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IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE)
e-ISSN: 2278-1684,p-ISSN: 2320-334X, Volume 12, Issue 6 Ver. V (Nov. - Dec. 2015), PP 89-97
www.iosrjournals.org
DOI: 10.9790/1684-12658997 www.iosrjournals.org 89 | Page
The Relationship between the Factors That Cause Road
Damage and Its Effect on Road Damage In the City Of
Palangka Raya
Fatma Sarie1
, Mohammad Bisri2
, Achmad Wicaksono2
,Rustam Effendi3
1
Doctoral Program of Environmental Studies, Graduate School, University of Brawijaya
2
Faculty of Engineering, University of Brawijaya
3
Faculty of Engineering, Lambung Mangkurat University
Abstract: The road pavement failure effect much problems for the city such traffic accident, side
effect of transportation, more failure if the problems did not solve effectively. There are several
factors that cause the road failure such as water, traffic problems, climate, the material of road
pavement, subgrade condition, and the process of compaction. The environmental factors like as
climate also effect the road pavement failure. The aims of this research is to analyze the
relationship among the cause factors that effectthe road pavement failure especially for road on
peatland.The research site is Palangka Raya City, Central Kalimantan Province, Indonesia.
The result showed that there is significant relationship between the factors that cause road
damage and its effect on road damage in the city of Palangka Raya for road on peatland This
relationship refer to this equation is Y= -2.78335 + 0.358X1 + 0.549X2 + 0.635X3 + 0,.675X4 +
1.142 X5 + 0.709 X6 where Y is the road pavement failure for road on peatland and X are the
factors which effected the road pavement failure. If the value of X increase so the value of Y is
bigger than before.
Keywords: peatland, infiltration, climate, fibrous peat.
I. Introduction
Palangka Raya City is the capital of Central Kalimantan Province. It is one of the province in
Kalimantan Island, Indonesia. The road in this city has 607,741 km2 length (Department of Public Works City
of Palangka Raya, 2010) . Several road is built on peatland because the route of the traffic of passenger and
goods must followed the locations. The conditions are good and very good about 49.7%and the road conditions
are poor and very poor about 50.3%.
Several factors can cause the road damages. According to Sukirman (1995) the factor that cause the
damages are water, the traffic, climate, the material of road construction, subgrade condition and the process of
compaction. The visual observation showed that the road damages has a relationship with the cause factors.
Based on preliminary studies it is known that the land base at the study site is peat soil. Peat is a type of
soft soil with high content of fibrous organic matters and can be defines as an accumulation of 100% pure
organic material contains less than 35% mineral or at least 65% organic content. (Muhamad et al, 2010). The
content of peat is different based on the location of study (Huat, 2004) depend on temperature, climate and
humidity also the origin fibre. Peat has its unique characteristic make it pose its own distinctive properties
different with the inorganic soils that made up by the soils particles (Deboucha et al, 2008).
Deposits of peat are found when the conditions are favorable for their accumulation and formation
(Asadi et al, 2009). Huat (2004) stated that peat deposits is distributed extensively at many countries of the
world. The peatland covers about 5 to 8% of the land of earth surface and covers about 60% of the wetlands.
The amount of tropical peatland is about 30 millions hectares and two third of 30 millions hectares are in South
East Asia. The amount of peat in Indonesia is about 26 million hectares, in Japan is about 2,000km2, in
Malaysia is approximately 3 millions hectares contained of 6,300 hectares is in Pontian, Batu Pahat and Muar in
West Johore (Yulindasari, 2006) and 1.66 million hectares in Sarawak (Said and Taib, 2009). Peat can be found
in Canada, Russia and in US, the total of peat is 30 million hectares (Mesri and Aljouni, 2007).
Peat can be slassified based on several criteria. One of the classification is based on their ash and
organic content (ASTM, 1990). Tropical peat like as in Peninsular Malaysia has the ash content is about 3.55
and organic content is about 96.45%,. It means that the peat is very high of organic matter and the lose of
ignition value about 90% (Islam and Hashim, 2008a,b). The texture of peat is dependent of the type of peat.
The fibrous peat is coarse and clay is smooth related to the particle size and behavior of compressibility (Gofar,
2006). Generally, peat is high water content because of peat has low bulk density and bearing capacity due to its
The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In
DOI: 10.9790/1684-12658997 www.iosrjournals.org 90 | Page
high buoyancy and pore volume. According to Aljouni (2000), Aljouni and Mesri (2009) peat has the water
content about 200 to 2000% and In West Malaysia, Huat (2004) stated that the water content about 200-700%.
The unit weight of fibrous peat in Peninsular Malaysia is about 8.3 to 11.5 kN/m3
(Huat, 2004). The unit weight
of this soil affected by its water content that if the water content increase so the unit weight decrease such as if
water content about 500% so the unit weight is about 10 to 13 kN/m3 (Kazemian et al, 2009a). Peat also has the
coefficient of permeability that expressed the velocity and Darcy’s law to determine the flow of water through
fibrous peat (Wong, 2005;Wong et al, 2008). At a given void ratio, the vertical coefficient of permeability is
lower than the horizontal coefficient of permeability that indicates the horizontal coefficient of consolidation of
peat is greater than the vertical coefficient of consolidation (Gofar, 2006). The acidity is one of chemical
characteristic of peat that usually tested in several studies. The acidity of peat is decreasing with depth and the
decrease may be large near the bottom layer depend on the kind of underlying soil (Aljouni, 2000;Kazemian et
al, 2009a,b,c,d,e; Kazemian et al, 2010 a,b). Generally, pH of peat is about 4 to 7 and the peat have hugh cation
exchange capacity (CEC). The CEC of fibrous peat is larger than amorphous peat (Moayedi et al, 2011a,b).
The aim of this research is to analyze the relationship between the dependent variable (road pavement
failure) and the independent variable (the factors that cause the road damages/failure) for road on peatland.
II. Study Method
Study Site
The research site is Palangka Raya City, Central Kalimantan Province Indonesia. It was
done at September-October 2015.
Figure 1.1 Map of Palangka Raya(Department Of Civil Work, 2010)
The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In
DOI: 10.9790/1684-12658997 www.iosrjournals.org 91 | Page
Figure 1.2 Map of Road in Palangka Raya City (Department Of Civil Work, 2010)
Study Approach
This study used the explanatory research method to explain the causal relationship between the road
pavement failure and the cause factors.
