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Journal Of Economics, Technology, And Business (JETBIS)

Volume 2, Number 8 August 2023

p-ISSN 2964-903X; e-ISSN 2962-9330

ANALYSIS OF FACTORS AFFECTING THE EFFECTIVENESS OF HANDLING

OVER-DIMENSION AND OVERLOADING (ODOL)

IN EAST JAVA AT UPPKB TROSOBO SIDOARJO AND

UPPKB SINGOSARI MALANG

I Made Buda Atmajaya

, Haris Muhammadun

, Wateno Oetomo

Universitas 17 Agustus 1945 Surabaya

[email protected]

KEYWORDS:

freight transport;

Overdimension &;

Overloading; multiple linear

regression

ABSTRACT

The problem of Overdimension and Overloading (ODOL) freight

transportation has become a national issue. Various impacts caused by

ODOL freight transportation include a decrease in vehicle speed, a

decrease in road technical life, loss of road maintenance budget, vehicle

damage, and the occurrence of traffic accidents on the road. East Java

Province has a fairly high economic activity by using freight

transportation in various conditions including Overdimension and

Overloading. The Ministry of Transportation through the UPPKB

Service Unit throughout East Java has made various efforts to handle

ODOL freight transportation, but the level of violations of freight

transportation still occurs. This study aims to determine the factors that

affect the effectiveness of handling Overdimension and Overloading

(ODOL) in freight transportation so that it can provide recommendations

for appropriate ODOL handling. The data collection method used

interviews and questionnaires to Korsatpel, UPPKB Operational Staff,

and freight transport drivers. While the analysis method used fishbone

diagram analysis and multiple linear regression analysis using field data.

Based on the results of the study, it is known that the dominant factors

that affect the effectiveness of handling Overdimension and Overloading

(ODOL) in freight transportation are the enforcement of Tilang (X1) and

Transfer of Cargo / Transfer of Excess Load (X3) with the value of

coefficient determination at UPPKB Trosobo and Singosari of 96.1% and

92.3%. The handling recommendations given are the need to increase

ticket fines and provide transportation services for excess cargo in the

form of vehicles and transportation personnel as well as forklifts and

cranes at the UPPKB Satpel to move heavy loads.

INTRODUCTION

The burden of logistics costs in Indonesia based on Gross Domestic Product (GDP) still

reaches 27%. More expensive than Malaysia and Thailand (Djumena, n.d.). Land transportation

costs are the largest component of logistics costs in Indonesia, amounting to 66.8%. The rest is

administrative costs and inventory handling costs and added to the cost of loading and unloading,

parking, and illegal levies. This situation is a major threat to logistics sovereignty and national

competitiveness considering that an integrated logistics network between ASEAN countries was

implemented in 2015 and 2020 entered the global logistics network (Buxbaum et al., 2019).

Good road infrastructure is the spearhead in supporting the smooth running of the logistics

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network. In Indonesia, road infrastructure conditions severely hinder the development of the freight

transportation industry in Indonesia and limit the ability of small business owners to reach profitable

target markets (Ismail, 2023). Poor road quality is an obstacle to trade activities between regions and

hinders integration between underdeveloped regions with more modern markets. Poor road

infrastructure is not only caused by low road quality but also caused by overload and excess

dimensions of freight transportation (Overdimension and Overloading ( ODOL)).

The occurrence of load loads and excess dimensions of freight transportation is a complication

of various problems including a cross-freight transportation network that is not optimal, the location

of the Motor Vehicle Weighing Unit (UPPKB) node that is not strategic, the number of UPPKB

Human Resources (HR) that is inadequate, the level of compliance of freight transportation owners

is still low and so on. The above problems cannot be solved by the Government alone, but must

involve various related parties, including the community, transportation entrepreneurs, body

workshop owners and road users (Agus Wijaya & Jayus, n.d.).

