EID Al-Fitr Homecoming Traffic Prediction to Anticipate Continuity on the Jakarta-Cikampek Toll Road

https://doi.org/10.35912/ijfam.v7i3.2876
Published: Jan 29, 2026

Abstract:

Purpose: This study focuses on homecoming traffic flow prediction for sustainable anticipation to overcome the surge in traffic flow on the Jakarta-Cikampek Toll Road. This study aims to identify traffic patterns based on historical data, develop a time-series prediction model (ARIMA), and evaluate congestion levels using the Volume Capacity Ratio (VCR). The main issue is the high traffic flow during homecoming, which requires predictive and proactive approaches. This study uses concepts and theories such as traffic management, traffic flow characteristics, and time series prediction models (ARIMA and decomposition). This quantitative study analyzed historical data from Jasa Marga (2019–2024).

Research Methodology: This quantitative study analyzed historical data from Jasa Marga (2019–2024). Analytical techniques included in this study, such as stationarity tests, ARIMA parameter identification, and VCR calculations, were used to assess congestion.

Results: The results indicate that peak homecoming traffic occurs from H-5 to H-1, whereas returning traffic peaks from H+2 to H+5. The SARIMA (1,1,2) (2,1,2)²² model was more accurate in capturing seasonal patterns than the decomposition model. The VCR indicator is more than 1.0 during peak days, which indicates a congested road. These findings support traffic management strategies, such as contraflow and one-way systems. In conclusion, historical data-based prediction models can be used to effectively anticipate future traffic congestion.

Conclusions: Historical data models can effectively anticipate congestion and support contraflows in urban traffic.

Limitations: Stakeholders must enhance their data, infrastructure, awareness, and sustainable transportation.

Contributions: This study used the Jakarta–Cikampek Toll Road for the results.

Keywords:
1. ARIMA
2. Jakarta-Cikampek Toll Road
3. SARIMA
4. Traffic Engineering
5. VCR
Authors:
1 . Ayu Dwi Rahmawati
Indonesian National Police Traffic Corps, Jakarta, Indonesia
2 . Saut Panggabean Sinaga
Police Science College (STIK – PTIK), Jakarta, Indonesia
3 . Novi Indah Earlyanti
Police Science College (STIK – PTIK), Jakarta, Indonesia
View PDF
How to Cite
Rahmawati, A. D., Sinaga, S. P. ., & Earlyanti, N. I. . (2026). EID Al-Fitr Homecoming Traffic Prediction to Anticipate Continuity on the Jakarta-Cikampek Toll Road. International Journal of Financial, Accounting, and Management, 7(3), 539–557. https://doi.org/10.35912/ijfam.v7i3.2876
Download Citation
  1. Endnote/Zotero/Mendeley (RIS)
  2. BibTeX

Downloads

Download data is not yet available.
Issue & Section
Vol. 7 No. 3 (2025): December
Articles
Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

References

    Alghamdi, T., Elgazzar, K., Bayoumi, M., Sharaf, T., & Shah, S. (2019). Forecasting Traffic Congestion Using ARIMA Modeling.

    Alkatiri, R., Mokodompit, N. E., & Paramata, S. H. (2025). Pelatihan Pembuatan Tepung Pisang di Desa Bongo III, Kecamatan Wonosari, Kabupaten Boalemo. Jurnal Pemberdayaan Ekonomi, 4(2), 85-92. doi:https://doi.org/10.35912/jpe.v4i1.4881

    Annisa Khoiri, H. (2023). Analisis Deret Waktu Univariat: UNIPMA PRESS.

    Baderan, U. S., Lantowa, F. D., Makur, D. S., & Idji, A. (2025). Manajemen Administrasi dan Keuangan di Desa Bajo, Kecamatan Tilamuta, Kabupaten Boalemo. Jurnal Pemberdayaan Ekonomi, 4(2), 69-75. doi:https://doi.org/10.35912/jpe.v4i1.4828

    Chen, Y., Wang, W., Hua, X., & Zhao, D. (2022). Survey of Decomposition-Reconstruction-Based Hybrid Approaches for Short-Term Traffic State Forecasting. Sensors (Basel), 22(14). doi:https://doi.org/10.3390/s22145263

    Cryer, J. D., & Chan, K.-S. (2008). Time series analysis: with applications in R: Springer.