.
Population and Sample
Population
In this research the population is the expert of road project or everyone that has knowledge and
experience in road engineering in Central Kalimantan.
Sample
According to Widayat (2004) the sample of research is about 30 to 500. So the sample is determined
about 121 persons. The collecting sample technique used accidental sampling.
The method of collecting data are questionnaire, interview and documentation.
Operational Definition of Variable and The Measurement of the Variable
Operational Definition of Variable
The variables in this research are dependent and independent variables. The dependent Variable (Y) is
the road pavement failure and the independent variables (X) are X1, X2, X3, X4, X5, X6. The indicators for Y are
cracks, distorsion, disintegration, polished aggregates, bleeding or flushing, utility cut depression. The indicators
for X1 (Infiltration of rainwater, drainage system is not good, water rising due to the nature of capillarity ), X2
(increase in load, repeated load), X3 (an increase in air temperature, high rainfall- water flooded the road),
X4(material quality standards that are less well, material processing system that is not good), X5(basic soil
properties is not good, system implementation is not good), X6(soil compaction process that is not well.
The Measurement of variable
The questions or statement in the questionnaire is the closed question with 5 options of the answers such
as very significant, significant, enough significant, not significant, very insignificant. Likert scale is used to
measure the variable, the scale are 5 (very significant), 4 (significant), 3 (enough significant), 2 (not significant),
1 (very insignificant).
III. Methode of Data Analysis
Validity and Reliability Test
The data that collecting from questionnaires is the primary data that must be processed and analyzed
using The Program SPSS for windows.
Validity Test
This test used SPSS Program for Windows based on Analysis of Product Moment that count the
correlation coefficient among the score items with the total score.
The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In
DOI: 10.9790/1684-12658997 www.iosrjournals.org 92 | Page
 
    2222
. yynxxn
yxyn
r



(Sudjana, 2010) ………(1.1)
where:
r = correlation coefficient among the items with the total score
x = score of the answer for each item
y = total score
n = amount of sample
Reliability Test
Testing reliability of the instrument in this study is done by comparing the Cronbach Alpha coefficients
were calculated using the computer program SPSS for Windows. Alpha formula to determine the reliability
of the instrument are: 




 


 2
1
2
11 1
1 
b
k
k
r
(Sudjana, 2010)……………………………(1.2)
where r11 = Instrument of Reliability
k = the number of questions
b2
= the number of varians
12
= Total varians
Multiple Regression Analysis
The analysis of the effect among two independent variables or more against the dependent variable
can be used the Multiple Regression Analysis. The equation is:
Y= a + b1X1 + b2X2+…….. + bnXn (Sugiyono, 2012) ………………….(1.3)
where:
Y = The dependent variable
X = The independent variable
a = constanta Of regression
b = coefisient of regression
Data Analysis
Table 1.1 Frequency Distribution of Variable X1
Item
Very
Significant
Significant
Significant
Enough
Less
Significant
Very
Insignificant
Total
F % F % F % F % F % F %
X1.1 29 24,0 53 43,8 31 25,6 2 8,0 0 0.0 121 100
X1.2 32 26,4 48 39,7 33 27,3 8 6,6 0 0.0 121 100
X1.3 39 32,2 33 27,3 41 33,9 8 6,6 0 0.0 121 100
Source: Primary data processing (2015)
From the results of questionnaires known to respondents' opinions about the first item of the variable
Air (X1) which is about the infiltration of rainwater in mind as much as 53 respondents, or 43.8% expressed
significant, as many as 31 respondents, or 25.6% stated enough, as many as 29 respondents or 24% of the total
respondents stated very significant and as many as 8 respondents or 6.6% of the total respondents expressed
less. With a mean value of 3.85 indicates if the respondent according to the infiltration of rain water has a
significant effect on road pavement damage on peat.
For road drainage system is not good as much as 48 respondents, or 39.7% of the total respondents
stated significant, as many as 33 respondents, or 27.3% of the total respondents stated enough, as many as 32
respondents, or 26.4% of the total respondents expressed a very significant and as many as 8 or 6.6% of
respondents expressed less. With a mean value of 3.86 indicates if the road drainage system according to
respondents who either do not have a significant effect on road pavement damage on peat.
For items rising waters due to the nature of capillarity as many as 41 respondents, or 33.9% of the total
respondents stated enough, as many as 39 respondents, or 32.2% of the total respondents stated very significant,
as many as 33 respondents, or 27.3% of the total respondents expressed significant and as much as 8
respondents or 6.6% of the total respondents expressed less. With a mean value of 3.85 indicates if the
respondent by rising water due to capillarity properties have a significant effect on road pavement damage on
peat.
The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In
DOI: 10.9790/1684-12658997 www.iosrjournals.org 93 | Page
Table 1.2 Frequency Distribution of Variable X2
Item
Very
Significant
Significant
Significant
Enough
Less
Significant
Very
Insignificant
Total
F % F % F % F % F % F %
X2.1 27 22,3 45 37,2 38 31,4 11 9,1 0 0.0 121 100
X2.2 26 21,5 33 27,3 45 37,2 17 14,0 0 0.0 121 100
Source: Primary data processing (2015)
From the results of questionnaires known to respondents' opinions about the first item of the variable
Traffic (X2), namely the increase of load is known by 45 respondents or 37.2% expressed significant, as many as
38 respondents, or 31.4% stated enough, as many as 27 respondents, or 22.3% of the total respondents stated
very significant and as many as 11 respondents or 9.1% of the total respondents expressed less. With a mean
value of 3.73 indicates if the load increases according to respondents have a significant effect on road pavement
damage on peat.
To reps load on the road as much as 45 respondents, or 37.2% of the total respondents stated enough,
as many as 33 respondents, or 27.3% of the total respondents stated significant, as many as 26 respondents, or
21.5% of the total respondents stated very significant and as many as 17 or 14.0% of respondents expressed less.
With a mean value of 3.56 indicates if the respondent according to the reps have a significant effect on road
pavement damage on peat.
