Volume 14, Issue 06 (June 2025)

Road Improvement Based on The Results of Road Deflection Test on Brigjend. Pol Imam Bachri HP Road Kediri City

DOI : 10.17577/IJERTV14IS060136

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Rahmat Sutomo, R.A Retno Hastijanti, Hanie Teki Tjendani, 2025, Road Improvement Based on The Results of Road Deflection Test on Brigjend. Pol Imam Bachri HP Road Kediri City, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume 14, Issue 06 (June 2025),

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Road Improvement Based on The Results of Road Deflection Test on Brigjend. Pol Imam Bachri HP Road Kediri City

Rahmat Sutomo

Department of Civil Engineering 17 Agustus 1945 University Surabaya, Indonesia

R.A Retno Hastijanti

Department of Civil Engineering 17 Agustus 1945 University Surabaya, Indonesia

Hanie Teki Tjendani

Department of Civil Engineering 17 Agustus 1945 University Surabaya, Indonesia

Abstract Roads are vital infrastructure that support community mobility and economic growth. Road damage can reduce comfort, safety, and service life. Over time and with increasing service age, road quality generally deteriorates, as indicated by damage to the pavement structure. Roads with high traffic volumes tend to experience faster surface quality degradation. This condition can lead to discomfort and pose safety risks for road users. One of the damaged road sections in Kediri City is Brigjend. Pol. Imam Bachri Hadi Pranoto Street. The damage includes 30 potholes, which have caused accidents along this road. This road serves as a strategic route for distribution and tourism access to Mount Kelud. This study aims to determine the necessary road improvement efforts based on the results of the Benkelman Beam deflection test. The analysis is conducted to formulate repair actions based on the 2024 Road Pavement Design Manual. The analysis results recommend the implementation of a 70 mm thick overlay to enhance the strength of the existing pavement structure.

Keywords Road, Road Improvement, Benkelman Beam

  1. INTRODUCTION

    Roads play a crucial role in the development of society as essential infrastructure for transportation, serving as a lifeline that connects communities. They hold strategic importance in supporting the achievement of national development goals, including equitable development and distribution of its benefits, stimulating economic growth, and realizing social justice for all Indonesians (Susantio, 2015). Roads are land- based infrastructure that include supporting and complementary structures intended for traffic, which may be located on the ground surface, above it, or below it, excluding railways, lorry tracks, and cable lines (Godinho et al., 2025). This role is emphasized in Law of the Republic of Indonesia Number 38 of 2004 concerning Roads, which states that roads are part of the national transportation system and have a vital function in supporting social, economic, cultural, and environmental sectors.

    Improving the quality of road infrastructure plays a crucial role in driving economic growth within a region. The development and maintenance of road networks are essential components of national development, as adequate road infrastructure not only enhances mobility and connectivity between regions but also contributes significantly to economic growth, social development, and the overall improvement of community welfare (Zuria et al., 2024).

    According to Susantio (2015) and Fikri (2016), over time and with the increasing service age, road performance tends to deteriorate, as indicated by the emergence of damage to the pavement structure. Roads with high traffic volumes are particularly susceptible to surface quality degradation. This condition may lead to discomfort and safety risks for road users (Evitya, 2020).

    Road damage can be caused by various factors, including traffic loads that exceed design capacity, the presence of water, substandard pavement materials, climatic conditions, subgrade instability, and inadequate compaction processes (Sukirman, 1991 as cited in Putra et al., 2022). Road damage in a particular area can hinder the smooth operation of community activities within and around the affected region. Technically, road damage occurs when the pavement exhibits structural and functional failures, ultimately preventing the road from providing optimal service to passing traffic (Ladja et al., 2022).

    Brigjend. Pol. Imam Bachri Hadi Pranoto Road is a critical roadway that plays a vital role in facilitating access and supporting the economic activities of the people in Kediri City. In addition to serving as a primary route to the Gunung Kelud tourist area, it also functions as a major distribution corridor for sand materials from Mount Kelud.