The problem of Overdimension and Overloading freight transportation has become a national

issue to date (Asie et al., 2022). Various impacts caused by Overdimension and Overloading

(ODOL) freight transportation include: a decrease in speed resulting in traffic congestion, a decrease

in the technical life of the road resulting in premature damage to the road, road maintenance budget

losses reaching 43 trillion rupiah (Baketrans, 2023), Early damage to vehicle spare parts and the

occurrence of traffic accidents on the road.

According to data from the National Police of the Republic of Indonesia, the number of

accidents caused by ODOL trucks has reached 97% from 2020 as many as 30 cases to 59 cases in

2021. Then the death toll increased from 12 victims to 26 victims or an increase of 117%

(Dharmacaraka & Susilowati, 2019). Meanwhile, in terms of material losses using the gross roots

method , it was recorded to increase to 22 billion in 2021 from 8.9 billion in 2020 (Maulandy Rizky

Bayu Kencana, 2021).

In accordance with Law Number 22 of 2009 concerning Road Traffic and Transportation and

Law Number 23 of 2014 concerning Regional Government, the location, operation and closure of

weighing equipment installed permanently on roads is carried out by the Government and the

operation and maintenance of weighing equipment installed permanently is carried out by the Motor

Vehicle Weighing Implementation Unit (UPPKB) appointed by the Central Government (Aryaputra,

n.d.). As a follow-up to the mandate of Law Number 23 of 2014 concerning Regional Government,

the division of government affairs in the field of transportation has been transferred the management

of UPPKB from the Provincial Regional Government to the Central Government which includes:

Personnel, Funding, Facilities and Infrastructure and Documents (P3D) (CNN Indonesia, 2021).

This transfer aims to improve UPPKB's performance better than before.

The UPPKB Trosobo, Sidoarjo and UPPKB Singosari Service Units, Malang have tried to

carry out various efforts to handle Overdimension and Overloading freight transportation in the

field, including: law enforcement in the form of tickets / warnings and other enforcement, such as:

travel delays, cargo transfer / excess load transfer, vehicle U-turn and vehicle normalization.

However, Overdimension and Overloading freight transport violations still occur (Indonesia, 2014).

Based on the description of the problem above, it is necessary to conduct research entitled

"Analysis of Factors Affecting the Effectiveness of Overdimension and Overloading (ODOL)

Handling in the East Java Region at UPPKB Trosobo Sidoarjo and UPPKB Singosari Malang". This

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research is expected to identify the effectiveness of various Overdimension and Overloading

freight transportation handling and more appropriate handling recommendations in the future.

Some previous studies on Overdimension and Overloading (ODOL) of freight transportation,

among others: the first study on the Application of Criminal Sanctions Against Overdimensional

and Overloading Vehicle Drivers at UPPKB Cekik (Novayana et al., 2021). The method used is

empirical legal research. The results of the analysis show that the application of criminal sanctions

against drivers of overdimensional and overloading vehicles at UPPKB Cekik has not run well and

effectively. There are still many violations of freight trucks by changing vehicle dimensions in the

form of body shape, vehicle chassis and vehicle engine either partially or completely with the interest

that the goods transported can exceed the specified maximum limit. The second study on the

Effectiveness of Weighbridges in reducing ODOL (overdimension overloading) violations on the

North Java Cross Road (Case Study of Tanjung Brebes Weighbridge). The method used is

qualitative descriptive through observation, questionnaires and interviews. The results of the

analysis showed that the effectiveness of the Tanjung Brebes weighbridge of 79.1% was categorized

as quite effective in reducing overdimension overloading violations, the number of violations was

the most overloading with a percentage of 80% with a total of 7,134 vehicles. The third research is

on Juridical Analysis of the Implementation of Zero Overdimension and Overloading Policy in

Indonesia . The research method uses normative legal research methods (applied law research). The

results showed that the implementation of Zero ODOL was hampered due to economic factors, the

ineffectiveness of existing legal products and the Covid-19 pandemic. In addition, the unavailability

of adequate sanctions for Zero ODOL violations results in low enforcement of Zero ODOL policies

in Indonesia.

