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Water quality monitoring is prone to encounter error on its recording or measuring process. The monitoring on river water quality not only aims to recognize the water quality dynamic, but also to evaluate the data to create river management policy and water pollution in order to maintain the continuity of human health or sanitation requirement, and biodiversity preservation. Evaluation on water quality monitoring needs to be started by identifying the important water quality parameter. This research objected to identify the significant parameters by using two transformation or standardization methods on water quality data, which are the river Water Quality Index, WQI ( Indeks Kualitas Air, Sungai , IKAs) transformation or standardization method and transformation or standardization method with mean 0 and variance 1; so that the variability of water quality parameters could be aggregated with one another. Both of the methods were applied on the water quality monitoring data which its validity and reliability have been tested. The PCA, Principal Component Analysis ( Analisa Komponen Utama , AKU), with the help of Scilab software, has been used to process the secondary data on water quality parameters of Gadjah Wong river in 2004-2013, with its validity and reliability has been tested. The Scilab result was cross examined with the result from the Excel-based Biplot Add In software. The research result showed that only 18 from total 35 water quality parameters that have passable data quality. The two transformation or standardization data methods gave different significant parameter type and amount result. On the transformation or standardization mean 0 variances 1, there were water quality significant parameter dynamic to mean concentration of each water quality parameters, which are TDS, SO4, EC, TSS, NO3N, COD, BOD5, Grease Oil and NH3N. On the river WQI transformation or standardization, the water quality significant parameter showed the level of Gadjah Wong River pollution, which are EC, DO, BOD5, COD, NH3N, Fecal Coliform, and Total Coliform. These seven parameters is the minimal amount of water quality parameters that has to be consistently measured on predetermined time and location, and also become the indicator of human health and environment health quality. The result of Scilab multivariate analysis was not different with the result from Biplot Add In multivariate analysis, in which the results of water quality significant parameter has been verified with bio-monitoring.

journal of the civil engineering forum

IDENTIFICATION OF WATER QUALITY SIGNIFICANT PARAMETER WITH TWO TRANSFORMATION/STANDARDIZATION METHODS ON PRINCIPAL COMPONENT ANALYSIS AND SCILAB SOFTWARE