    According to a report by Radar Kediri (2025), Brigjend. Pol. Imam Bachri Hadi Pranoto Road in Kediri City has experienced damage characterized by the presence of potholes

    at 30 locations. These potholes have contributed to traffic accidents along the road, with the damage worsening during the rainy season. This condition has led to a decline in the level of service provided by this road segment.

    B. Research Location and Time

    The research was conducted along Brigjend. Pol. Imam Bachri Hadi Pranoto Road in Kediri City. The study was carried out over a period of six months, starting from the literature review, data collection, to analysis. The literature review was conducted over a span of two months, data collection took three months, and the analysis and conclusion stages were completed within four months. The location of this studi presents on the Figure 1.

    .

    Figure 1 Road Condition

    Source: Researcher Documentation, 2025

    The image illustrates the locations of damage along Brigjend. Pol. Imam Bachri Hadi Pranoto Road in Kediri City. The observed damage can be categorized into several levels of severity. Minor damage, such as small potholes on the road surface, is present at various points along the roadway. In addition, moderate damage is identified in the form of longitudinal hairline cracks on the asphalt surface, indicating potential structural deterioration within the surface layer. Furthermore, severe damage is also evident, characterized by changes in asphalt elevation such as surface depressions or heaving that pose risks to road user comfort and safety. To address these issues, a road improvement analysis using overlay thickness is required.

    This integrated approach is highly beneficial for making technical decisions regarding road improvement. By applying the 2024 Road Pavement Design Manual method, this study aims to determine the optimal road treatment strategy to repair existing damage and strengthen the pavement structure to accommodate the planned traffic load effectively.

  2. METHODOLOGY

    A. Research Design

    The type of research conducted in this study is descriptive quantitative. The research was carried out by collecting road deflection test data using the Benkelman Beam method and average daily traffic (ADT) data. The collected data were then analyzed using formulas based on the 2024 Road Pavement Design Manual..

    Figure 2 Research Location

    Source: DPUPR Kediri City, 2025

    C. Data Collection

    The data collected in this study are categorized into two types: primary data and secondary data, as detailed below:

    1. Primary Data

      Data obtained through direct measurements and surveys at the research site are referred to as primary data. The primary data used in this study include the following:

      1. Indetification road damage

      2. Road Deflection Test (Benkelman Beam)

        The road deflection test data in this study were obtained using the Benkelman Beam (BB) method. This test was conducted to determine the magnitude of elastic deflection caused by traffic loads on the pavement. The following are several documentation images taken durng the road deflection survey using the Benkelman Beam (BB).

        Figure 3 Road Deflection Survey

        Source: Researcher Documentation, 2025

        The results of the deflection test measurements can be seen in the following table.

        Sta

        Load

        D0

        D200

        Field Temperature [Oc]

        Existing Asphalt Thickness [mm]

        [kN] [µm] [µm]

        0+000

        117.68

        750

        320

        39

        150

        0+250

        117.68

        990

        380

        39

        150

        0+500

        117.68

        980

        390

        39

        150

        0+750

        117.68

        880

        360

        39

        150

        1+000

        117.68

        1070

        430

        39

        150

        1+250

        117.68

        1240

        520

        39

        150

        1+500

        117.68

        1280

        510

        39

        150

        1+750

        117.68

        1140

        460

        39

        150

        2+000

        117.68

        1050

        420

        39

        150

        2+250

        117.68

        1150

        460

        39

        150

        Table 1 Benkelman Beam Test Result

        Source: Researcher Analysis, 2025

        The table presents the results of pavement deflection testing using Benkelman Beam which has been converted to Falling Weight Deflectometer (FWD).

    2. Secondary Data

      1. Average daily traffic (ADT) Data

    Table 2 Annual Average Daily Traffic (AADT)

    Vehicle types

    ADT

    ( 2 Direction)

    ADT2025

    Type 1-4

    16819

    17,408

    Type 5 A

    37

    38

    Type 5 B

    25

    26

    Type 6 A

    159

    165

    Type 6 B

    210

    217

    Type 7A1

    115

    119

    Type 7B2

    15

    16

    Source: DPUPR Kediri City, 202

    The Average Daily Traffic (ADT) volume increased from 17,380 to 17,989 vehicles in 2025, representing a growth of approximately 3.5%. The increase occurred across all vehicle types, with light vehicles remaining the dominant category..

