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

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.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

Mathematical Modeling-Based Management of a Sand Trap throughout Operational and Maintenance Periods: Case Study Pengasih Irrigation Network, Indonesia

Surface irrigation networks in Indonesia are damaged by several factors, and sedimentation is among the most severe challenges. Sand traps play a substantial role in improving irrigation system efficiency by reducing sedimentation. There are two periods in sand trap operation: the operational and maintenance periods. Pengasih is one of the irrigation schemes implemented in the Progo Opak Serang (POS) River Basin, which has a high level of erosion. This study aimed to propose an appropriate management strategy for the Pengasih sand trap as the first barrier in irrigation network sedimentation based on mathematical modeling. The HEC-RAS simulation software was used to simulate the sand trap hydraulic behaviour. The results show that the validated Manning’s coefficient was 0.025. The optimal transport parameters were Laursen for the potential function, Exner 5 for the sorting method, and Rubey for the fall velocity method. The recommended flushing timeframe is 315 min, with a discharge of 2 m3/s. We suggest that the sand trap flushing frequency be performed twice a year, and it can be performed at the end of March and October. This coincides with the end of the first and third planting seasons of the irrigation scheme. © 2022 by the authors

Mathematical Modeling-Based Management of a Sand Trap throughout Operational and Maintenance Periods (Case Study: Pengasih Irrigation Network, Indonesia)

Surface irrigation networks in Indonesia are damaged by several factors, and sedimentation is among the most severe challenges. Sand traps play a substantial role in improving irrigation system efficiency by reducing sedimentation. There are two periods in sand trap operation: the operational and maintenance periods. Pengasih is one of the irrigation schemes implemented in the Progo Opak Serang (POS) River Basin, which has a high level of erosion. This study aimed to propose an appropriate management strategy for the Pengasih sand trap as the first barrier in irrigation network sedimentation based on mathematical modeling. The HEC-RAS simulation software was used to simulate the sand trap hydraulic behaviour. The results show that the validated Manning’s coefficient was 0.025. The optimal transport parameters were Laursen for the potential function, Exner 5 for the sorting method, and Rubey for the fall velocity method. The recommended flushing timeframe is 315 min, with a discharge of 2 m3/s. We suggest that the sand trap flushing frequency be performed twice a year, and it can be performed at the end of March and October. This coincides with the end of the first and third planting seasons of the irrigation scheme

Recognition of Agricultural Land-Use Change with Machine Learning-Based for Regional Food Security Assessment in Kulon Progo Plains Area

High conversion of agricultural land in Kulon Progo Regency, as such the construction of the Yogyakarta International Airport (YIA) and the Bedah Menoreh road, has resulted in food production and impacted food security, including Kulon Progo plains area. This study aimed to calculate the conversion rate of agricultural land and analyze its impact on food security in the Kulon Progo plains area from 2005 to 2020. The primary materials needed are Kulon Progo administrative maps, Landsat 7 and 8 images, land productivity data, population data, and consumption per capita data. With tools used is Google Earth Engine (GEE), SPSS 25, Google Earth Pro, and ArcGIS 10.3. The method used is calculating the Normalized Difference Vegetation Index (NDVI) and machine learning-based classification through GEE to identify land-use change and analyze the state of food security. The study proved that between 2015 and 2020, there was a conversion of paddy fields, with an average rate of 126 ha/year. The existence of new paddy fields influenced this land increase. However, in 2020 there is still food insecurity in Pengasih District, thus caused by the new paddy fields not being optimally used for rice growth. The productivity of the land produced is not optimal. With the availability of agricultural land in 2020 (1382.85 ha), food self-sufficiency will be limited for the next 24.75 years if there is no effort to increase paddy fields