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Analisis Prioritas Pembangunan Embung Metode Cluster Analysis, AHP dan Weighted Average (Studi Kasus: Embung di Kabupaten Semarang)

*Bima Anjasmoro  -  Bidang Sumber Daya Air, Indonesia
Suharyanto Suharyanto  -  Jurusan Teknik Sipil, Fakultas Teknik, Universitas Diponegoro, Indonesia
Sri Sangkawati  -  Jurusan Teknik Sipil, Fakultas Teknik, Universitas Diponegoro

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Abstract
The Feasibility study potential of small dams in Semarang District has identified 8 (eight) urgent potential small dams. These potential dams here to be constructed within 5 (five) years in order to overcome the problem of water shortage in the district. However, the government has limited funding source. It is necessary to select the more urgent small dams to be constructed within the limited budget. The purpose of the research is determining the priority of small dams construction in Semarang District. The method used to determine the priority in this study is cluster analysis, AHP and weighted average method. The criteria used to determine the priority in this study consist of: vegetation in the inundated area, volume of embankment, land acquisition area, useful storage, recervoir life time, water cost/m³, access road to the dam site, land status at abutment and inundated area, construction cost, operation and maintenance cost, irrigation service area and raw water benefit. Based on results of cluster analysis, AHP and weighted average method can be conclude that the priority of small dams construction is 1) Mluweh Small Dam (0.165), 2) Pakis Small Dam (0.142), 3) Lebak Small Dam (0.134), 4) Dadapayam Small Dam (0.128), 5) Gogodalem Small Dam (0.119), 6) Kandangan Small Dam (0.114), 7) Ngrawan Small Dam (0.102) and 8) Jatikurung Small Dam (0.096). Based on analysis of the order of priority of 3 (three) method showed that method is more detail than cluster analysis method and weighted average method, because the result of AHP method is closer to the conditions of each dam in the field.
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Keywords: AHP, Cluster analysis, Priority dam, Weighted average.

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