Table 1.3 Distribusi Frekuensi Variabel X3
Item
Very
Significant
Significant
Significant
Enough
Less
Significant
Very
Insignificant
Total
F % F % F % F % F % F %
X3.1 48 39,7 39 32,2 30 24,8 4 3,3 0 0.0 121 100
X3.2 41 33,9 46 38,0 23 19,0 11 9,1 0 0.0 121 100
Source: Primary data processing (2015)
From the results of questionnaires known to respondents' opinions about the first item of the variable
climate (X3) that the air temperature increases (heat) is known as much as 48 respondents, or 39.7% stated very
significant, as many as 39 respondents, or 32.2% expressed significant, as many as 30 respondents, or 24.8% of
the total respondents stated enough and as much as 4 respondents or 3.3% of the total respondents expressed
less. With a mean value of 4.08 indicates if the respondent according to the air temperature increases (hot) has a
significant effect on road pavement damage on peat.
For high rainfall (water flooded the street) as many as 46 respondents, or 38.0% of the total
respondents stated significant, as many as 41 respondents, or 33.9% of the total respondents stated very
significant, as many as 23 respondents, or 19.0% of total respondents stated enough and as many as 11
respondents or 9.1% said less. With a mean value of 3.97 indicates if the respondent according to the high
rainfall (water flooded the road) has a significant effect on road pavement damage on peat.
Table 1.4 Distribusi Frekuensi Variabel X4
Item
Very
Significant
Significant
Significant
Enough
Less
Significant
Very
Insignificant
Total
F % F % F % F % F % F %
X4.1 12 9,9 61 50,4 42 34,7 6 5,0 0 0.0 121 100
X4.2 17 14,0 45 37,2 55 45,5 4 3,3 0 0.0 121 100
Source: Primary data processing (2015)
From the results of questionnaires known to respondents' opinions about the first item of variables
Construction Materials Pavement (X4), namely the quality standard of materials that are less well known as
many as 61 respondents or 50.74 declared significant, as many as 42 respondents, or 34.7% stated enough, as
many as 12 respondents or 9.9% of the total respondents stated very significant and as much as 6 respondents or
5.0% of the total respondents expressed less. With a mean value of 3.65 indicates if the respondent according to
quality standards that are less good material has a significant effect on road pavement damage on peat.
For material processing system that is not good by 55 respondents, or 45.5% of the total respondents
stated enough, as many as 45 respondents, or 37.2% of the total respondents stated significant, as many as 17
respondents, or 14.0% of the total respondents stated enough and as much 4 respondents or 3.3% said less. With
The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In
DOI: 10.9790/1684-12658997 www.iosrjournals.org 94 | Page
a mean value of 3.62 indicates if the material processing system according to respondents who either do not
have a significant effect on road pavement damage on peat.
Table 1.5 Distribusi Frekuensi Variabel X5
Item
Very
Significant
Significant
Significant
Enough
Less
Significant
Very
Insignificant
Total
F % F % F % F % F % F %
X5.1 11 9,1 55 45,5 45 37,2 10 8,3 0 0.0 121 100
X5.2 6 5,0 63 52,1 49 40,5 3 2,5 0 0.0 121 100
Source: Primary data processing (2015)
From the results of questionnaires known to respondents' opinions about the first item of the variable
Land Condition Basic (X5) is about the nature of the land base that is not well known by 55 respondents or
45.5% expressed significant, as many as 45 respondents, or 37.2% stated enough, as many as 11 respondents or
9.1 % of the total respondents stated very significant and as many as 10 respondents or 8.3% of the total
respondents expressed less. With a mean value of 4.55 indicates if the respondent according to the basic soil
properties is not good to have a significant effect on road pavement damage on peat.
For the implementation of the system is not good as much as 46 respondents, or 38.0% of the total
respondents stated significant, as many as 63 respondents, or 52.1% of the total respondents stated significant,
as many as 49 respondents, or 40.5% of the total respondents stated enough and as much as 6 or 5.0% of
respondents expressed a very significant and as high as 3 respondents or 2.5% of the total respondents expressed
less. With a mean value of 3.60 indicates if the implementation of the system according to the respondents who
either do not have a significant effect on road pavement damage on peat.
From the results of questionnaires known to respondents' opinions about the variables Process
Compaction (X6) is the process of soil compaction that is not well known as many as 40 respondents, or 33.1%
stated enough, as many as 36 respondents, or 29.8% expressed significant, as many as 25 respondents, or 20.7%
of the total respondents stated very significant and as many as 20 respondents, or 16.5% of the total respondents
expressed less. With a mean value of 3.55 indicates if the soil compaction process according to respondents who
either do not have a significant effect on road pavement damage on peat.
IV. Result Of Validity Test
Table 1.6 Validity Testing Results (X1)
Item
The value of
r
r table Sig Description
X1.1 0,841 0,176 0,000 Valid
X1.2 0,753 0,176 0,000 Valid
X1.3 0,765 0,176 0,000 Valid
X2.1 0,852 0,176 0,000 Valid
X2.2 0,873 0,176 0,000 Valid
X3.1 0,850 0,176 0,000 Valid
X3.2 0,872 0,176 0,000 Valid
X4.1 0,804 0,176 0,000 Valid
X4.2 0,826 0,176 0,000 Valid
X5.1 0,879 0,176 0,000 Valid
X5.2 0,809 0,176 0,000 Valid
Y1 0,828 0,176 0,000 Valid
Y2 0,784 0,176 0,000 Valid
Y3 0,821 0,176 0,000 Valid
Y4 0,818 0,176 0,007 Valid
Y5 0,787 0,176 0,000 Valid
Y6 0,826 0,176 0,000 Valid
Source: Primary data processing (2015)
Based on this test the result is every variables can be used for the research because they are valid.
Table 1.7 Result of Realibilty Test
No. Variable Alpha Cronbach Description
1. X1 0,820 Reliable
2. X2 0,873 Reliable
3. X3 0,872 Reliable
4. X4 0,843 Reliable
5. X5 0,861 Reliable
6. Y 0,801 Reliable
Source: Primary data processing (2015)
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DOI: 10.9790/1684-12658997 www.iosrjournals.org 95 | Page
According to calculation can be conclude that the instrument of research is reliable.
