Proceeding of the Electrical Engineering Computer Science and Informatics Vol. 7, October 2020 ISSN: 2407-439X 98 Implementation of Linear and Lagrange Interpolation on Compression of Fibrous Peat Soil Prediction Badar Said Informatics Engineering Study Program University of Madura Pamekasan, Indonesia badarsaid@unira.ac.id Faisal Estu Yulianto Civil Engineering Study Program University of Madura Pamekasan, Indonesia faisal_ey@yahoo.co.id Abstract—Previous studies have predicted the compression of fibrous peat soils using the Gibson & Lo method. But the prediction process is still done manually so it requires quite a long time. Therefore this research implements linear and Lagrange interpolation methods using Matlab software to speed up the prediction process. This study also carried out a comparison of the results of the implementation of the two methods to determine its effectiveness in making predictions. Based on the results of trials and analysis, it can be seen that the prediction of compression of fibrous peat soil using linear interpolation is more effective than using Lagrange interpolation, this can be proven by the smaller average RMSE prediction results using linear interpolation, with a difference in the average value of RMSE 7.7. Besides, prediction testing using Lagrange interpolation requires longer time, because it still does the iteration process as much as laboratory test data. Keywords—prediction, peat soil, interpolation, linear, lagrange I. PRELIMINARY Peat soil is a type of soil that forms in areas with low climate change rates, usually in lowland areas and swamps. This type of soil is formed due to the accumulation of plant residues that are always moist due to waterlogging and poor oxygen circulation. Resulting in the process of humification by bacteria does not run perfectly, as a result, some plant fibers are still clearly visible and greatly affect the behavior of this soil type [1]. Peatland based on fiber content is divided into 2 types, namely fibrous peat with fiber content> 20% and non- fibrous peat with fiber content <20%. The compression behavior of fibrous peat is very different from that of non- fibrous peat, this is because fibrous peat has 2 pores, namely the macropore which lies between the peat fiber and the micropore which is inside the peat fiber [2]. Previous research has predicted the compression of fibrous peat soils that have decreased water levels in the Bareng Bengkel village, Palangkaraya, Central Kalimantan using the Gibson & Lo method. But the prediction process is still done manually so it requires a long time which is 14 days. therefore in this study, the implementation of linear and Lagrange interpolation methods is implemented in software to speed up the prediction process. Linear interpolation is indeed very different when compared to Lagrange interpolation, but both have their advantages and disadvantages [3]. So in this study, a comparison of the results of the implementation of the two methods was carried out to determine its effectiveness in predicting the compression of Palangkaraya fibrous peat soil. II. LITERATURE REVIEW A. Linear Interpolation The easiest form of interpolation is to determine the value between two known values based on a linear equation [4], [5]. Linear equations are also called straight-line equations because if the results of linear equations are drawn on a graph, then the shape of the curve is a straight line [6]. Linear interpolation is based on comparative theory as shown in the following figure. Fig. 1. Curve linear equation. A comparison of distance (X - X1) with distance (X2 - X1) is the same as the comparison of distance (Y - Y1) with distance (Y2 - Y1) [7], [8]. So that each point between two points is known to have a linear relationship, and can be determined by calculation using the following linear interpolation equation: (− 1 ) ( 2 − 1 ) = (− 1 ) ( 2 − 1 )  = (− 1 )( 2 − 1 ) ( 2 − 1 ) + 1  B. Lagrange Interpolation Some cases in practice require guessing the value of an unknown value for various pieces of information. The process of guessing the value is interpolation and extrapolation. There are many methods used to guess interpolation, one of them among these is the Lagrange polynomial method [9], [10].