Irrigation Asset Management Planning (Influence of the Five Pillars of Irrigation on Asset Management Planning) - Rahayu*, Noor Rakhmah; Poernomo, Ilham; Bhakty, Tania Edna; Andari, Eni (Riwayat: Educational Journal of History and Humanities, 2024)
Irrigation is very important in supporting sustainability food in the Dadapan area, Sleman Regency, but is hampered by budget limitations. Asset Management Planning (PMA) is needed to determine appropriate irrigation management budget priorities, according to regional characteristics. It is also important to know the influence of the five pillars of irrigation on Asset Management Planning. This research uses data on irrigation conditions and budget allocations for 2019-2022, maps of irrigation areas, maps of irrigation networks, both analog and digital, digital maps combined with related thematic maps on image maps or Google Earth with the Geographic Information System (GIS). Tabular data on network conditions was inventoried from 116 DI. Descriptive analysis method for regional characteristics and asset conditions, multiple regression for asset value using the Cost Replacement New (CRN) and Depreciated Replacement Cost (DRC) method and Partial Least Square analysis to determine the relationship between irrigation pillars with PMA. The results of the inventory of irrigation performance achievements in 2022 are 82%, but the irrigation network is good at less than 40%. Most were in a condition of light damage (58%) and some were moderately damaged (20%). PMA is appropriate in the Dadapan area by considering the priority scale according to the condition of asset damage and regional characteristics, interpreted using GIS, taking into account risk factors. The results of the 2023 CRN calculation are approximately 219% of the 2003 calculation. The most dominant variable influencing PMA is management with = 0.699 p = 0.000, then the condition of infrastructure with = 0.131 p = 0.031. The other variables are not significant. The R-square value is 471, which means that the variable that can be explained by the dependent variable PMA is 47.10% of the other constructs.