    D. Analysis Method

    The road improvement analysis is selected based on the type and condition of the existing damage. The steps of the road improvement analysis are as follows..

    1. Road damage identification Data collected from field surveys were processed and analyzed using Microsoft Excel software.

    2. Road Deflection Test

      The Benkelman Beam test is used to measure deflection on the asphalt surface. The testing device is placed between the left/right dual wheels of a truck with an 8.2-ton rear axle load. Dial gauge readings are taken twice: once when the truck moves forward by 0.2 meters, and again when it moves 6 meters away from the Benkelman Beam device.

    3. Determinationof Road Improvement

      The overlay analysis involves traffic analysis and overlay design, detailed as follows:

      Traffic Analysis

      • Calculate the cumulative traffic growth factor (R),

      • Determine the directional distribution factor (DD),

      • Determine the lane distribution factor (DL),

      • Determine the Vehicle Damage Factor (VDF),

      • Determine the design life of the road,

      • Calculate the cumulative equivalent standard axle load (CESAL) over the design life.

        Overlay Design Analysis

        Determine the minimum overlay thickness to meet the following criteria:

        • Profile correction to reduce the IRI value to 3 m/km

        • Superelevation correction

        • Requirements based on maximum deflection

    Determining the minimum overlay thickness, if a thin overlay meets both the structural requirements and is capable of reducing the International Roughness Index (IRI) to 3 m/km, it can be chosen as the primary option. However, if the thin overlay does not meet either criterion, an alternative overlay that satisfies the structural requirements and achieves the target IRI value of 3 m/km should be used.

  3. RESULT

    1. Analsis Beban Sumbu Standar (ESA)

      Table 3 Analysis of Design Lane Traffic Load

      Vehicle types

      VDF 4

      VDF 5

      ESA 4

      ESA 5

      Factual

      Factual

      2025-2035

      2025-2035

      Type 1-4

      –

      –

      –

      –

      Type 5 A

      –

      –

      –

      –

      Type 5 B

      1,20

      1,30

      95.059,479

      102.981,102

      Type 6 A

      0,50

      0,40

      249.424,083

      199.539,266

      Type 6 B

      2,70

      3,70

      1.774.657,702

      2.431.938,332

      Type 7A1

      10,30

      16,50

      3.704.750,497

      5.934.794,486

      Type 7B2

      18,20

      26,70

      857.248,092

      1.257.611,213

      Sum of ESA

      6.681.139,85

      9.926.864,40

      Source: Researcher Analysis, 2025

      The Average Daily Traffic (ADT) volume increased from 17,380 to 17,989 vehicles in 2025, representing a growth of approximately 3.5%. The increase occurred across all vehicle types, with light vehicles remaining the dominant category. Articulated trucks recorded the highest percentage increase, reaching 6.7%.

      Table 4 Benkelman Beam Test Data

      Sta

      Load

      D0

      D200

      Field Temperature [Oc]

      Existing Asphalt Thickness

      [mm]
      [kN] [µm] [µm]

      0+000

      117.68

      750

      320

      39

      150

      0+250

      117.68

      990

      380

      39

      150

      0+500

      117.68

      980

      390

      39

      150

      0+750

      117.68

      880

      360

      39

      150

      1+000

      117.68

      1070

      430

      39

      150

      1+250

      117.68

      /td>

      1240

      520

      39

      150

      1+500

      117.68

      1280

      510

      39

      150

      1+750

      117.68

      1140

      460

      39

      150

      2+000

      117.68

      1050

      420

      39

      150

      2+250

      117.68

      1150

      460

      39

      150

      Source: Researcher Analysis, 2025

      Table 4 The table presents the results of pavement deflection testing using Benkelman Beam which has been converted to Falling Weight Deflectometer (FWD) at several observation points (STA) ranging from STA 0+000 to STA 2+250. At each point, a load of 117.68 kN was applied under a constant field temperature of 39°C. These test results were subsequently used for deflection analysis calculations, as shown in Table 5..