    Empat Pilar Transformasi, J. P. y. P. (2022). Retrieved from https://www.tempo.co/info-tempo/empat-pilar-transformasi-jantung-polri-yang-presisi-316795

    Evanita, E., Noersasongko, E., & Pramunendar, R. A. (2016). Prediksi Volume Lalu Lintas Angkutan Lebaran Pada Wilayah Jawa Tengah Dengan Metode K-Means Clustering Untuk Adaptive Neuro Fuzzy Inference System (Anfis). Simetris J. Tek. Mesin, Elektro dan Ilmu Komput, 7(1), 199-208. doi:https://doi.org/10.24176/simet.v7i1.505

    Febrianaa, F., Salima, Y., & Darwisa, H. (2022). Implementasi Analisis Volume Capacity Ratio Untuk Memprediksi Kepadatan Lalu Lintas Di Kota Makassar. Buletin Sistem Informasi dan Teknologi Islam ISSN, 2721, 0901. doi:https://doi.org/10.33096/busiti.v3i3.864

    Fuad, M. (2011). Makna hidup di bauk tradisi mudik lebaran (studi fenomenologi atas pengalaman pemudik dalam merayakan Idul Fitri di kampung halaman). KOMUNIKA: Jurnal Dakwah Dan Komunikasi, 5(1), 107-123. doi:https://doi.org/10.24090/komunika.v5i1.774

    Hamidah, S. N., Salam, N., & Susanti, D. S. (2017). Teknik Peramalan Menggunakan Metode Pemulusan Eksponensial Holt-Winters. EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS), 7(2), 26-33. doi:https://doi.org/10.20527/epsilon.v7i2.97

    Harahap, E., Wijekoon, J., Purnamasari, P., Darmawan, D., Ceha, R., & Nishi, H. (2018). Improving Road Traffic Management by A Model-Based Simulation.

    Hendrawan, H. (2020). Preferensi Perubahan Rute terhadap Informasi Kondisi Rute Mudik. MEDIA KOMUNIKASI TEKNIK SIPIL, 26, 17-25. doi:https://doi.org/10.14710/mkts.v26i1.25987

    Ita Yulianto, V. (2019). Is the Past Another Country? A Case Study of RuralUrban Affinity on Mudik Lebaran in Central Java. Journal of Indonesian Social Sciences and Humanities, 4, 49-66. doi:https://doi.org/10.14203/jissh.v4i0.118

    Japarudin, J. (2023). Fenomena dan nilai-nilai tradisi mudik lebaran. Al Qalam: Jurnal Ilmiah Keagamaan dan Kemasyarakatan, 17(3), 2034-2045. doi:http://dx.doi.org/10.35931/aq.v17i3.2202

    Kadarisman, M., Arubusman, D. A., & Kania, D. D. (2014). Manajemen Angkutan Lebaran Terpadu. Jurnal Manajemen Transportasi & Logistik (JMTRANSLOG), 1(2), 103-116. doi:https://doi.org/10.54324/j.mtl.v1i2.11

    Karimullah, S. S. (2021). Tinjauan antropologi hukum dan budaya terhadap mudik lebaran masyarakat Yogyakarta. Sosial Budaya, 18(1), 64-74. doi:http://dx.doi.org/10.24014/sb.v18i1.12725

    Khisty, C. J., . Dan B. Kent Lall. (2005). Basics - Basics of Transportation Engineering, 3rd Edition (Vol. 1). Jakarta: Erlangga Publishers.

    Khisty, C. J., & Lall, B. K. (2005). Dasar-dasar rekayasa transportasi. Jakarta: Erlangga, 1-23.

    Kumar, S. V., & Vanajakshi, L. (2015). Short-term traffic flow prediction using seasonal ARIMA model with limited input data. European Transport Research Review, 7(3), 21. doi:https://doi.org/10.1007/s12544-015-0170-8

    Liu, R., & Shin, S.-Y. (2025). A Review of Traffic Flow Prediction Methods in Intelligent Transportation System Construction. Applied Sciences, 15(7), 3866. doi:https://doi.org/10.3390/app15073866

    Machmud, J., Imbran, H., & Baderan, U. S. (2025). Pengembangan Kapasitas BUMDES di Desa Bongo III, Kecamatan Wonosari, Kabupaten Boalemo. Jurnal Pemberdayaan Ekonomi, 4(2), 77-84. doi:https://doi.org/10.35912/jpe.v4i1.4876

    Marta, J., Fauzi, A., Juanda, B., & Rustiadi, E. (2020). Understanding migration motives and its impact on household welfare: evidence from rural–urban migration in Indonesia. Regional Studies, Regional Science, 7, 118-132. doi:https://doi.org/10.1080/21681376.2020.1746194

    Muslih, M., Abduljabbar, A., & Joni, H. (2023). Review of traffic demand management strategies. IOP Conference Series: Earth and Environmental Science, 1232, 012055. doi:https://doi.org/10.1088/1755-1315/1232/1/012055