V. Result of Classical Assumption Test
a. The Result of Heteroskedastisitas Test
Scatter Plot of Heteroskedastisitas Test
Figure 1.3 Scatter Plot of Heteroskedastisitas Test
Based on the graphic that there is not an heteroskedastisitas to regression model.
b. Test results Multicolinearity
Table 1.8 The Result of Multicolinearity Assumption Test
Independent Variable VIF Description
X1 1.539 Non Multikolinear
X2 1.282 Non Multikolinear
X3 1.236 Non Multikolinear
X4 1.286 Non Multikolinear
X5 1.688 Non Multikolinear
X6 1.781 Non Multikolinear
Source: Primary data processing (2015)
Based on the calculation show that every variables has the value of VHF no more than 10.
c. Result of Normality Test
The graphic of P-P Plot is shown in Figure 1.4
Figure 1.4 Normal P-P Plot of Regression Standardized Residual
The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In
DOI: 10.9790/1684-12658997 www.iosrjournals.org 96 | Page
The standardized residual value make a linear pattern that indicate the residual value has normal
distribution.
Result of Analysis
Table 1.9 Result of Multiple Regression Analysis
No Variable Coefficient of
Regression
t-count Sig
1. X1 0.358 2.494 0.014
2. X2 0.549 3.219 0.002
3. X3 0.635 3.652 0.000
4. X4 0.675 2.944 0.004
5. X5 1.142 4.241 0.000
6. X6 0.709 2.157 0.033
Source: Primary data processing (2015)
constanta = -5.480
R = 0.819
R Square = 0.670
Fcount = 38.658
Sig = 0.000
1. The coefficient of correlation (R) show the level of the relationship among the independent variables (X)
simultaneously against the dependent variable (Y).. Value of R which is obtained from the analysis is 0.819
showed that the variables X (X1,X2, X3, X4 dan X5) ssimultaneously have a very strong relationship with Y.
Table 1.10 Interpretation of Correlation Coefficient (r)
Interval Coefficient Relationship Level (Interpretation)
0,00-0,199 Very low
0,20-0,399 Low
0,40-0,599 Enough
0,60-0,799 Strong
0,80-1,00 Very Strong
2. The value of R Square shows the contribution (contribution) independent variables were examined
simultaneously on the dependent variable. The results of analysis R square value of 0.670 indicates if the
independent variables (X1, X2, X3, X4, X5 and X6) simultaneously affect the dependent variable (Y) of
67.0% for the remaining 33.0% is influenced by other variables not examined in this study.
3. F Test
F count indicates whether all independent variables (X) studied simultaneously have a significant influence
on the dependent variable (Y).
4. t test
From t test can conclude that all independent variables has the significant effect to dependent variable (Y).
Regression Equation :
Y = -5.480 + 0.358 X1 + 0.549 X2 + 0.635 X3 + 0.675 X4 + 1.142 X5 + 0.709 X6
The explanation of the equation are:
a. Constanta about -5.480 show that if no effect of the independent variables so the dependent variable has
the constant value about -5.480.
b. Coefisient of regression X1 (b1) about 0.358 show that there is an positive effect between variable X1
against the variable Y, it mean that the higher the value of X1, the higher the value of Y.
c. Coefisient of regression X2 (b2) about 0.549 show that there is an positive effect between variable X2
against the variable Y, it mean that the higher the value of X2, the higher the value of Y.
d. Coefisient of regression X3 (b3) 0.635 show that there is an positive effect between variable X3 against
the variable Y, it mean that the higher the value of X3, the higher the value of Y.
e. Coefisient of regression X4 (b4) 0.675 show that there is an positive effect between variable X4 against
the variable Y, it mean that the higher the value of X4, the higher the value of Y.
f. Coeffisient of regression X5 (b5) 1.142 show that there is an positive effect between variable X5 against
the variable Y, it mean that the higher the value of X5, the higher the value of Y.
g. Coeffisient of regression X6 (b6) 0.709 show that there is an positive effect between variable X6 against
the variable Y, it mean that the higher the value of X6, the higher the value of Y.
The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In
DOI: 10.9790/1684-12658997 www.iosrjournals.org 97 | Page
VI. Conclusion
There is a significant relationship among the factor that cause the road pavement failure
following the equation: Y = -5.480 + 0.358 X1 + 0.549 X2 + 0.635 X3 + 0.675 X4 + 1.142 X5 + 0.709 X6
.
Coeffisient of regression X5 (b5) 1.142 is greater than others it means that soil condition of peatland has more
effect to road pavement damage.
Suggestion
It is important to know well the key of suitable maintenance for the road on peatland based
on the the cause of failure to prevent more failure in the road pavement. Beside that it need a
comprehensive design of the road refer to the cause of failure to anticipate the failure or damage of
the road on peatland in Palangka Raya City.
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Malaysia

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K012658997

  • 1. IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) e-ISSN: 2278-1684,p-ISSN: 2320-334X, Volume 12, Issue 6 Ver. V (Nov. - Dec. 2015), PP 89-97 www.iosrjournals.org DOI: 10.9790/1684-12658997 www.iosrjournals.org 89 | Page The Relationship between the Factors That Cause Road Damage and Its Effect on Road Damage In the City Of Palangka Raya Fatma Sarie1 , Mohammad Bisri2 , Achmad Wicaksono2 ,Rustam Effendi3 1 Doctoral Program of Environmental Studies, Graduate School, University of Brawijaya 2 Faculty of Engineering, University of Brawijaya 3 Faculty of Engineering, Lambung Mangkurat University Abstract: The road pavement failure effect much problems for the city such traffic accident, side effect of transportation, more failure if the problems did not solve effectively. There are several factors that cause the road failure such as water, traffic problems, climate, the material of road pavement, subgrade condition, and the process of compaction. The environmental factors like as climate also effect the road pavement failure. The aims of this research is to analyze the relationship among the cause factors that effectthe road pavement failure especially for road on peatland.The research site is Palangka Raya City, Central Kalimantan Province, Indonesia. The result showed that there is significant relationship between the factors that cause road damage and its effect on road damage in the city of Palangka Raya for road on peatland This relationship refer to this equation is Y= -2.78335 + 0.358X1 + 0.549X2 + 0.635X3 + 0,.675X4 + 1.142 X5 + 0.709 X6 where Y is the road pavement failure for road on peatland and X are the factors which effected the road pavement failure. If the value of X increase so the value of Y is bigger than before. Keywords: peatland, infiltration, climate, fibrous peat. I. Introduction Palangka Raya City is the capital of Central Kalimantan Province. It is one of the province in Kalimantan Island, Indonesia. The road in this city has 607,741 km2 length (Department of Public Works City of Palangka Raya, 2010) . Several road is built on