      Table 5 Deflection Analysis

      STA

      D0

      normal

      D200

      normal

      D0-200

      normal

      AMPT / Field Temp

      0+000

      254.93

      108.77

      146.16

      1.05

      0+250

      336.5

      129.16

      207.34

      1.05

      0+500

      333.11

      132.56

      200.54

      1.05

      0+750

      299.12

      122.37

      176.75

      1.05

      1+000

      363.7

      146.16

      217.54

      1.05

      1+250

      421.48

      176.75

      244.73

      1.05

      1+500

      435.08

      173.35

      261.73

      1.05

      1+750

      387.49

      156.36

      231.13

      1.05

      2+000

      356.9

      142.76

      214.14

      1.05

      2+250

      390.89

      156.36

      234.53

      1.05

      Source: Researcher Analysis, 2025

      The results of the pavement deflection analysis are based on normalized values derived from Falling Weight Deflectometer (FWD) testing data at several observation points (STA). The parameters presented include the normalized deflection at the center of the load (D normal), the deflection at a distance of 200 mm from the load center (D normal), and the difference between them (DD normal), which reflects the structural response of the pavement layers to dynamic loading.

      The D normal values range from 254.93 to 435.08 µm, while the D normal values vary between 108.77 and 173.35 µm. The deflection difference (DD normal) indicates the rate of deflection reduction with increasing distance from the load center, ranging from 146.16 to 261.73 µm. A constant correction factor for temperature or thickness (AMPT/T. Layer) of 1.05 was applied at all points. This data provides an overview of the structural condition of the pavement and serves as a basis for evaluating and determining the necessary pavement reinforcement.

      Table 6 Deflection Analysis

      Sta

      D0

      Factor Correction Temp

      D0-200

      Factor Correction

      Temp

      D0

      Corrected

      D0-200

      Corrected

      D0

      Adjustment to FWD

      0+000

      1.03

      1.04

      262.58

      152

      181.18

      0+250

      1.03

      1.04

      346.6

      215.63

      239.15

      0+500

      1.03

      1.04

      343.1

      208.56

      236.74

      0+750

      1.03

      1.04

      308.09

      183.82

      212.58

      1+000

      1.03

      1.04

      374.61

      226.24

      258.48

      1+250

      1.03

      1.04

      434.12

      254.52

      299.55

      1+500

      1.03

      1.04

      448.13

      272.19

      309.21

      1+750

      1.03

      1.04

      399.11

      240.38

      275.39

      2+000

      1.03

      1.04

      367.61

      222.7

      253.65

      2+250

      1.03

      1.04

      402.62

      243.91

      277.8

      Sum

      2,219.98

      2,543.73

      Average

      222

      254.37

      Standart Deviation

      39.02

      Variation Coefficien

      15.30%

      Characteristic Deflection

      318.56

      Source: Researcher Analysis, 2025

      Table 6 presents the results of further analysis of pavement deflection data that have been corrected based on the temperature correction factor (Temp Correction Factor) for the parameters D and D. The D and D values corrected for temperature were then used to calculate the final values adjusted to the Falling Weight Deflectometer (FWD) standard. The corrected D values range from 262.58 to 438.13 µm, while the corrected D values range from 152 to 258.42 µm. The adjustment of D values to the FWD standard resulted in final values ranging from 181.18 to 303.65 µm. The average adjusted D value is 254.73 µm, with a standard deviation of

      39.02 µm and a coefficient of variation of 15.30%, indicating a moderate degree of data dispersion. Based on these calculations, the characteristic deflection value is determined to be 318.56 µm, which serves as a fundamental parameter in evaluating pavement structural strength and designing the overlay thickness.

    2. Overlay Analysis

    The analysis using the 2024 Road Pavement Design Manual method yielded the following values:

    D0 average, 0 = 0,25 mm Standart Deviation, s = 0,039 mm Variation Coeficien = 15,30 % D0 representative = 0,32 mm D0 D200 average = 0,22 mm

    ADT 2034 = 6.681.139,85 ESA4

    = 9.926.864,40 ESA5

    These values are then plotted into the overlay thickness determination graph, as shown in Figure 4 and Figure 5 below.