The purpose of the study is to analyze what factors affect the effectiveness of handling

Overdimension and Overloading (ODOL) of freight transportation in the East Java Region, analyze the

dominant factors that affect the handling of Overdimension and Overloading (ODOL) of freight

transportation in the East Java Region and provide recommendations for improvements in handling

Overdimension and Overloading (ODOL) of freight transportation in the East Java Region. While the

benefits in the research are as input material to the Government in efforts to handle Overdimension and

Overloading (ODOL) freight transportation in Indonesia and reference material for further research. The

data analysis method in this study that distinguishes it from previous studies is for the analysis of UPPKB

performance barriers using descriptive methods and fishbone diagrams and for handling ODOL using

multiple linear regression tests.

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RESEARCH METHODS

Location and Time of Research

Figure 1

UPPKB Trosobo Satpel Office, Sidoarjo

Figure 2

UPPKB Singosari Satpel Office, Malang

The research was conducted in 2 locations, namely Satpel UPPKB Trosobo, Sidoarjo which

is located at Jl. Raya Trosobo KM 21,700 Trosobo, Sidoarjo and Satpel UPPKB Singosari, Malang

which is located at Jl. Raya Singosari 3, Malang.

The research time is 5 days (weekdays) during UPPKB operating hours.

Research Instruments

Equipment used to support data retrieval in the field includes:

1. Survey forms, stationery and clip boards are used to record the results of observational surveys

and interviews in the field;

2. Mobile phones are used to document during field surveys;

3. Vests are used for body armor and surveyor identity while in the field;

4. Hats are used for head protection from the heat of the sun and surveyor's identity while in the

field;

5. Laptops are used to process or process survey data in the field.

Data Collection Techniques

This stage aims to obtain the information needed to achieve research objectives. Techniques

used to collect data in this study include: interviews, questionnaires and documentation.

Data Primer

This data is obtained from field surveys and interviews or questions and answers directly to

respondents and filling out questionnaires through google forms. The respondents in this study

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were Korsatpel, UPPKB officers and freight transport drivers.

Secondary data

This data is used to support research. This data includes:

1. Daily Traffic Data of freight transportation (Satpel UPPKB Trosobo and UPPKB Singosari)

2. Freight Transport Violation Data (Satpel UPPKB Trosobo and UPPKB Singosari)

3. Data on Enforcement of Freight Transport Violations (Satpel UPPKB Trosobo and UPPKB

Singosari)

Data Analysis Techniques

The techniques used to analyze the data consist of:

Freight Transport Violation Data Analysis

The method used to analyze freight violation data uses a pie chart (pie chart diagram). In this

diagram, the composition of each violation is symbolized by a percentage value (highest and lowest).

In deciphering the details of breach data using descriptive analysis.

Freight Transport Violation Enforcement Analysis

The method used to analyze data on the enforcement of freight transport violations uses a pie

chart (pie chart diagram). In this diagram, the composition of each violation is symbolized by a

percentage value (highest and lowest). In deciphering the details of violation enforcement data using

descriptive analysis.

Fish Bone Diagram Analysis

Used to analyze obstacle factors / obstacles in the enforcement of freight transportation

violations. Where each obstacle is depicted in a branch of fish bones.

Multiple Linear Regression Analysis

In determining the research variable (X) using regulatory guidelines on handling

Overdimension and Overloading (ODOL) of freight transportation carried out by the Government.

Regression analysis used using multiple linear regression analysis. Where will compare the effect

of each enforcement of freight transportation violations (speeding tickets, cargo transfer / overload

transfer, U-turn, travel delays, vehicle normalization) on the number of Overdimension and

Overloading (ODOL) violations of freight transportation using field data at UPPKB (Perhubungan,

2020). The dependent / bound variable in this study is the number of violations of Overdimension

and Overloading (ODOL) of freight transportation (Y). While the independent / independent

variables are all enforcement of freight transportation violations, in the form of: speeding tickets

(X1), travel delays (X2), cargo transfer / overload transfer (X3), vehicle normalization (X4) and U-

turns (X5).