peatland because the route of the traffic of passenger and goods must followed the locations. The conditions are good and very good about 49.7%and the road conditions are poor and very poor about 50.3%. Several factors can cause the road damages. According to Sukirman (1995) the factor that cause the damages are water, the traffic, climate, the material of road construction, subgrade condition and the process of compaction. The visual observation showed that the road damages has a relationship with the cause factors. Based on preliminary studies it is known that the land base at the study site is peat soil. Peat is a type of soft soil with high content of fibrous organic matters and can be defines as an accumulation of 100% pure organic material contains less than 35% mineral or at least 65% organic content. (Muhamad et al, 2010). The content of peat is different based on the location of study (Huat, 2004) depend on temperature, climate and humidity also the origin fibre. Peat has its unique characteristic make it pose its own distinctive properties different with the inorganic soils that made up by the soils particles (Deboucha et al, 2008). Deposits of peat are found when the conditions are favorable for their accumulation and formation (Asadi et al, 2009). Huat (2004) stated that peat deposits is distributed extensively at many countries of the world. The peatland covers about 5 to 8% of the land of earth surface and covers about 60% of the wetlands. The amount of tropical peatland is about 30 millions hectares and two third of 30 millions hectares are in South East Asia. The amount of peat in Indonesia is about 26 million hectares, in Japan is about 2,000km2, in Malaysia is approximately 3 millions hectares contained of 6,300 hectares is in Pontian, Batu Pahat and Muar in West Johore (Yulindasari, 2006) and 1.66 million hectares in Sarawak (Said and Taib, 2009). Peat can be found in Canada, Russia and in US, the total of peat is 30 million hectares (Mesri and Aljouni, 2007). Peat can be slassified based on several criteria. One of the classification is based on their ash and organic content (ASTM, 1990). Tropical peat like as in Peninsular Malaysia has the ash content is about 3.55 and organic content is about 96.45%,. It means that the peat is very high of organic matter and the lose of ignition value about 90% (Islam and Hashim, 2008a,b). The texture of peat is dependent of the type of peat. The fibrous peat is coarse and clay is smooth related to the particle size and behavior of compressibility (Gofar, 2006). Generally, peat is high water content because of peat has low bulk density and bearing capacity due to its
  • 2. The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In DOI: 10.9790/1684-12658997 www.iosrjournals.org 90 | Page high buoyancy and pore volume. According to Aljouni (2000), Aljouni and Mesri (2009) peat has the water content about 200 to 2000% and In West Malaysia, Huat (2004) stated that the water content about 200-700%. The unit weight of fibrous peat in Peninsular Malaysia is about 8.3 to 11.5 kN/m3 (Huat, 2004). The unit weight of this soil affected by its water content that if the water content increase so the unit weight decrease such as if water content about 500% so the unit weight is about 10 to 13 kN/m3 (Kazemian et al, 2009a). Peat also has the coefficient of permeability that expressed the velocity and Darcy’s law to determine the flow of water through fibrous peat (Wong, 2005;Wong et al, 2008). At a given void ratio, the vertical coefficient of permeability is lower than the horizontal coefficient of permeability that indicates the horizontal coefficient of consolidation of peat is greater than the vertical coefficient of consolidation (Gofar, 2006). The acidity is one of chemical characteristic of peat that usually tested in several studies. The acidity of peat is decreasing with depth and the decrease may be large near the bottom layer depend on the kind of underlying soil (Aljouni, 2000;Kazemian et al, 2009a,b,c,d,e; Kazemian et al, 2010 a,b). Generally, pH of peat is about 4 to 7 and the peat have hugh cation exchange capacity (CEC). The CEC of fibrous peat is larger than amorphous peat (Moayedi et al, 2011a,b). The aim of this research is to analyze the relationship between the dependent variable (road pavement failure) and the independent variable (the factors that cause the road damages/failure) for road on peatland. II. Study Method Study Site The research site is Palangka Raya City, Central Kalimantan Province Indonesia. It was done at September-October 2015. Figure 1.1 Map of Palangka Raya(Department Of Civil Work, 2010)
  • 3. The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In DOI: 10.9790/1684-12658997 www.iosrjournals.org 91 | Page Figure 1.2 Map of Road in Palangka Raya City (Department Of Civil Work, 2010) Study Approach This study used the explanatory research method to explain the causal relationship between the road pavement failure and the cause factors. . Population and Sample Population In this research the population is the expert of road project or everyone that has knowledge and experience in road engineering in Central Kalimantan. Sample According to Widayat (2004) the sample of research is about 30 to 500. So the sample is determined about 121 persons. The collecting sample technique used accidental sampling. The method of collecting data are questionnaire, interview and documentation. Operational Definition of Variable and The Measurement of the Variable Operational Definition of Variable The variables in this research are dependent and independent variables. The dependent Variable (Y) is the road pavement failure and the independent variables (X) are X1, X2, X3, X4, X5, X6. The indicators for Y are cracks, distorsion, disintegration, polished aggregates, bleeding or flushing, utility cut depression. The indicators for X1 (Infiltration of rainwater, drainage system is not good, water rising due to the nature of capillarity ), X2 (increase in load, repeated load), X3 (an increase in air temperature, high rainfall- water flooded the road), X4(material quality standards that are less well, material processing system that is not good), X5(basic soil properties is not good, system implementation is not good), X6(soil compaction process that is not well. The Measurement of variable The questions or statement in the questionnaire is the closed question with 5 options of the answers such as very significant, significant, enough significant, not significant, very insignificant. Likert scale is used to measure the variable, the scale are 5 (very significant), 4 (significant), 3 (enough significant), 2 (not significant), 1 (very insignificant). III. Methode of Data Analysis Validity and Reliability Test The data that collecting from questionnaires is the primary data that must be processed and analyzed using The Program SPSS for windows. Validity Test This test used SPSS Program for Windows based on Analysis of Product Moment that count the correlation coefficient among the score items with the total score.