    Figure 4 Determination of Overlay Thickness (Thin)

    Source: Researcher Analysis, 2025

    This graph is utilized to determine the required overlay thickness based on the target deflection value after reinforcement and the projected cumulative traffic loading. The intersection of the red horizontal and vertical guide lines represents the calculated values that reflect the actual conditions, namely the characteristic deflection and design traffic load. From the graph, it can be observed that for a design load of approximately 10 million ESAL and a target deflection of around 0.22 mm, the required overlay thickness falls within the range of 70 mm, as indicated by the dashed red curve. This information serves as a reference in designing the pavement overlay thickness to ensure it can sustain traffic loads over the intended design life.

    Figure 5 Determination of Overlay Thickness (Thick)

    Source: Researcher Analysis, 2025

    Based on the overlay thckness determination graph, an overlay thickness of 100 mm was initially identified. However, to enhance the structural capacity of the existing pavement to adequately support the anticipated traffic loads, the implementation of an overlay is required. The analysis results indicate that an overlay thickness of 70 mm satisfies both structural criteriaresistance to permanent deformation and fatigue crackingas well as the minimum thickness requirement to reduce the International Roughness Index (IRI) value. Therefore, the recommended minimum overlay thickness for the pavement design is 70 mm.

  4. CONCLUSION

Based on the evaluation results, the recommended treatment includes localized repairs such as crack rehabilitation, pothole patching, and rut correction due to wheel path deformation. Furthermore, to enhance the structural capacity of the existing pavement in accommodating the projected traffic loads as outlined in the design plan, the implementation of an overlay with a thickness of 70 mm is recommended.

ACKNOWLEDGMENT

The author would like to express sincere gratitude to the Public Works and Spatial Planning Agency of Kediri City for their invaluable support in providing data and information essential to the completion of this research. Deepest appreciation is also extended to the beloved family for their unwavering support and motivation throughout the research process. Furthermore, special thanks are given to the entire academic community of the Faculty of Engineering, Masters Program in Civil Engineering, University of 17 August 1945 Surabaya, for their collaboration, insightful discussions, and continuous support during the course of study.

REFERENCES

  1. Aptarila, G., Lubis, F. L., & Saleh, A. (2020). Analisis Kerusakan Jalan Metode SDI Taluk Kuantan – Batas Provinsi. SIKLUS, 6, 195203. https://doi.org/10.31849/siklus.v6i2.4647

  2. Chaniago, A., & Annur Ma, dan. (t.t.). ANALISA KERUSAKAN JALAN DENGAN METODE INTERNATIONAL ROUGHNESS

    INDEX (IRI) DAN SURFACE DISTRESS INDEX (SDI) PADA JALAN NASIONAL RUAS KOTA WLINGI-KABUPATEN

    MALANG KM 135+478 SAMPAI 139+478. Dalam Student Journal GELAGAR.

  3. Desei, F. L., Kadir, Y., & Ende, A. Z. (2023a). Evaluasi Kerusakan Jalan Menggunakan Metode Surface Distress Index dan International Roughness Index. Konstruksia, 15(1), 67.

    https://doi.org/10.24853/jk.15.1.67-77

  4. Dita Armah Zuria, Nur Azlinda Herawati, Putresa Eka Irmandini, Yani Septia Rachmawati, Putri Sefhiatul Rohma, Ida Faizahtun Nafiah, Marsianus Aparato, Goldensia Katarina Nay, Rheyna Putri Arditiya, Kurniatul Putri Mukhfidah, Anggraeni Retno Pangestu, & Suyono Suyono. (2024). Dampak Perbaikan Jalan Terhadap Peningkatan Ekonomi Masyarakat Di Desa Mergosari Kecamatan Tarik Kabupaten Sidoarjo. Guruku: Jurnal Pendidikan dan Sosial Humaniora, 2(4), 0107. https://doi.org/10.59061/guruku.v2i4.757

  5. Farida, I., & Hamid, M. Z. (2022). Efektivitas Aplikasi Smartphone Roadbump Pro dan Roadroid Dengan Nilai Kekasaran Jalan Pada Perkerasan Kaku. Teras Jurnal : Jurnal Teknik Sipil, 12(2), 405.

    https://doi.org/10.29103/tj.v12i2.737

  6. Febriani, F. (2022). Kajian Penilaian Kerusakan Jalan Dengan Metode Pavement Condition Index (PCI) dan Surface Distress Index (SDI) Dalam Rangka Penilaian Kondisi Jalan. Doctoral dissertation, Universitas Islam Riau.

