu - Pugung Tampak)

The overall map of soil sample characteristics in the

Bengkulu - Pugung Tampak area is shown in Figure

8. Whereas, in general, soil samples are classified

into three groups based on their physical

characteristics and CBR value, with each group

sharing some physical characteristics and CBR

value similarities. Percent Lose filter 200 and the

Atterberg Limit LL are two soil physical properties

that have a high content value and diversity. The

contents of W and W Opt have a very strong

positive correlation with the contents of the

Atterberg Limits LL, PL, and PI. This means that

increasing the W and W Opt content in a soil sample

increases the Atterberg Limit LL, PL, and PI

contents, whereas the CBR value has a negative

correlation with the Atterberg Limit LL, PL, PI, W,

and W Opt contents. This means that as the CBR

value in the soil sample increases, the Atterberg

Limit values LL, PL, PI, W, and W Opt decrease.

Because the MDD content of each soil sample is

relatively low, it can be seen that the conditions

around the centre value of 0 are relatively stable.

Fig. 9: Relationship between % Pass through Filter

and CBR

Fig. 10: Test Pit Bi-plot Data (Bukit Kemuning -

Pugung Tampak)

The overall mapping of soil sample

characteristics in the Bukit Kemuning – Pugung

Tampak area is shown in Figure 9. As illustrated in

Figure 8, soil samples are classified into three

groups based on their physical properties and CBR

value, with each group having some similarities in

terms of physical properties and CBR value. Percent

Lose Filter No. 200 describes the physical properties

of soils with a high content value and a high degree

of diversity (long line in Figure 10). The value of W

and the W Opt contents are highly correlated with

the Atterberg Limit LL, PL, and PI contents. This

means that the greater the amount of W and W Opt

in the soil sample, the greater the amount of the

Atterberg Limit LL, PL, and PI. Meanwhile, the

CBR value is inversely proportional to the content

of the Atterberg Limit LL, PL, PI, W, and W Opt.

This means that the greater the CBR value in a soil

sample, the lower the Atterberg Limit values for LL,

PL, PI, W, and W Opt. The MDD content of each

soil sample is relatively low; it is shown to be close

to the centre value of 0, indicating that the MDD

value has not varied significantly.

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Fig. 11: Data Plotting of Water Content Values

Distribution

4 Conclusion

It is extremely precise in the Bi-plot programme,

which was used to determine the similarity of land

locations. The similarities and differences revealed

by the analysis serve as a guide for civil engineering

in terms of determining the source point of soil

material suitable for use as a landfill in civil

engineering construction. The data used in the CBR

test were the results of physical property testing and

soil sample testing. This parameter was chosen

using a sample of 31 samples spread over a distance

of 31 kilometres. The test results indicate that a 31-

kilometre distance does not result in a significant

difference in soil properties, which are generally

similar except for areas with high clay content.

Additionally, the laboratory analysis results indicate

that the amount of water in the soil sample has an

effect on the LL, PL, MDD, and CBR values. The

less water in the soil, the lower the plastic limit

value, and thus the lower the CBR value.

The findings of the current study also have

implications. It is widely known that the

government or contractors must use local land in

order to find better land. Apart from being more

cost-effective and quicker to obtain, it saves time at

work. Therefore, the findings of this study are

extremely useful in determining the location of

existing land. In addition, they can be used to map

conditions associated with specific soil types or

differences within an area. Therefore, if the

government, contractors, or consultants intend to

utilise the land surrounding the study site, it is

critical that this data be utilised because typically,

before soil is used as a landfill, it is tested in a soil

mechanics laboratory to determine its physical

properties. If the requirements for roads and other

earthworks do not comply with those of the

Directorate General of Highways (DGH), the land

cannot be used as a landfill or for any other purpose.

References:

[1] J. A. Baldock and J. O. Skjemstad, “Role of

the soil matrix and minerals in protecting

natural organic materials against biological

attack,” Org. Geochem., vol. 31, no. 7–8, pp.

697–710, 2000.

[2] J. K. Mitchell, K. Soga, and others,

Fundamentals of soil behavior, vol. 3. John

Wiley \& Sons New York, 2005.

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Ryzal Perdana, Rina Febrina, Yan Juansyah

E-ISSN: 2224-3496

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Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

Lusmeilia Afriani drafted the manuscript, collected

data, and conducted the analysis. Nusyirwan and

Ryzal Perdana conducted the literature review,

drafted the general conclusions, edited the language,

and were responsible for the paper's formatting and

revision. Rina Febrina and Yan Juansyah enhanced

the study's structure, clarified the analysis,

completed the paper's finalisation, and developed

the abstract.

Sources of Funding for Research Presented

in a Scientific Article or Scientific Article

Itself

We would like to express our gratitude to the

Faculty of Engineering of the University of

Lampung for facilitating and assisting with the field

survey and data collection, as well as providing

financial support.

Creative Commons Attribution License 4.0

(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

https://creativecommons.org/licenses/by/4.0/deed.en

_US

WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT

DOI: 10.37394/232015.2022.18.10

Lusmeilia Afriani, Nursyirwan,

Ryzal Perdana, Rina Febrina, Yan Juansyah

E-ISSN: 2224-3496

Volume 18, 2022