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Figure 3

Research Variables (Dependent and Independent)

RESULTS AND DISCUSSION

Research Sample Calculation

The population used in the study was the entire freight transport drivers who passed through

Jalan Krian – Taman Sidoarjo and Jalan Singosari. While the sampling refers to the Average Annual

Daily Traffic of Freight Transport at Satpel UPPKB Trosobo and UPPKB Singosari. In the

calculation of the number of samples using the Slovin formula (Ilie & Ciocoiu, 2010).

a. Number of Samples at UPPKB Trosobo

The Total Annual Average Daily Traffic of Freight Transport per year 2020 at Satpel UPPKB

Trosobo (N) is 3,558 vehicles (CNN Indonesia, 2021). Margin of error (e) = 10%. So that the

number of samples (n) is obtained:

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The minimum number of samples needed in research at UPPKB Trosobo is 100 samples.

b. Number of Samples at UPPKB Singosari

The Total Annual Average Daily Traffic of Freight Transport per year 2021 at Satpel UPPKB

Singosari (N) is 6,098 vehicles (CNN Indonesia, 2021). Margin of error (e) = 10%. So that the

number of samples (n) is obtained:

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The minimum number of samples needed in research at UPPKB Singosari is 100 samples.

Results of Characteristic Analysis with Descriptive Statistics

Descriptive analysis serves to determine the characteristics of respondents, namely freight

transport drivers as people involved in Overdimension and Overloading violations of freight

transportation and UPPKB officers as people who handle/act on Overdimension and Overloading

freight transportation at UPPKB. The results of the questionnaire that have been distributed to

respondents through google forms are then recapitulated. The results of the analysis of descriptive

statistical characteristics are as follows:

a. Characteristics of Freight Transport Drivers at UPPKB Trosobo

number of ODOL

violations of

freight transport

(Y)

Ticketed (X1)

Travel delays (X2)

Load transfer/overload transfer

(X3)

Vehicle normalization (X4)

Rewind to where the trip came

from (X5)

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Figure 5

Distribution Diagram of Characteristics of Freight Transport Drivers at UPPKB Trosobo

Based on the picture above, it can be seen that the characteristics of freight transportation

drivers at UPPKB Trosobo are the most age in the range of 26 to 45 years old by 55 people (55.0%),

the most male gender is 100 people (100%), the last most education is in high school / equivalent by

59 people (59.0%), the highest average income per month is Rp. 2,500,000,- up to Rp. 5.000.000,-

amounting to 88 people (88.0%), the most types of freight transportation vehicles pickup open /

closed tubs (konf. Axis 1.1 and JBI: 1,800 to 3,500 kg) amounted to 35 people (35.0%), the highest

vehicle load in the form of general goods (general loads, metal, wood, cargo loaded into pallets /

packed, vehicles with side curtain lids and sheet glass) amounted to 44 people (44.0%) and the most

vehicle ownership status was owned by the Company (PT / CV) by 43 people (43.0%).

a. Characteristics of Freight Transport Drivers at UPPKB Singosari

Figure 6

Distribution Diagram of Characteristics of Freight Transport Drivers at UPPKB Singosari

Based on the picture above, it can be seen the characteristics of freight transportation drivers

at UPPKB Singosari, namely the most age is in the range of 26 to 45 years old by 58 people (58.0%),

the most male gender is 100 people (100%), the last most education is in high school / equivalent by

50 people (50.0%), the highest average income per month is Rp. 2,500,000,- up to Rp. 5.000.000,-

amounting to 91 people (91.0%), the most types of freight transportation vehicles pickup open /

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closed tubs (konf. Axis 1.1 and JBI: 1,800 to 3,500 kg) amounted to 46 people (46.0%), the highest

vehicle load in the form of general goods (general loads, metal, wood, cargo loaded into pallets /

packed, vehicles with side curtain lids and sheet glass) amounted to 40 people (40.0%) and the most

vehicle ownership status belonged to other people by 40 people (40.0%).

b. Characteristics of UPPKB Trosobo Officers

Figure 7

Distribution Diagram of UPPKB Trosobo Officer Characteristics

c. Characteristics of UPPKB Singosari Officers

Figure 8

Distribution Diagram of UPPKB Singosari Officer Characteristics

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Results of Fish Bone Analysis Diagram of Obstacles / Obstacles in Handling ODOL Freight

Transport

Based on fish bone analysis, the obstacle diagram / obstacle handling ODOL freight

transportation obtained in the field (Ribbens-Pavella et al., 1985).