    Ogushi, F., Roy, C., & Kaski, K. (2025). Differences of communication activity and mobility patterns between urban and rural people. Journal of Computational Social Science, 8(2), 51. doi:https://doi.org/10.48550/arXiv.2311.13652

    Oktavio, A., & Indrianto, A. T. L. (2019). Social economic perspectives of homecoming tradition: An Indonesian context. KATHA-The Official Journal of the Centre for Civilisational Dialogue, 15(1), 46-65. doi:https://doi.org/10.22452/KATHA.vol15no1.3

    Putra, D. A., Indriani, R., Midiastuty, P. P., Suranta, E., & Rahmat, A. (2025). Model Edukasi Pajak UMKM: Studi Kasus Liquid Fotocopy Kota Bengkulu. Jurnal Pemberdayaan Ekonomi, 4(2), 43-55. doi:https://doi.org/10.35912/jpe.v4i2.4991

    Ramadhan, M. R., & Nugraha, J. (2023). Analisis Peramalan Jumlah Kedatangan Pesawat Internasional di Bandar Udara Soekarno-Hatta dengan Menggunakan Metode Dekomposisi-Arima: Analisis Peramalan Jumlah Kedatangan Pesawat Internasional di Bandar Udara Soekarno-Hatta. Emerging Statistics and Data Science Journal, 1(1), 159-169. doi:https://doi.org/10.20885/esds.vol1.iss.1.art17

    Rio, w. (2024). Perandirektorat Lalu Lintas (Ditlantas) Kepolisian Daerah (Polda) Jawa Tengah Patroli Jalan Raya (Pjr) Unit 6 Tegal Dalam Mekanisme Rekayasa Lalu Lintas. UPT. Perpustakaan Undaris.

    Risdiyanto. (2014). Engineering and Traffic Management: Theory and Applications.

    Sorokin, P. A. (1959). Social and cultural mobility. New York, 4, 99-145.

    Suryawan, R. F., Husainah, N., Latuconsina, A. S., Pahala, Y., & Sumardi, S. (2025). Sinergi Cuci Tradisional dan Modern untuk Pelestarian Budaya dan Usaha Lokal. Jurnal Pemberdayaan Ekonomi, 4(2), 57-68. doi:https://doi.org/10.35912/jpe.v4i1.4816

    Turner, J. H. (2013). The structure of sociological theory: Rawat publications.

    Wei, W. W. (2006). Time series analysis: univariate and multivariate. Methods. Boston, MA: Pearson Addison Wesley.

    Wibowo, A. R. (2017). Analisis data time series dan VCR kepadatan lalu lintas (studi kasus: Jalan Adisucipto depan Ambarukmo Plaza). Elinvo (Electronics, Informatics, and Vocational Education), 2(2), 130-137. doi:https://doi.org/10.21831/elinvo.v2i2.17838

    Wibowo, A. R., Soesanti, I., & Widyawan. (2018). Analisis Nilai VCR (Volume,Capacity, Ratio) untuk Bobot Dinamis dalam Analisis Rute Menggunakan Metode Dijkstra (Studi Kasus Jalan Godean KM 4,5). Jurnal Ilmiah Komputasi, 17(1), 1-10.

    Wibowo, M., & Widayanti, A. (2023). Analisis Kinerja Simpang Tak Bersinyal Pada Ruas Jalan Menur Pumpungan - Jalan Manyar Indah Raya - Jalan Manyar Tirtoyoso di Kota Surabaya Dengan Metode PKJI 2014. Jurnal Media Publikasi Terapan Transportasi, 279-290. doi:https://doi.org/10.26740/mitrans.v1n3.p279-290

