Abstract
The diversity of activities along the Brantas watershed causes waste disposal, which contributes to an increase in pollution load in the Brantas watershed and a decrease in water quality. It is necessary to periodically monitor water quality changes, but the constraints faced are the high cost of sample testing. The solution that can be done is to predict changes in water quality through the neighborhood method to reduce the number of samples. The purpose of this study is to predict the water quality conditions spatially by using the Inverse Distance Weighted (IDW) method, especially in the watershed area of ??Batu Upper Brantas and find out the differences in the spread of pollution water in the conditions of the rainy and dry season, as the last output is to determine the water purification zone. The IDW method is able to visualize the spread of water pollution with distance-based interpolation calculations, where the advantages of IDW compared to other methods are that the calculations are at the minimum limit and the maximum limit of input values. The results obtained from this study were from 13 sampling points obtained 1 point experienced an increase in pollution status in the rainy season to dry season, namely from weight to moderate, 1 sample point that experienced changes in pollution status from mild to moderate, 7 points experienced a change in status from moderate to severe and 4 sample points experiencing changes in status from mild to severe. Branats River degradation zone upstream of Batu City at a distance of 2 km has experienced a decrease in DO during the rainy and dry season, the decomposition zone of Sunga Upper Brantas in Batu City is at a distance of 3 km to 6 km in the rainy season, and at a distance of 3-4 km dry season conditions , rehabilitation zone in the Brantas River in the Upper Batu City at a distance of 7 km to 8 km in the rainy season and at a distance of 5-11 km during the dry season and a re-purification zone, there was no purification zone at a distance of 11 km along the Brantas River in the Upper Batu City.
 
 Keywords : distribution, prediction, purification zone, water pollution
Highlights
Kota Batu merupakan salah satu lokasi hulu DAS Brantas dan berada pada sub DAS Ambang
which contributes to an increase in pollution load
the constraints faced are the high cost of sample testing
Summary
Kota Batu merupakan salah satu lokasi hulu DAS Brantas dan berada pada sub DAS Ambang. 13 titik pengambilan sampel ditentukan dengan alasan 50% dari jumlah pengambilan sampel awal yang merepresentasikan kualitas air sungai Brantas Kota Batu (Bambang Rahadi dkk, 2015). Upaya monitoring dan evaluasi dapat dilakukan melalui pengambilan sampel air secara berkala dan menyeluruh untuk mendapatkan informasi perubahan kualitas air di tiga bagian DAS. Proses merealisasikan monitoring dan evaluasi masih menemui kendala yaitu besarnya biaya yang dibutuhkan untuk pengambilan sampel dan uji sampel laboratorium mengingat luasnya catchment area pada satu DAS. Salah satu metode prediksi yang dapat digunakan adalah Neighborhood yang mana metode ini menghasilkan data spasial baru yang berbentuk polygon atau area dengan jarak tertentu dari data spasial yang menjadi masukannya. Opsi power dan jumlah sampel tidak memberikan perubahan yang signifikan pada hasil interpolasi
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