Figure 9

Fishbone Analysis Diagram of obstacles / obstacles handling ODOL freight transportation

From the results of the Fishbone Diagram analysis of Obstacles / Obstacles in handling ODOL

Freight Transportation there are 5 main factors, namely:

1. Law enforcement does not cause a deterrent effect (3 root causes)

2. Circulating vehicles are not testworthy / fake kir test books (3 root causes)

3. UPPKB does not function optimally both on roads and ports (3 root causes)

4. Lack of consistency in ODOL vehicle law enforcement (3 root causes)

5. Rejection and resistance of the Zero ODOL program (3 root causes)The root causes are obtained

from various problems that occur in the field.

As for the obstacles / obstacles of each handling ODOL freight transportation at UPPKB can be

seen in the picture below.

Figure 10

Fishbone Analysis Diagram of obstacles / obstacles Tilang at UPPKB

Figure 11

Fishbone Analysis Diagram of Travel Delay obstacles at UPPKB

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Figure 12

Fishbone Analysis Load Transfer bottleneck/constraint diagram in UPPKB

Figure 13

Fishbone Analysis Diagram of obstacles / constraints of Vehicle Normalization at UPPKB

Figure 14

Fishbone Analysis Bottleneck/constraint diagram U-turn at UPPKB

Results of Data Analysis of Freight Transport Violations at UPPKB

1. Data on Freight Transport Violations at UPPKB Trosobo from 2019 to 2022

The results of the recapitulation of data on violations of freight transportation at UPPKB

Trosobo from 2019 to 2022 can be seen in the following table and figure.

Table 1

Recapitulation of Freight Transport Violations at UPPKB Trosobo from 2019 to 2022

No.

Types of Violations

Sum

Percentage

Payload + Dimension (ODOL)

39.275

46,7%

Technical requirements

3.304

3,9%

Loading Procedures

12.823

15,2%

Document

28.778

34,2%

Total Amount

84.180

100%

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Figure 15

Diagram of the Percentage of Freight Transport Violations at UPPKB Trosobo

Year 2019 to 2022

The majority of freight transportation violations at UPPKB Trosobo during 2019 to 2022

were in the form of Carrying Capacity and Dimensions (ODOL) of 39,275 vehicles (46.7%).

a. Data on Freight Transport Violations at UPPKB Singosari from 2019 to 2022

The results of the recapitulation of data on violations of freight transportation at UPPKB

Singosari from 2019 to 2022 can be seen in the following table and figure.

Table 2

Recapitulation of Freight Transport Violations at UPPKB Singosari from 2019 to 2022

No.

Types of Violations

Sum

Percentage

Payload + Dimension (ODOL)

47.697

48,9%

Technical requirements

2.908

3,1%

Loading Procedures

12.478

12,8%

Document

34.292

35,2%

Total Amount

97.447

100%

Figure 16

Percentage Diagram of Freight Transport Violations at UPPKB Singosari

Year 2019 to 2022

The majority of freight transportation violations at UPPKB Singosari during 2019 to 2022

were in the form of Carrying Capacity and Dimensions (ODOL) of 47,697 vehicles (46.7%).

Results of Data Analysis of Enforcement of Freight Transport Violations at UPPKB

a. Data on Enforcement of Freight Transport Violations at UPPKB Trosobo from 2019 to 2022

The results of the recapitulation of data on the enforcement of violations of freight

transportation at UPPKB Trosobo from 2019 to 2022 can be seen in the following table and

figure.

