Performance Index Model of Main Structure (CASE STUDY IN IPDMIP)

Abstract

Purpose: This research intends to build a performance index model of main stucture by case study in IPDMIP. Theoretical reference: It is important to evaluate the percentage weights of 6 (six) variables in the Irrigation System Performance Index (ISPI) assessment so that irrigation managers get assessment results close to actual conditions in the field, improving the quality of irrigation system management. Method: The methodology or the main structure model in this study was analyzed by using SEM-PLS software and GRG analysis. The selection of a research location in the Central Authority Irrigation Area was by considering the same data availability as previous research. In this research, the author used the Smart-PLS (Partial Least Square) application to analyze and reduce variables, which were then analyzed again using the GRG (Generalized Reduced Gradient) method to calculate non-linear equations. Result and Conclusion: The result shows that in this equation, there is only 1 (one) variable, 3 (three) dimensions, and 13 (thirteen) indicators analyzed. After analyzing with SEM PLS, followed by GRG (Generalized Reduced Gradient) analysis with the solver in Microsoft Excel, changes in variable weights occur, so the new model equation for the main structure performance index (Y) is 0.348, with structure body dimensions of + 0.492 and door & gear to operate of +0.160. Mud Bags and drain doors apply to the Central Authority. Implication of research: Based on the results of previous research, where the assessment weight of the variable of the main irrigation network (with a weight of 0.744) is greater than the tertiary irrigation network (with a weight of 0.256). Originality/ value: the role of the main irrigation network is more dominant in channeling water from the intake to the tertiary irrigation network. However, previous research has not been completed since the main structure still has a level below it and has not been included in the scope of previous research.