Uji Efektivitas Penyaringan Air Multi Media Dalam Penurunan Kadar Besi (Fe) Dan Mangan (Mn) Pada Air Sumur Bor
Abstract
The content of Iron (Fe) and Manganese (Mn) in water causes water to interfere with health and cause disease, so the use of multimedia filters with walnut shell charcoal, black sand, palm fiber and gravel is expected to reduce Iron and Manganese levels as part of improving water quality clean and drinking water. This type of research is Experimental Research (applied research) with "One group Pretest - Posttest". Research variables: The dependent variable is the levels of Iron (Fe) and Manganese (Mn) in the borehole water and Independent, namely the multimedia filter 1st filter with media arrangement (gravel, palm fiber, black sand, walnut shell charcoal, palm fiber and gravel) and 2nd filter array. media (gravel, palm fiber, walnut shell charcoal, black sand, palm fiber and gravel) with various flow systems. With the aim of research to determine the effectiveness of using a multimedia filter consisting of gravel, palm fiber, black sand, walnut shell charcoal. The results of the study were screening 1 with media composition (gravel, palm fiber, black sand-walnut shell charcoal) and screening 2 with media composition (gravel, palm fiber, walnut shell charcoal-black sand) effectively reduced levels of iron (Fe) and manganese (Mn). dug well water. The mean of screening for Fe content in filter 1 was 4.681 to 0.029, the Fe content in filter 2 was 4.312 to 0.016, the Manganese (Mn) content in filter 1 was from 1.606 to 0.014 and in filter 2 was 1.165 to 0.029. Conclusion of multimedia sieves with the arrangement (gravel, palm fiber, black sand-walnut shell charcoal Fe on sieve 1 value p=0.00 < α=0.05, Mn sieve 1 p value=0.00 < α=0.05 and arrangement media (gravel, palm fiber, walnut shell charcoal- black sand) sieve 2 Fe p=0.00 < α=0.05, Mn sieve 2 p=0.00 < α=0.05 Significance value of the t test shows that Ho is rejected, meaning that there is a significant influence between the independent variables on the dependent variable
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