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Table 3

Recapitulation of Enforcement of Freight Transport Violations at UPPKB Trosobo

Year 2019 to 2022

No.

Jenis Penindakan Pelanggaran

Jumlah

Persentase

Peringatan

17.353

20,6%

Tilang Kepolisian

7.229

8,6%

Tilang UPPKB

41.304

49,1%

Keseluruhan Penindakan

18.294

21,7%

Jumlah Total

84.180

100%

Figure 17

Percentage Diagram of Enforcement of Freight Transport Violations at UPPKB Trosobo

Year 2019 to 2022

The majority of enforcement of freight transportation violations at UPPKB Trosobo during

2019 to 2022 in the form of UPPKB tickets were 41,304 vehicles (49.1%).

b. Data on Enforcement of Freight Transport Violations at UPPKB Singosari from 2019 to 2022

The results of the recapitulation of data on the enforcement of violations of freight transportation

at UPPKB Singosaru from 2019 to 2022 can be seen in the following table and figure.

Table 4

Recapitulation of Enforcement of Freight Transport Violations at UPPKB Singosari

Year 2019 to 2022

No.

Types of Violation

Enforcement

Sum

percentage

Commemoration

16.629

17,1%

Police Ticke

8.663

8,9%

UPPKB ticket

49.083

50,4%

Overall Enforcement

23.072

23,7%

Total Amount

97.447

100%

Figure 18

Percentage Diagram of Enforcement of Freight Transport Violations at UPPKB Singosari

Year 2019 to 2022

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The majority of enforcement of goods transportation violations at UPPKB Singosari during

2019 to 2022 in the form of Carrying Capacity and Dimensions (ODOL) was 49,083 vehicles

(50.4%).

Multiple Linear Regression Test Results

This test was carried out using SPSS software between independent variables (each

enforcement of ODOL violations) against dependent / bound variables (number of ODOL

violations)

Results of Tilang Regression Test (X1) and Travel Delay (X2) on the Number of ODOL

(Y) Violations at UPPKB Trosobo

a. Output Analysis of Coefficient of Determination

It is known that the adjusted R square value of 0.898 then it is concluded that the effect of

the independent variable (speeding tickets and travel delays) on the dependent variable (the

number of ODOL violations) simultaneously (together) is 89.8%.

Model Summary

Model

R Square

Adjusted R

Square

Std. The error

of the Estimate

.950

.903

.898

18.470

a. Predictors: (Constant), Penundaan_Perjalanan_X2, Tilang_X1

b. F Test Outpit Analysis (Simultaneous)

Hypothesis :

There was no significant effect between the independent variable and the dependent

variable simultaneously (model not fit / not feasible)

There is a significant influence between the independent variable and the dependent

variable simultaneously (fit / feasible model)

Test Statistics :

• H0 rejected if value Sig. < 0,05

• H0 rejected if F value count > F tabel

ANOVA

Model

Sum of Squares

Mean Square

Sig.

Regression

142570.764

71285.382

208.957

.000

Residual

15351.715

341.149

Total

157922.479

a. Predictors: (Constant), Penundaan_Perjalanan_X2, Tilang_X1

b. Dependent Variable: Jumlah_Pelanggaran_ODOL_Y

Interpretation of Test Results :

Based on the table above, it can be seen that the value of Sig. = 0.000 < 0.05 and the value of

F count = 208.987 > F table = 3.20 (DF1 = 2 and DF2 = N-2-1 = 48-2-1 = 45) so that H0 is rejected.

So it is concluded that the fit / feasible model and the independent variable (speeding tickets and

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travel delays) have a significant effect on the dependent variable (number of ODOL violations)

simultaneously (together).

c. T-Test Analysis

Hypothesis :

There was no significant effect between the independent variable and the dependent

variable partially

There is a significant influence between the independent variable and the dependent

variable partially

Test Statistics :

• H0 rejected if value Sig. < 0,05

• H0 rejected if value T hitung > T tabel

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig.

Std.

