ANALISIS PERBANDINGAN METODE REGRESI LINIER DAN NON-LINIER PADA SAMBUNGAN MATERIAL PELAT BAJA KARBON ASTM A36

Authors

  • Zefri Azharman Universitas Universal
  • Adi Nugroho Universitas Universal
  • Suharlina Suharlina Universitas Universal
  • Delia Meldra Universitas Ibnu Sina

DOI:

https://doi.org/10.33884/jrsi.v10i2.9967

Keywords:

Linear Regression, Carbon Steel ASTM A36 Plate, Non-Linear Regression (Quadratic)

Abstract

The joining of ASTM A36 carbon steel plates using the Shield Metal Arc Welding (SMAW) technique is influenced by the tensile strength and hardness of the joint. To improve the quality of ASTM A36 carbon steel plate joints in the future, prediction methods are used. The prediction results play a significant role in determining the quality of the material connection.The method used in this research was descriptive quantitative, by predicting linear regression and non-linear (quadratic) regression models. The purpose of the discussion in this article was to determine the best prediction model for current variations on the tensile strength of future material connections. The analysis of the correlation coefficient showed a strong relationship in both models discussed. This indicates that the current strength variable had a strong relationship with tensile strength. Meanwhile, the highest R-square score was obtained in the non-linear regression model. The determination of the best prediction method was found in the non-linear regression model on tensile strength, with a MAPE value of 3.57%. These results indicate that the non-linear regression model better describes the relationship between current strength and tensile strength in ASTM A 36 carbon steel plate joining.

References

Ainiyah, N., Deliar, A., & Virtriana, R. (2016). THE CLASSICAL ASSUMPTION TEST TO DRIVING FACTORS OF LAND COVER CHANGE IN THE DEVELOPMENT REGION OF NORTHERN PART OF WEST JAVA. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B6, 205–210. https://doi.org/10.5194/isprs-archives-XLI-B6-205-2016

Alfarisi, S., Astuti, R., & M Basysyar, F. (2024). IMPLEMENTASI DATA MINNING MENGGUNAKAN ALGORITMA REGRESI LINEAR UNTUK PREDIKSI PENJUALAN DAN CASHFLOW DI AYAM GEPREK CAP CANGKIR. JATI (Jurnal Mahasiswa Teknik Informatika), 8(3), 3392–3395. https://doi.org/10.36040/jati.v8i3.9717

Bakhori, A. (2017). PERBAIKAN METODE PENGELASAN SMAW (SHIELD METAL ARC WELDING) PADA INDUSTRI KECIL DI KOTA MEDAN. Buletin Utama Teknik, 13(1), 14–21. https://doi.org/https://doi.org/10.30743/but.v13i1.255

Bhardwaj, S., & Chandima Ratnayake, R. M. (2021). Residual stress estimation in defect assessment procedures at weld toe and away locations on girth welds: Review of key parameters. Theoretical and Applied Fracture Mechanics, 111, 102848. https://doi.org/10.1016/j.tafmec.2020.102848

Chicco, D., Warrens, M. J., & Jurman, G. (2021). The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. PeerJ Computer Science, 7, e623. https://doi.org/10.7717/peerj-cs.623

Djatmiko, R. D., Kurniawan, D. A., & Pratiwi, H. (2020). Visual inspection on shielded metal arc welding products of Asian welding contestants in Yogyakarta province. Journal of Physics: Conference Series, 1446(1), 012006. https://doi.org/10.1088/1742-6596/1446/1/012006

Gunawan, E., Choifin, M., Khoirul Rosidin, M., Nur Afifah, Y., Lestariningsih, W., Sungging Pradana, M., Adhi Prasnowo, M., & Makki, A. (2019). Analysis of the Effect of Current Flow Variations in GTAW on SS 400 Plate Material Connected with SUS 304 Stainless Steel Plate Against Tensile Strength and Hardness with ER308L Electrodes. Journal of Physics: Conference Series, 1175, 012277. https://doi.org/10.1088/1742-6596/1175/1/012277

Hamid, A. (2016). ANALISA PENGARUH ARUS PENGELASAN SMAW PADA MATERIAL BAJA KARBON RENDAH TERHADAP KEKUATAN MATERIAL HASIL SAMBUNGAN. Jurnal Teknologi Elektro, 7(1). https://doi.org/10.22441/jte.v7i1.813

