Analisis Kesiapan Modernisasi Daerah Irigasi Kedung Putri Pada Tingkat Sekunder Menggunakan Metode K-Medoids Clustering

Author:

Pradipta Ansita Gupitakingkin,Pratyasta Anditya Sridamar,Arif Sigit Supadmo

Abstract

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, the decision making was conducted by using the Analytic Hierarchy Process (AHP) method. Performance assessment of 21 secondary channels was stated as the readiness index of irrigation modernization (IKMI). The assessment result showed that 9,52% included in good criteria, 71,43% included in fair criteria, and 19,05% included in poor criteria. Based on these results that DI Kedung Putri was 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 were 4 clusters, with the Davies Bouldin Index (DBI) value -1,959. The members of the 0, 1, 2 and 3 cluster were 6, 6, 8 and 1 secondary channels, respectively. Furthermore, the 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, such as increasing water supply, routine infrastructure maintenance, technical assistance, and public campaigns in irrigation management. The secondary channel incorporated in cluster 3 had good performance on all pillars, so it only needed to maintain the existing operation and maintenance patterns.

Publisher

Universitas Gadjah Mada

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3