Error

Beta

(Constant)

5.874

12.299

.478

.635

Tilang_X1

.719

.080

.655

9.012

.000

Penundaan_Perjalanan_X2

.620

.129

.350

4.816

.000

a. Dependent Variable:

Jumlah_Pelanggaran_ODOL_Y

Interpretation of Test Results :

Based on the table above, it can be seen that :

a. Ticket Variable (X1)

Sig. value = 0.000 < 0.05 and calculated T value = 9.012 table T > = 2.01410 (DF = 45, α =

5% for 2-sided test) so H0 is rejected. So it is concluded that the ticket variable (X1) has a

significant effect on the variable number of ODOL violations (Y) partially.

b. Travel Delay Variable (X2)

Sig. value = 0.000 < 0.05 and calculated T value = 4.816 table T > = 2.01410 (DF = 45, α =

5% for 2-sided test) so H0 is rejected. So it is concluded that the variable of travel delay (X2)

has a significant effect on the variable number of ODOL violations (Y) partially.

Multiple Linear Regression Equation Analysis

a. Regression equation obtained:

Y = 0,719 X1 + 0,620 X2 + 5,874

b. The constant value obtained is 5.874 then it means that if the independent variable is 0 (zero)

(constant) then the dependent variable is 5.874.

c. The value of the regression coefficient of variable X1 is positive (+) of 0.719, so it can be

interpreted that if variable X1 increases, variable Y will also increase and vice versa.

d. The value of the regression coefficient of variable X2 is positive (+) of 0.620, so it can be

interpreted that if variable X2 increases, variable Y will also increase and vice versa.

Next, using the same method, repeat steps (1) to (4) to test the model on Variables X3,

X4, X5 at UPPKB Trosobo and UPPKB Singosari.

CONCLUSION

Factors affecting the effectiveness of handling Overdimension and Overloading (ODOL)

violations of freight transportation in the East Java Region Tilang Enforcement (X1), consisting of:

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Analysis Of Factors Affecting The Effectiveness Of Handling

Over-Dimension And Overloading (Odol) In East Java At

Uppkb Trosobo Sidoarjo And Uppkb Singosari Malang

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drivers, vehicle owners (individuals / companies), UPPKB officers and courts / prosecutors, Travel

Delay Enforcement (X2), consisting of: drivers, vehicle owners (individuals / companies) and

UPPKB officers, Cargo Transfer Enforcement (X3), consisting of: drivers, vehicle owners

(individuals / company), UPPKB officers and the surrounding community, Vehicle Normalization

Enforcement (X4), consisting of: drivers, vehicle owners (individuals / companies), UPPKB officers

and body body workshops, U-turn Enforcement (X5), consisting of: drivers, vehicle owners

(individuals / companies) and UPPKB Satpel, The dominant factor affecting the handling of

Overdimension and Overloading (ODOL) violations of freight transportation in the East Java

Region, especially the UPPKB Trosobo and UPPKB Singosari Satpel based on the coefficient value,

the largest determination is the enforcement of speeding tickets (X1) and Cargo Transfer / Overload

Transfer (X3) by 96.1% and 92.3%, recommendations for improvement in handling violations of

Overdimension and Overloading (ODOL) of freight transportation in the East Java Region include

the need for increased law enforcement at UPPKB such as ticket fines that need to be aggravated;

The need for a routine agenda of cutting / normalizing vehicles accompanied by legal sanctions in

the form of prison confinement and large fines, The need to build an integrated database system

between the Online Weighbridge (JTO) and E-Blue (proof of passing the electronic test) to minimize

falsification of test books, The need to improve UPPKB facilities, UPPKB HR competency

qualifications and UPPKB PPNS authority by reviewing existing regulations, The need to establish

a special forum between institutions to deal with violations of Overdimension and Overloading

(ODOL) freight transportation, The need for the establishment of a Special Task Force engaged in

violations of Overdimension and Overloading (ODOL) freight transportation with strong authority,

The need for freight transportation subsidies from the Government to reduce vehicle operational

costs that are large enough for entrepreneurs and freight transport drivers.

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