<![CDATA[Preparation for the modernization of the Kedung Putri Irrigation System (DI Kedung Putri) required a comprehensive assessment of the irrigation pillars, one of which was at the secondary level. To facilitate the assessment and development plan, a clustering was carried out using the k-medoids method, that used a representative data (called medoid) as the cluster center. Then, decision making was conducted by using the Analytic Hierarchy Process (AHP) method. The performance assessment of 21 secondary channels was stated as the readiness index of irrigation modernization (IKMI). The assessment result showed that 9.52% belonged to good criteria, 71.43% belonged to fair criteria, and 19.05% belonged to poor criteria. Based on these results that DI Kedung Putri was considered not ready yet to be modernized. For this reason, it was necessary to conduct the system improvement in groups, namely by grouping based on similarities (clustering). The used method was k-medoids clustering using Rapid Miner 9.0 software. The clustering result showed that the optimal cluster number was 4clusters, with the Davies Bouldin Index (DBI) value -1.959. The members of the 0, 1, 2 and 3 clusters were 6, 6, 8 and 1 secondary channels, respectively. Furthermore, a priority scale in clusters development was needed based on the performance of irrigation pillars on secondary channels. The results of AHP analysis showed that the order of priority development starts from cluster 0, followed by cluster 2, 1 and 3. The recommendations for the development of secondary channels incorporated in cluster 0, such as increasing water supply, routine infrastructure maintenance, technical assistance, and public campaigns in irrigation management. The secondary channels incorporated in cluster 3 had good performance on all pillars, so it only needed to maintain the existingoperation and maintenance patterns.]]>