  1. Alghamdi, T., Elgazzar, K., Bayoumi, M., Sharaf, T., & Shah, S. (2019). Forecasting Traffic Congestion Using ARIMA Modeling.
  2. Alkatiri, R., Mokodompit, N. E., & Paramata, S. H. (2025). Pelatihan Pembuatan Tepung Pisang di Desa Bongo III, Kecamatan Wonosari, Kabupaten Boalemo. Jurnal Pemberdayaan Ekonomi, 4(2), 85-92. doi:https://doi.org/10.35912/jpe.v4i1.4881
  3. Annisa Khoiri, H. (2023). Analisis Deret Waktu Univariat: UNIPMA PRESS.
  4. Baderan, U. S., Lantowa, F. D., Makur, D. S., & Idji, A. (2025). Manajemen Administrasi dan Keuangan di Desa Bajo, Kecamatan Tilamuta, Kabupaten Boalemo. Jurnal Pemberdayaan Ekonomi, 4(2), 69-75. doi:https://doi.org/10.35912/jpe.v4i1.4828
  5. Chen, Y., Wang, W., Hua, X., & Zhao, D. (2022). Survey of Decomposition-Reconstruction-Based Hybrid Approaches for Short-Term Traffic State Forecasting. Sensors (Basel), 22(14). doi:https://doi.org/10.3390/s22145263
  6. Cryer, J. D., & Chan, K.-S. (2008). Time series analysis: with applications in R: Springer.
  7. Empat Pilar Transformasi, J. P. y. P. (2022). Retrieved from https://www.tempo.co/info-tempo/empat-pilar-transformasi-jantung-polri-yang-presisi-316795
  8. Evanita, E., Noersasongko, E., & Pramunendar, R. A. (2016). Prediksi Volume Lalu Lintas Angkutan Lebaran Pada Wilayah Jawa Tengah Dengan Metode K-Means Clustering Untuk Adaptive Neuro Fuzzy Inference System (Anfis). Simetris J. Tek. Mesin, Elektro dan Ilmu Komput, 7(1), 199-208. doi:https://doi.org/10.24176/simet.v7i1.505
  9. Febrianaa, F., Salima, Y., & Darwisa, H. (2022). Implementasi Analisis Volume Capacity Ratio Untuk Memprediksi Kepadatan Lalu Lintas Di Kota Makassar. Buletin Sistem Informasi dan Teknologi Islam ISSN, 2721, 0901. doi:https://doi.org/10.33096/busiti.v3i3.864
  10. Fuad, M. (2011). Makna hidup di bauk tradisi mudik lebaran (studi fenomenologi atas pengalaman pemudik dalam merayakan Idul Fitri di kampung halaman). KOMUNIKA: Jurnal Dakwah Dan Komunikasi, 5(1), 107-123. doi:https://doi.org/10.24090/komunika.v5i1.774
  11. Hamidah, S. N., Salam, N., & Susanti, D. S. (2017). Teknik Peramalan Menggunakan Metode Pemulusan Eksponensial Holt-Winters. EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS), 7(2), 26-33. doi:https://doi.org/10.20527/epsilon.v7i2.97
  12. Harahap, E., Wijekoon, J., Purnamasari, P., Darmawan, D., Ceha, R., & Nishi, H. (2018). Improving Road Traffic Management by A Model-Based Simulation.
  13. Hendrawan, H. (2020). Preferensi Perubahan Rute terhadap Informasi Kondisi Rute Mudik. MEDIA KOMUNIKASI TEKNIK SIPIL, 26, 17-25. doi:https://doi.org/10.14710/mkts.v26i1.25987
  14. Ita Yulianto, V. (2019). Is the Past Another Country? A Case Study of RuralUrban Affinity on Mudik Lebaran in Central Java. Journal of Indonesian Social Sciences and Humanities, 4, 49-66. doi:https://doi.org/10.14203/jissh.v4i0.118
  15. Japarudin, J. (2023). Fenomena dan nilai-nilai tradisi mudik lebaran. Al Qalam: Jurnal Ilmiah Keagamaan dan Kemasyarakatan, 17(3), 2034-2045. doi:http://dx.doi.org/10.35931/aq.v17i3.2202
  16. Kadarisman, M., Arubusman, D. A., & Kania, D. D. (2014). Manajemen Angkutan Lebaran Terpadu. Jurnal Manajemen Transportasi & Logistik (JMTRANSLOG), 1(2), 103-116. doi:https://doi.org/10.54324/j.mtl.v1i2.11
  17. Karimullah, S. S. (2021). Tinjauan antropologi hukum dan budaya terhadap mudik lebaran masyarakat Yogyakarta. Sosial Budaya, 18(1), 64-74. doi:http://dx.doi.org/10.24014/sb.v18i1.12725
  18. Khisty, C. J., . Dan B. Kent Lall. (2005). Basics - Basics of Transportation Engineering, 3rd Edition (Vol. 1). Jakarta: Erlangga Publishers.
  19. Khisty, C. J., & Lall, B. K. (2005). Dasar-dasar rekayasa transportasi. Jakarta: Erlangga, 1-23.
  20. Kumar, S. V., & Vanajakshi, L. (2015). Short-term traffic flow prediction using seasonal ARIMA model with limited input data. European Transport Research Review, 7(3), 21. doi:https://doi.org/10.1007/s12544-015-0170-8