Hidayat, M., Febnesia, H., & Ramdani, S. (2021). Effect of DCRP and DCSP Polarity on SMAW Welding on the Depth of Penetration with E7018 Electrodes using Low Carbon Steel ASTM A36. Journal of Mechanical Engineering Science and Technology, 5(1), 36–46. https://doi.org/10.17977/um016v5i12021p037

Kusuma, M. D. H., & Hidayat, S. (2024). Penerapan Model Regresi Linier dalam Prediksi Harga Mobil Bekas di India dan Visualisasi dengan Menggunakan Power BI. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 5(2), 1097–1110. https://doi.org/10.35870/jimik.v5i2.629

Nabillah, I., & Ranggadara, I. (2020). Mean Absolute Percentage Error untuk Evaluasi Hasil Prediksi Komoditas Laut. JOINS (Journal of Information System), 5(2), 250–255. https://doi.org/10.33633/joins.v5i2.3900

Nazaré, G., Castro, R., & Gabriel Filho, L. R. A. (2020). Wind power forecast using neural networks: Tuning with optimization techniques and error analysis. Wind Energy, 23(3), 810–824. https://doi.org/10.1002/we.2460

Ntumi, S., & Effrim, P. K. (2022). Beyond Standardized Regression Coefficients Beta Weights: Interpreting and Applying Multiple Linear Regression in Educational Research. Al-Hikmah Journal of Arts & Social Sciences Education, 4(2), 8–15.

Nugroho, A., & Setiawan, E. (2018). Pengaruh Variasi Kuat Arus Pengelasan Terhadap Kekuatan Tarik Dan Kekerasan Sambungan Las Plate Carbon Steel ASTM 36. Jurnal Rekayasa Sistem Industri, 3(2), 134–142.

Nurani, A. T., Setiawan, A., & Susanto, B. (2023). Perbandingan Kinerja Regresi Decision Tree dan Regresi Linear Berganda untuk Prediksi BMI pada Dataset Asthma. Jurnal Sains Dan Edukasi Sains, 6(1), 34–43. https://doi.org/10.24246/juses.v6i1p34-43

Nurfadhilah, A. N., Budi, W., Kurniati, E., & Suhaedi, D. (2022). Penerapan Metode Moving Average untuk Prediksi Indeks Harga Konsumen. Matematika: Jurnal Teori Dan Terapan Matematika, 21(1), 19–26.

Pratomo, M. A., Jasman, J., Erizon, N., & Fernanda, Y. (2020). The Variation Effect of Electric Current Toward Tensile Strength on Low Carbon Steel Welding with Electrode E7018. Teknomekanik, 3(1), 9–16. https://doi.org/10.24036/tm.v3i1.5572

Roy, S. S., Samui, P., Nagtode, I., Jain, H., Shivaramakrishnan, V., & Mohammadi-ivatloo, B. (2020). Forecasting heating and cooling loads of buildings: a comparative performance analysis. Journal of Ambient Intelligence and Humanized Computing, 11(3), 1253–1264. https://doi.org/10.1007/s12652-019-01317-y

Shrestha, N. (2020). Detecting Multicollinearity in Regression Analysis. American Journal of Applied Mathematics and Statistics, 8(2), 39–42. https://doi.org/10.12691/ajams-8-2-1

Tanujaya, C. (2017). Perancangan Standart Operational Procedure Produksi Pada Perusahaan Coffeein. Jurnal Performa: Jurnal Manajemen Dan Start-up Bisnis, 2(1), 90–95. https://doi.org/https://doi.org/10.37715/jp.v2i1.441

Utami, G. F., Suhaedi, D., & Kurniati, E. (2021). Perbandingan metode regresi linier dan non-linier kuadratik pada peramalan penjualan air minum. Matematika: Jurnal Teori Dan Terapan Matematika, 20(2), 33–41.

Wang, D. Q. Q., Yao, D. D., Gao, Z. B., Wang, Q., Zhang, Z. F., & Li, X. W. (2021). Fatigue mechanism of medium-carbon steel welded joint: Competitive impacts of various defects. International Journal of Fatigue, 151, 106363. https://doi.org/10.1016/j.ijfatigue.2021.106363

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Published

2025-05-22

Issue

Vol. 10 No. 2 (2025): Mei 2025

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