  7. Fikri, M. (2016). ANALISIS TINGKAT KERUSAKAN JALAN LENTUR DENGAN METODE PAVEMENT CONDITION INDEX (PCI) STUDI KASUS RUAS JALAN POROS LAMASI- WALENRANG KABUPATEN LUWU.

  8. Godinho, D., Tjendani, H. T., & Wulandari, E. (2025). Enrichment: Journal of Multidisciplinary Research and Development Road Performance Analysis in Maliana District, Bobonaro Regency, Timor Leste. Dalam Enrichment: Journal of Multidisciplinary Research and Development (Vol. 2, Nomor 11).

  9. Hasrudin, L., & Maha indra. (2024). Analisis Penilaian Kondisi Perkerasan Jalan Dengan Metode PCI (Pavement Condition Index), SDI (Surface Distress Index) dan IRI (International Roughness Index).

    Syntax Idea, 6. https://doi.org/10.36418/syntax-idea.v3i6.1227

  10. La Hasrudin, I. M. (2024). Analisis PenilaianKondisi Perkerasan Jalan dengan Metode PCI, SDI, dan IRI. Syntax Idea, 6(6), 1247.

    https://doi.org/10.36418/syntax-idea.v3i6.1227

  11. Lars Forslöf, & Hans Jones. (2015). Roadroid: Continuous Road Condition Monitoring with Smart Phones. Journal of Civil Engineering and Architecture, 9(4). https://doi.org/10.17265/1934-7359/2015.04.012

  12. Minarti, E. (2014). Studi Evaluasi Kerusakan Jalan Yang Mengkombinasikan Nilai Surface Distress Index (SDI) Dengan Nilai International Roughness Index (IRI) Untukrn Menunjang Pengambilan Keputusanan (Studi Kasus : Jalan Nasional Ruas Calang – Teunom Km.150 S/D Km.157). Banda Aceh : Prog. Studi Magister Teknik Sipil.

  13. Ramadona, F., Yermadona, H., Dewi, S., Program, M., Sipil, S. T., Teknik, F., Sumatera Barat, U. M., & Program, D. (2023). ANALISIS KERUSAKAN JALAN RAYA PADA LAPIS PERMUKAAN DENGAN METODE PAVEMENT CONDITION INDEX (PCI) DAN METODE BINA MARGA (STUDI KASUS RUAS JALAN LANDAI

    SUNGAI DATA STA 0 + 000-STA 2 + 000). Ensiklopedia Research and Community Service Review, 2(2). http://jurnal.ensiklopediaku.org

  14. Rifai, M., Setyawan, A., Handayani, F. S., & Arun, A. D. (2023). Evaluation of functional and structural conditions on flexible pavements using pavement condition index (PCI) and international roughness index (IRI) methods. E3S Web of Conferences, 429.

    https://doi.org/10.1051/e3sconf/202342905011

  15. Sukirman, S. (2010). Tebal Struktur Perkerasan Lentur.

  16. Susantio, L. (2015). Pemilihan Metode Penilaian Kondisi Jalan yang Mendekati Perkiraan Kondisi Jalan Saat Pemeliharaan (Studi Kasus : Ruas Jalan Sadang Bts. Kota gresik STA Km.55+000 Km. 60+239).

  17. Syukri, M., Juandana, H., Kusdian, D., Garnida, H., & Pratiwi, A. A. R. (2024). Analysis of Pavement Conditions and Handling of Road Damage at the Surface Layer. IOP Conference Series: Earth and Environmental Science, 1321(1). https://doi.org/10.1088/1755- 1315/1321/1/012032