  21. Liu, R., & Shin, S.-Y. (2025). A Review of Traffic Flow Prediction Methods in Intelligent Transportation System Construction. Applied Sciences, 15(7), 3866. doi:https://doi.org/10.3390/app15073866
  22. Machmud, J., Imbran, H., & Baderan, U. S. (2025). Pengembangan Kapasitas BUMDES di Desa Bongo III, Kecamatan Wonosari, Kabupaten Boalemo. Jurnal Pemberdayaan Ekonomi, 4(2), 77-84. doi:https://doi.org/10.35912/jpe.v4i1.4876
  23. Marta, J., Fauzi, A., Juanda, B., & Rustiadi, E. (2020). Understanding migration motives and its impact on household welfare: evidence from rural–urban migration in Indonesia. Regional Studies, Regional Science, 7, 118-132. doi:https://doi.org/10.1080/21681376.2020.1746194
  24. Muslih, M., Abduljabbar, A., & Joni, H. (2023). Review of traffic demand management strategies. IOP Conference Series: Earth and Environmental Science, 1232, 012055. doi:https://doi.org/10.1088/1755-1315/1232/1/012055
  25. Ogushi, F., Roy, C., & Kaski, K. (2025). Differences of communication activity and mobility patterns between urban and rural people. Journal of Computational Social Science, 8(2), 51. doi:https://doi.org/10.48550/arXiv.2311.13652
  26. Oktavio, A., & Indrianto, A. T. L. (2019). Social economic perspectives of homecoming tradition: An Indonesian context. KATHA-The Official Journal of the Centre for Civilisational Dialogue, 15(1), 46-65. doi:https://doi.org/10.22452/KATHA.vol15no1.3
  27. Putra, D. A., Indriani, R., Midiastuty, P. P., Suranta, E., & Rahmat, A. (2025). Model Edukasi Pajak UMKM: Studi Kasus Liquid Fotocopy Kota Bengkulu. Jurnal Pemberdayaan Ekonomi, 4(2), 43-55. doi:https://doi.org/10.35912/jpe.v4i2.4991
  28. Ramadhan, M. R., & Nugraha, J. (2023). Analisis Peramalan Jumlah Kedatangan Pesawat Internasional di Bandar Udara Soekarno-Hatta dengan Menggunakan Metode Dekomposisi-Arima: Analisis Peramalan Jumlah Kedatangan Pesawat Internasional di Bandar Udara Soekarno-Hatta. Emerging Statistics and Data Science Journal, 1(1), 159-169. doi:https://doi.org/10.20885/esds.vol1.iss.1.art17
  29. Rio, w. (2024). Perandirektorat Lalu Lintas (Ditlantas) Kepolisian Daerah (Polda) Jawa Tengah Patroli Jalan Raya (Pjr) Unit 6 Tegal Dalam Mekanisme Rekayasa Lalu Lintas. UPT. Perpustakaan Undaris.
  30. Risdiyanto. (2014). Engineering and Traffic Management: Theory and Applications.
  31. Sorokin, P. A. (1959). Social and cultural mobility. New York, 4, 99-145.
  32. Suryawan, R. F., Husainah, N., Latuconsina, A. S., Pahala, Y., & Sumardi, S. (2025). Sinergi Cuci Tradisional dan Modern untuk Pelestarian Budaya dan Usaha Lokal. Jurnal Pemberdayaan Ekonomi, 4(2), 57-68. doi:https://doi.org/10.35912/jpe.v4i1.4816
  33. Turner, J. H. (2013). The structure of sociological theory: Rawat publications.
  34. Wei, W. W. (2006). Time series analysis: univariate and multivariate. Methods. Boston, MA: Pearson Addison Wesley.
  35. Wibowo, A. R. (2017). Analisis data time series dan VCR kepadatan lalu lintas (studi kasus: Jalan Adisucipto depan Ambarukmo Plaza). Elinvo (Electronics, Informatics, and Vocational Education), 2(2), 130-137. doi:https://doi.org/10.21831/elinvo.v2i2.17838
  36. Wibowo, A. R., Soesanti, I., & Widyawan. (2018). Analisis Nilai VCR (Volume,Capacity, Ratio) untuk Bobot Dinamis dalam Analisis Rute Menggunakan Metode Dijkstra (Studi Kasus Jalan Godean KM 4,5). Jurnal Ilmiah Komputasi, 17(1), 1-10.
  37. Wibowo, M., & Widayanti, A. (2023). Analisis Kinerja Simpang Tak Bersinyal Pada Ruas Jalan Menur Pumpungan - Jalan Manyar Indah Raya - Jalan Manyar Tirtoyoso di Kota Surabaya Dengan Metode PKJI 2014. Jurnal Media Publikasi Terapan Transportasi, 279-290. doi:https://doi.org/10.26740/mitrans.v1n3.p279-290