  • 4. The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In DOI: 10.9790/1684-12658997 www.iosrjournals.org 92 | Page       2222 . yynxxn yxyn r    (Sudjana, 2010) ………(1.1) where: r = correlation coefficient among the items with the total score x = score of the answer for each item y = total score n = amount of sample Reliability Test Testing reliability of the instrument in this study is done by comparing the Cronbach Alpha coefficients were calculated using the computer program SPSS for Windows. Alpha formula to determine the reliability of the instrument are:           2 1 2 11 1 1  b k k r (Sudjana, 2010)……………………………(1.2) where r11 = Instrument of Reliability k = the number of questions b2 = the number of varians 12 = Total varians Multiple Regression Analysis The analysis of the effect among two independent variables or more against the dependent variable can be used the Multiple Regression Analysis. The equation is: Y= a + b1X1 + b2X2+…….. + bnXn (Sugiyono, 2012) ………………….(1.3) where: Y = The dependent variable X = The independent variable a = constanta Of regression b = coefisient of regression Data Analysis Table 1.1 Frequency Distribution of Variable X1 Item Very Significant Significant Significant Enough Less Significant Very Insignificant Total F % F % F % F % F % F % X1.1 29 24,0 53 43,8 31 25,6 2 8,0 0 0.0 121 100 X1.2 32 26,4 48 39,7 33 27,3 8 6,6 0 0.0 121 100 X1.3 39 32,2 33 27,3 41 33,9 8 6,6 0 0.0 121 100 Source: Primary data processing (2015) From the results of questionnaires known to respondents' opinions about the first item of the variable Air (X1) which is about the infiltration of rainwater in mind as much as 53 respondents, or 43.8% expressed significant, as many as 31 respondents, or 25.6% stated enough, as many as 29 respondents or 24% of the total respondents stated very significant and as many as 8 respondents or 6.6% of the total respondents expressed less. With a mean value of 3.85 indicates if the respondent according to the infiltration of rain water has a significant effect on road pavement damage on peat. For road drainage system is not good as much as 48 respondents, or 39.7% of the total respondents stated significant, as many as 33 respondents, or 27.3% of the total respondents stated enough, as many as 32 respondents, or 26.4% of the total respondents expressed a very significant and as many as 8 or 6.6% of respondents expressed less. With a mean value of 3.86 indicates if the road drainage system according to respondents who either do not have a significant effect on road pavement damage on peat. For items rising waters due to the nature of capillarity as many as 41 respondents, or 33.9% of the total respondents stated enough, as many as 39 respondents, or 32.2% of the total respondents stated very significant, as many as 33 respondents, or 27.3% of the total respondents expressed significant and as much as 8 respondents or 6.6% of the total respondents expressed less. With a mean value of 3.85 indicates if the respondent by rising water due to capillarity properties have a significant effect on road pavement damage on peat.
  • 5. The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In DOI: 10.9790/1684-12658997 www.iosrjournals.org 93 | Page Table 1.2 Frequency Distribution of Variable X2 Item Very Significant Significant Significant Enough Less Significant Very Insignificant Total F % F % F % F % F % F % X2.1 27 22,3 45 37,2 38 31,4 11 9,1 0 0.0 121 100 X2.2 26 21,5 33 27,3 45 37,2 17 14,0 0 0.0 121 100 Source: Primary data processing (2015) From the results of questionnaires known to respondents' opinions about the first item of the variable Traffic (X2), namely the increase of load is known by 45 respondents or 37.2% expressed significant, as many as 38 respondents, or 31.4% stated enough, as many as 27 respondents, or 22.3% of the total respondents stated very significant and as many as 11 respondents or 9.1% of the total respondents expressed less. With a mean value of 3.73 indicates if the load increases according to respondents have a significant effect on road pavement damage on peat. To reps load on the road as much as 45 respondents, or 37.2% of the total respondents stated enough, as many as 33 respondents, or 27.3% of the total respondents stated significant, as many as 26 respondents, or 21.5% of the total respondents stated very significant and as many as 17 or 14.0% of respondents expressed less. With a mean value of 3.56 indicates if the respondent according to the reps have a significant effect on road pavement damage on peat. Table 1.3 Distribusi Frekuensi Variabel X3 Item Very Significant Significant Significant Enough Less Significant Very Insignificant Total F % F % F % F % F % F % X3.1 48 39,7 39 32,2 30 24,8 4 3,3 0 0.0 121 100 X3.2 41 33,9 46 38,0 23 19,0 11 9,1 0 0.0 121 100 Source: Primary data processing (2015) From the results of questionnaires known to respondents' opinions about the first item of the variable climate (X3) that the air temperature increases (heat) is known as much as 48 respondents, or 39.7% stated very significant, as many as 39 respondents, or 32.2% expressed significant, as many as 30 respondents, or 24.8% of the total respondents stated enough and as much as 4 respondents or 3.3% of the total respondents expressed less. With a mean value of 4.08 indicates if the respondent according to the air temperature increases (hot) has a significant effect on road pavement damage on peat. For high rainfall (water flooded the street) as many as 46 respondents, or 38.0% of the total respondents stated significant, as many as 41 respondents, or 33.9% of the total respondents stated very significant, as many as 23 respondents, or 19.0% of total respondents stated enough and as many as 11 respondents or 9.1% said less. With a mean value of 3.97 indicates if the respondent according to the high rainfall (water flooded the road) has a significant effect on road pavement damage on peat. Table 1.4 Distribusi Frekuensi Variabel X4 Item Very Significant Significant Significant Enough Less Significant Very Insignificant Total F % F % F % F % F % F % X4.1 12 9,9 61 50,4 42 34,7 6 5,0 0 0.0 121 100 X4.2 17 14,0 45 37,2 55 45,5 4 3,3 0 0.0 121 100 Source: Primary data processing (2015) From the results of questionnaires known to respondents' opinions about the first item of variables Construction Materials Pavement (X4), namely the quality standard of materials that are less well known as many as 61 respondents or 50.74 declared significant, as many as 42 respondents, or 34.7% stated enough, as many as 12 respondents or 9.9% of the total respondents stated very significant and as much as 6 respondents or 5.0% of the total respondents expressed less. With a mean value of 3.65 indicates if the respondent according to quality standards that are less good material has a significant effect on road pavement damage on peat. For material processing system that is not good by 55 respondents, or 45.5% of the total respondents stated enough, as many as 45 respondents, or 37.2% of the total respondents stated significant, as many as 17 respondents, or 14.0% of the total respondents stated enough and as much 4 respondents or 3.3% said less. With
