Open AccessFactors Affecting Dissolved Oxygen at Bengawan Solo River: A Spatial Filtering with Eigenvector Technique
Author(s) -
Evellin Dewi Lusiana,
Arief Darmawan,
Sarah Hutahaean,
Muhammad Musa,
Mohammad Mahmudi,
Sulastri Arsad
Publication year - 2021
Publication title -
jurnal varian
Language(s) - English
Resource type - Journals
ISSN - 2581-2017
DOI - 10.30812/varian.v5i1.1407
Subject(s) - spatial analysis , autocorrelation , linear regression , heteroscedasticity , statistics , sampling (signal processing) , eigenvalues and eigenvectors , mathematics , regression analysis , control variable , environmental science , residual , hydrology (agriculture) , computer science , filter (signal processing) , algorithm , geology , physics , geotechnical engineering , quantum mechanics , computer vision
The quality of the river changes according to the development of the surrounding environment which is influenced by various human activities. Analysis of factors affecting Dissolved Oxygen (DO) at Bengawan Solo River is crucial for river management purpose and pollution control. Previous research suggested the use classic multiple linear regression. However, DO measurement were usually took place of sampling sites along the river channel. Therefore, there is a high chance that the measurements results may spatially correlated. As the consequence, the utilization of multiple linear regression technique for the dataset can be inappropriate. In this paper, we applied a modification of multiple linear regression model to incorporate with spatial autocorrelation that exist in the data by adding control variable such vector eigen to the model which known as Spatial Filtering with Eigenvector (SFE). The results showed that nitrate and nitrite were the predictor variables that have a negative and significant effect. However, the model contains spatial autocorrelation. The application of SFE technique by adding three eigenvectors as control variables in the model succeeded in making the residual model free from spatial autocorrelation. However, a new problem arose where there was a violation of the non-heteroscedasticity assumption.