Vol. 12 No. 4 (2026): In Progress
Open Access
Peer Reviewed

Analysis of Calibration and Validation of Road Roughness Survey Equipment (Hawkeye 2000) Based on SNI 3426:2022

Authors

Dody Kusmana , Ade Kurniawan , Ivany Sarief , Cecep Deni Mulyadi

DOI:

10.29303/jppipa.v12i4.14816

Published:

2026-04-25

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Abstract

Road roughness measurement using the International Roughness Index (IRI) plays a critical role in road asset management, influencing maintenance prioritization and budget allocation. However, discrepancies between instruments may introduce bias without proper calibration. This study aims to analyze the calibration and validation of the Hawkeye 2000 as a Digital Laser Profiler for IRI measurement based on SNI 3426:2022. Calibration was conducted using a Walking Profilometer as the reference instrument, followed by validation on five test segments (SP1–SP5) with lengths of 100–500 meters under three speed variations (40, 50, and 60 km/h). The results show that the Hawkeye 2000 meets the requirements of SNI 3426:2022, with coefficients of determination (R²) of 0.9819 (left), 0.9850 (right), and 0.9820 (combined), indicating high accuracy. The coefficient of variation (CV) ranges from 0.0159 to 0.0241 (<5%), reflecting high precision. Calibration parameters (A = 0.9956; B = −0.0093) are within acceptable limits. The instrument also demonstrates consistent performance across different speeds. In conclusion, the Hawkeye 2000 is reliable for field IRI measurement, although further studies are needed to consider broader road conditions and external factors.

Keywords:

Calibration Instrument validation International roughness index Measurement accuracy Measurement precision SNI 3426:2022

References

Amru, T., Nugroho, Y. A., Agustin, E. C., Fitri, L., & Hadi, S. (2025). Analisis tingkat kerataan jalan dengan metode international roughness index menggunakan hawkeye (studi kasus : Jl . Gajahmada Slawi). Wahana Aktivitas Dan Kreativitas Teknologi Unipasby (WAKTU), 23(01), 42–49. https://doi.org/10.36456/waktu.v23i1.9398

Andersson, A., Isaksson, J., Lennartsson, A., & Engström, F. (2024). Insights into the Valorization of Electric Arc Furnace Slags as Supplementary Cementitious Materials. Journal of Sustainable Metallurgy, 10(1), 96–109. https://doi.org/10.1007/s40831-023-00778-y

Baharufahmi. (2020). Kajian Kondisi Fungsional Dan Implementasi Perkerasan Lentur (Aspal) Antara Metode Pci Dan Bina Marga Pada Ruas Jalan Simpang Panam – Simpang Air Hitam-Simpang Gemar Menabung Kota Pekanbaru. Universitas Islam Riau. Retrieved from https://repository.uir.ac.id/17810/1/163121025.pdf

Budiharto, P., & Amanah, T. (2023). Ketidakrataan Jalan Laser Profilemeter Kelas I. Bearing Jurnal Penelitian Dan Kajian Teknik Sipil, 08(01), 18–26. https://doi.org/10.32502/jbearing.v8i1.6263

BSN. (2022). SNI 3426:2022 Cara survei ketidakrataan perkerasan jalan dengan alat tipe respons. Badan Standardisasi Nasional.

Karamihas, S. M., & Sayers, M. W. (2025). The Little Book of Profiling. The Regents of the University of Michigan.

Kurnia, R., & Nugraha, M. I. (2021). Validasi Nilai Ketidakrataan Jalan Menggunakan Aplikasi Android Road Bump Pro. Potensi: Jurnal Sipil Politeknik, 23(2), 102–111. https://doi.org/10.35313/potensi.v24i1.2589

Loprencipe, G., Zoccali, P., & Cantisani, G. (2019). applied sciences E ff ects of Vehicular Speed on the Assessment of Pavement Road Roughness. Applied Sciences (Switzerland), 9(1783), 1–18. https://doi.org/10.3390/app9091783

Lu, Y., Huang, Y., Xue, W., & Zhang, G. (2018). Seismic data processing method based on wavelet transform for de-noising. Cluster Computing. https://doi.org/10.1007/s10586-018-2355-0

Marga, D. J. B. (2021). Pedoman penyelenggaraan sistem manajemen aset jalan. Kementerian Pekerjaan Umum dan Perumahan Rakyat.

Mazzi, C., Carini, C., Meocci, M., Paliotto, A., & Marradi, A. (2025). Floating Car Data for Road Roughness : An Innovative Approach to Optimize Road Surface Monitoring and Maintenance. Future Transportation, 5(162), 1–27. https://doi.org/10.3390/futuretransp5040162

Meidasari, A. (2024). Rehabilitasi Perencanaan Irigasi Pasang Surut Rawa Pitu (Way Pidada – Way Tulang Bawang) Studi Kasus Saluran Primer 3. Universitas Lampung.