  • 6. The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In DOI: 10.9790/1684-12658997 www.iosrjournals.org 94 | Page a mean value of 3.62 indicates if the material processing system according to respondents who either do not have a significant effect on road pavement damage on peat. Table 1.5 Distribusi Frekuensi Variabel X5 Item Very Significant Significant Significant Enough Less Significant Very Insignificant Total F % F % F % F % F % F % X5.1 11 9,1 55 45,5 45 37,2 10 8,3 0 0.0 121 100 X5.2 6 5,0 63 52,1 49 40,5 3 2,5 0 0.0 121 100 Source: Primary data processing (2015) From the results of questionnaires known to respondents' opinions about the first item of the variable Land Condition Basic (X5) is about the nature of the land base that is not well known by 55 respondents or 45.5% expressed significant, as many as 45 respondents, or 37.2% stated enough, as many as 11 respondents or 9.1 % of the total respondents stated very significant and as many as 10 respondents or 8.3% of the total respondents expressed less. With a mean value of 4.55 indicates if the respondent according to the basic soil properties is not good to have a significant effect on road pavement damage on peat. For the implementation of the system is not good as much as 46 respondents, or 38.0% of the total respondents stated significant, as many as 63 respondents, or 52.1% of the total respondents stated significant, as many as 49 respondents, or 40.5% of the total respondents stated enough and as much as 6 or 5.0% of respondents expressed a very significant and as high as 3 respondents or 2.5% of the total respondents expressed less. With a mean value of 3.60 indicates if the implementation of the system according to the respondents who either do not have a significant effect on road pavement damage on peat. From the results of questionnaires known to respondents' opinions about the variables Process Compaction (X6) is the process of soil compaction that is not well known as many as 40 respondents, or 33.1% stated enough, as many as 36 respondents, or 29.8% expressed significant, as many as 25 respondents, or 20.7% of the total respondents stated very significant and as many as 20 respondents, or 16.5% of the total respondents expressed less. With a mean value of 3.55 indicates if the soil compaction process according to respondents who either do not have a significant effect on road pavement damage on peat. IV. Result Of Validity Test Table 1.6 Validity Testing Results (X1) Item The value of r r table Sig Description X1.1 0,841 0,176 0,000 Valid X1.2 0,753 0,176 0,000 Valid X1.3 0,765 0,176 0,000 Valid X2.1 0,852 0,176 0,000 Valid X2.2 0,873 0,176 0,000 Valid X3.1 0,850 0,176 0,000 Valid X3.2 0,872 0,176 0,000 Valid X4.1 0,804 0,176 0,000 Valid X4.2 0,826 0,176 0,000 Valid X5.1 0,879 0,176 0,000 Valid X5.2 0,809 0,176 0,000 Valid Y1 0,828 0,176 0,000 Valid Y2 0,784 0,176 0,000 Valid Y3 0,821 0,176 0,000 Valid Y4 0,818 0,176 0,007 Valid Y5 0,787 0,176 0,000 Valid Y6 0,826 0,176 0,000 Valid Source: Primary data processing (2015) Based on this test the result is every variables can be used for the research because they are valid. Table 1.7 Result of Realibilty Test No. Variable Alpha Cronbach Description 1. X1 0,820 Reliable 2. X2 0,873 Reliable 3. X3 0,872 Reliable 4. X4 0,843 Reliable 5. X5 0,861 Reliable 6. Y 0,801 Reliable Source: Primary data processing (2015)
  • 7. The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In DOI: 10.9790/1684-12658997 www.iosrjournals.org 95 | Page According to calculation can be conclude that the instrument of research is reliable. V. Result of Classical Assumption Test a. The Result of Heteroskedastisitas Test Scatter Plot of Heteroskedastisitas Test Figure 1.3 Scatter Plot of Heteroskedastisitas Test Based on the graphic that there is not an heteroskedastisitas to regression model. b. Test results Multicolinearity Table 1.8 The Result of Multicolinearity Assumption Test Independent Variable VIF Description X1 1.539 Non Multikolinear X2 1.282 Non Multikolinear X3 1.236 Non Multikolinear X4 1.286 Non Multikolinear X5 1.688 Non Multikolinear X6 1.781 Non Multikolinear Source: Primary data processing (2015) Based on the calculation show that every variables has the value of VHF no more than 10. c. Result of Normality Test The graphic of P-P Plot is shown in Figure 1.4 Figure 1.4 Normal P-P Plot of Regression Standardized Residual
  • 8. The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In DOI: 10.9790/1684-12658997 www.iosrjournals.org 96 | Page The standardized residual value make a linear pattern that indicate the residual value has normal distribution. Result of Analysis Table 1.9 Result of Multiple Regression Analysis No Variable Coefficient of Regression t-count Sig 1. X1 0.358 2.494 0.014 2. X2 0.549 3.219 0.002 3. X3 0.635 3.652 0.000 4. X4 0.675 2.944 0.004 5. X5 1.142 4.241 0.000 6. X6 0.709 2.157 0.033 Source: Primary data processing (2015) constanta = -5.480 R = 0.819 R Square = 0.670 Fcount = 38.658 Sig = 0.000 1. The coefficient of correlation (R) show the level of the relationship among the independent variables (X) simultaneously against the dependent variable (Y).. Value of R which is obtained from the analysis is 0.819 showed that the variables X (X1,X2, X3, X4 dan X5) ssimultaneously have a very strong relationship with Y. Table 1.10 Interpretation of Correlation Coefficient (r) Interval Coefficient Relationship Level (Interpretation) 0,00-0,199 Very low 0,20-0,399 Low 0,40-0,599 Enough 0,60-0,799 Strong 0,80-1,00 Very Strong 2. The value of R Square shows the contribution (contribution) independent variables were examined simultaneously on the dependent variable. The results of analysis R square value of 0.670 indicates if the independent variables (X1, X2, X3, X4, X5 and X6) simultaneously affect the dependent variable (Y) of 67.0% for the remaining 33.0% is influenced by other variables not examined in this study. 3. F Test F count indicates whether all independent variables (X) studied simultaneously have a significant influence on the dependent variable (Y). 4. t test From t test can conclude that all independent variables has the significant effect to dependent variable (Y). Regression Equation : Y = -5.480 + 0.358 X1 + 0.549 X2 + 0.635 X3 + 0.675 X4 + 1.142 X5 + 0.709 X6 The explanation of the equation are: a. Constanta about -5.480 show that if no effect of the independent variables so the dependent variable has the constant value about -5.480. b. Coefisient of regression X1 (b1) about 0.358 show that there is an positive effect between variable X1 against the variable Y, it mean that the higher the value of X1, the higher the value of Y. c. Coefisient of regression X2 (b2) about 0.549 show that there is an positive effect between variable X2 against the variable Y, it mean that the higher the value of X2, the higher the value of Y. d. Coefisient of regression X3 (b3) 0.635 show that there is an positive effect between variable X3 against the variable Y, it mean that the higher the value of X3, the higher the value of Y. e. Coefisient of regression X4 (b4) 0.675 show that there is an positive effect between variable X4 against the variable Y, it mean that the higher the value of X4, the higher the value of Y. f. Coeffisient of regression X5 (b5) 1.142 show that there is an positive effect between variable X5 against the variable Y, it mean that the higher the value of X5, the higher the value of Y. g. Coeffisient of regression X6 (b6) 0.709 show that there is an positive effect between variable X6 against the variable Y, it mean that the higher the value of X6, the higher the value of Y.
