Hendrata Wibisana
Faculty of Engineering, Universitas Pembangunan Nasional "Veteran" East Java

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Analysis of Noise on Pantura Road Tripe – Shoot Comparation of Linear and Lagrange Methods Mohammad Hendrik Saputra Romadhon; Hendrata Wibisana
Journal of Management, Economic, and Financial Vol. 1 No. 2 (2023): Journal of Management, Economic and Financial
Publisher : Politeknik Siber Cerdika Internasional

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Abstract

The purpose of this study was to determine the correlation of noise level with traffic volume on the pantura route, especially in the Babat-Pucuk sub-district section using the mathematical method of linear regression and the polynomial lagrangge method. The results of this study, it can be known the correlation between noise and traffic volume on the Pantura route, especially the Babat - Pucuk District section, it was found that the highest traffic volume results in the 2-way segment of Babat - Gresik with a value of 3348.9 emp / hour, for the highest noise was in the 4-way segment of Babat - Gresik with a noise value of 87.8 dBA. The results of the study were processed using linear regression methods and lagrange polynomials, followed by a comparison of the results in the linear regression method = t stat value = 0.007474 < critical t = 2.262157 then H0 was accepted which means there is no significant difference between the insitu noise value (Y) and the results of linear regression calculations. p value = 0.9 > ? = 0.05 then H0 is accepted which means that there is no significant difference between the insitu noise value (Y) and the results of linear regression calculations. In the lagrange polynomial method = stat t value = 2.303102485 > critical t = 2.262157163 then Ha is accepted which means that there is a significant difference between the insitu noise value (Y) and the results of the lagrange polynomial calculation. p value = 0.046 < ? = 0.05 then Ha is accepted which means there is no significant difference between the insitu noise value (Y) and the results of the lagrange polynomial calculation. So it can be concluded that the linear regression method is more feasible to use because there is no significant difference between the noise value and the calculation results.