Nisumanti, S., & Prawinata, D. (2020). Penilaian Kondisi Jalan Menggunakan Metode International Roughness Index (IRI) Dan Surface Distress Index (SDI) Pada Ruas Jalan Akses Terminal Alang-Alang Lebar (Studi Kasus : Sp . Soekarno Hatta – Bts. Kota Palembang Km 13). Jurnal Tekno Global, 09(2), 57–62. Retrieved from https://ejournal.uigm.ac.id/index.php/TG/article/view/1302/1212

Nugroho, S. (2024). Validasi Penggunaan Laser Profilometer dalam Penentuan Kondisi Mantap Jalan Nasional. Jurnal Litbang Jalan, 41(1), 1–12.

Pembuain, A., Priyanto, S., & Suparma, L. B. (2018). Evaluasi Kemantapan Permukaan Jalan Berdasarkan International Roughness Index Pada 14 Ruas Jalan di Kota Yogyakarta. Teknik, 39(2), 126–131. https://doi.org/10.14710/teknik.v39n2.21459

Putri, Z. S., Berlianindya, F., Ramadhan, T., Fahriza, D., & Hadi, S. (2025). Analisis Kondisi Jalan Berdasarkan Nilai Iri (International Rougness Index) (Studi Kasus : JL IR H Juanda – JL Anoa Kabupaten Tegal). Jurnal Teknik Sipil Dan Arsitektur, 30(1), 1–8. Retrieved from https://garuda.kemdiktisaintek.go.id/documents/detail/4842352

Rahmansyah, D. (2021). Pengaruh Kecepatan Kendaraan Terhadap Akurasi Pengukuran IRI pada Alat Tipe Respons. Jurnal Jalan Dan Jembatan, 38(2), 112–125.

Sayers, M. W., Gillespie, T. D., & Paterson, W. D. (1986). Guidelines for Conducting and Calibrating Road Roughness Measurements. Work BAnk.

Setiawan, A. (2022). Analisis Perbandingan Hasil Pengukuran IRI Menggunakan Alat Roughometer III dan Dipstick. Jurnal Infrastruktur, 8(1), 45-53, 8(1), 45–53.

Surbakti, S., & Samsuri. (2023). A Study on the Road Conditions Assessment Obtained from International Roughness Index (IRI): Roughometer Vs Hawkeye. Pena Teknik: Jurnal Ilmiah Ilmu-Ilmu Teknik, 14(2), 88–96. https://doi.org/10.32734/jet.v1i2.756

Xu, S., Liu, Q., Bo, Y., Chen, Z., & Wang, C. (2024). Estimating the International Roughness Index of asphalt pavement using a low-cost portable system. Construction and Building Materials, 411(134301). https://doi.org/10.1016/j.conbuildmat.2024.136659

Yang, M., Yan, Z., & Li, Z. (2025). Cement and Concrete Research Revealing the tricalcium silicate formation behaviors in modified EAF slag at high temperatures for the production of electric recycled cement. Cement and Concrete Research, 189(August), 107756. https://doi.org/10.1016/j.cemconres.2024.107756

Yen, K. S., Lasky, T. A., & Ravani, B. (2014). Cost-Benefit Analysis of Mobile Terrestrial Laser Scanning Applications for Highway Infrastructure. Journal of Infrastructure Sys- Tems, 20. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000192.

Zhang, Z., Zhang, H., Xu, S., & Lv, W. (2021). Pavement roughness evaluation method based on the theoretical relationship between acceleration measured by smartphone and IRI. International Journal of Pavement Engineering, 1–17. https://doi.org/10.1080/10298436.2021.1881783

Author Biographies

Dody Kusmana, Sangga Buana YPKP University

Author Origin : Indonesia

Ade Kurniawan, Sangga Buana YPKP University

Author Origin : Indonesia

Ivany Sarief, Sangga Buana YPKP University

Author Origin : Indonesia

Cecep Deni Mulyadi, Sangga Buana YPKP University

Author Origin : Indonesia

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How to Cite

Kusmana, D., Kurniawan, A., Sarief, I., & Mulyadi, C. D. (2026). Analysis of Calibration and Validation of Road Roughness Survey Equipment (Hawkeye 2000) Based on SNI 3426:2022. Jurnal Penelitian Pendidikan IPA, 12(4), 619–625. https://doi.org/10.29303/jppipa.v12i4.14816