  • 9. The Relationship Between The Factors That Cause Road Damage And Its Effect On Road Damage In DOI: 10.9790/1684-12658997 www.iosrjournals.org 97 | Page VI. Conclusion There is a significant relationship among the factor that cause the road pavement failure following the equation: Y = -5.480 + 0.358 X1 + 0.549 X2 + 0.635 X3 + 0.675 X4 + 1.142 X5 + 0.709 X6 . Coeffisient of regression X5 (b5) 1.142 is greater than others it means that soil condition of peatland has more effect to road pavement damage. Suggestion It is important to know well the key of suitable maintenance for the road on peatland based on the the cause of failure to prevent more failure in the road pavement. Beside that it need a comprehensive design of the road refer to the cause of failure to anticipate the failure or damage of the road on peatland in Palangka Raya City. References [1] Aljouni, MA.(2000) Geotechnical Properties of Peat and Related Engineering Problems. PhD Dissertation, University of Illnois at Urbana-Champaign. [2] Asadi, A., Huat, B., Hanafi, M., Mohamed, T., Shariatmadari, N, (2009) Role of Organic Matter on Electroosmotic Properties and Ionic Modification of Organic Soils, Geocsci. J., 13(2):175-181. [3] Deboucha S, Hashim R, Alwi A. (2008) Engineering Properties of Stabilized Tropical Peat Soils. J. Geotech. Eng. 13E: 1-9. [4] Department of Civil Works City of Palangka Raya. (2010) Data of The Street in Palangka Raya City. [5] Islam MS, Hashim R. (2008a) Use of Macintosh Probe Test for Field Investigation in Peat Soil. Proceeding of The International Conference, May 26-27, Best Western Premier Seti Pacific Kuala Lumpur, Malaysia, pp 27. [6] Islam S, Hashim R. (2008b) Engineering Properties of Peat Soils In Peninsular Malaysia. J. Appl. Sci., 8(22). [7] Gofar, N (2006) Determination of Coefficient of Rate of Horizontal Consolidation of Peat Soil. Master Dissertation, Universiti Teknologi Malaysia, Malaysia [8] Gofar, Nurly and Sutejo, Yulindasari. (2007) Long Term Compression Behavior of Fibrous Peat. Malaysian Journal of Civil Engineering, 19 (2). Pp. 104-116. ISSN 1823-7843. [9] Huat, BBK. (2004) Organic and Peat Soils Engineering. University Putra Malaysia Press Serdang, Malaysia. [10] Kazemian S, Huat BBK. (2009a) Compressibility Characteristic of Fibrous Tropical Peat Reinforced with Cement Column, Electronic J. Geotech. Eng., 14E:1-8. [11] Kazemian S, Asadi A, Huat BBK. (2009c) Laboratory Study On Geotechnical Properties of Tropical Peat Soils, Int. J. Geotechnics Environ., 1:69-79. [12] Kazemian S, Prasad A, Huat BBK, Ali TAM, Aznieta FN. (2010a) Effect of cement, Sodium Silicate, Kaolinite and Water on The Viscosity of The Grout, Sci. Res. Essay J., 5(22): 3434-3442. [13] Mesri G, Aljouni M. (2007) Engineering Properties of Fibrous Peat. J. Geotech. Geoenviron. Eng., 133(7): 850-866. [14] Moayedi H, Asadi A, Huat BBK, Moayedi F. (2011a) Zeta Potential of Tropical Soil in Presence of Polyvinyl Alcohol, Int. J. ElectrochemSci., 6(5): 1294-1306. [15] Moayedi H, Asadi A, Huat BBK, Moayedi F. (2011b) Optimizing Stabilizers Enhanced Electrokinetic Environment to Improve Physicochemical Properties of Highly Organic Soil, Int. J. ElectrochemSci., 6(5): 1277-1293. [16] Muhamad IS, Gandaseca S, Ahmed OH, Majid NMA. (2010) Comparison of Selected Chemical Properties of Peat Swamp Soil Before and After Timber Harvesting. Am. J. Environ. Sci., 6 (2). [17] Said JM, Taib SNL(2009) Peat Stabilization with Carbide Lime. UNIMAS E-J. Civil Eng. 1:1. [18] Sudjana,(1996) Teknik Analisis Regresi dan Korelasi. Tarsito. Bandung. [19] Sugiyono, (2012) Metode Penelitian Kuantitatif Kualitatif dan R & B Alfabeta. Bandung. [20] Sukirman, S.(1995) Perkerasan Lentur Jalan Raya, Nova, Bandung. [21] Widayat (2004) Aplikasi Software SPSS. Universitas Muhammadiyah Malang. Malang. [22] Wong, Leong Sing (2005) Laboratory Evaluation of Horizontal Coefficient of Consolidation Cc of Fibrous Peat Soil, Master Dissertation, Universiti Teknologi Malaysia. [23] Wong LS, Hashim R, Ali FH. (2008) Strength and Permeability of Stabilized Peat Soil. J. Appl. Sci, 8(17):1-5. [24] Wong, Leong Sing., Hashim Roslan., Ali, Faisal Haji (2008) Compression Rates of Untreated and Stabilized Peat Soils, EJGE Volume 13, Bund. F. [25] Yulindasari I. (2006) Compressibilty Characteristic of Fibrous Peat Soil. Master Disstertation, Universiti Teknologi Malaysia, Malaysia