Irrigation Performance Index Model (Case Study in IPDMIP)

Abstract

Each irrigation area has its own unique characteristics, depending on its geographical location, topography, population, climate, soil, and others. Based on government regulation, since 2015, all irrigation schemes in Indonesia have to be measured with the irrigation system performance index (IKSI or Indeks Kinerja Sistem Irigasi) every year. Several studies have been conducted since that year, but the IKSI model has not been evaluated yet, especially for surface irrigation. An increasing value of IKSI indicates an increase in the quality of irrigation system services. Conversely, the decreasing value of IKSI means that the efficiency and effectiveness of irrigation system management need further review and improvement. Therefore, this research aims to develop a mathematical model of the irrigation performance index as an evaluation using six parameters that examine the quality of irrigation system management. The research locations are in 947 Central Government Authorized Irrigation Areas, which was chosen considering that the irrigation performance index model had not been evaluated. The methodology consists of a SmartPLS (partial least square) application to analyze and narrow down the variables in this study, the analysis using the GRG (generalized reduced gradient) method to calculate nonlinear equations. In the initial equation, two variables, 12 dimensions, 24 indicators were analyzed. After analyzing the results using PLS-SEM, three indicators were eliminated so that the composition of the new equation became two variables, 12 dimensions, and 21 indicators that were interrelated with one another. Furthermore, GRG analysis using Microsoft Excel solver showed changes in variable weights so that the new model equation for IKSI-Bakti was 0.744 x primary irrigation network + 0.256 x tertiary irrigation network, which applies to the irrigation area of the Central Authority, especially for surface irrigation. Keywords : irrigation, partial least square, generalized reduced gradient, performance index. https://doi.org/10.55463/issn.1674-2974.50.4.1