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All Journal Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan
Nastasia Margini
Institut Teknologi Sepuluh Nopember

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Optimization Balongganggang Reservoir Capacity for Irrigation Nastasia Margini; Asyraf Kamilul Basyar
Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan Vol 9 No 1 (2024): MARCH
Publisher : Program Studi Teknik Sipil, Fakultas Teknik, Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/cvl.v9i1.1184

Abstract

Indonesian agriculture is the largest economic contributor after the non-oil and gas industry. However, ensuring stability in agriculture poses a significant challenge, as indicated by BPS data in 2020 and 2022, showing a decrease in the rice sector in crop area and productivity value by 2.3%. Therefore, this research aimed to increase agricultural output by optimizing planting patterns and reservoirs in Balongganggang Irrigation Area and Reservoir, Sukodadi District, Lamongan Regency, East Java. Optimization of planting patterns was carried out using rainfall and climatology data from 2013 – 2022, with a linear programming method, facilitated by POM-QM for Windows V5 program. The process of optimization focused on two objectives, namely considering maximum land area and maximizing profit. According to the analysis, optimization based on land area and profit provided the same optimal value, leading to a 9.98% increase in planting intensity from 120.57% to 130.55%, with a profit of Rp 33,967,000,000.00.
Rainfall Forecasting Using Historical Rainfall and Humidity Data in Wonorejo Watershed, Indonesia Nastasia Margini; M. Bagus Ansori
Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan Vol 11 No 1 (2026): MARET
Publisher : Program Studi Teknik Sipil, Fakultas Teknik, Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/cvl.v11i1.1645

Abstract

Rainfall prediction plays a crucial role in the design, planning, and management of water resource systems. This study addresses the importance of accurate rainfall forecasting to optimize the operational efficiency of the Wonorejo Reservoir in Tulungagung Regency, Indonesia. By improving rainfall predictions, it becomes possible to estimate available water volumes more precisely and enhance reservoir utilization beyond current practices. This research employs three analytical approaches—Decomposition, Multiple Linear Regression, and Nonlinear Regression—to forecast rainfall in the Wonorejo Watershed. The models are developed using monthly total rainfall and average air humidity data collected from January 1998 to December 2018. Model performance is evaluated using the Root Mean Square Error (RMSE). The Nonlinear Regression method yields the lowest RMSE (72.71), followed by Decomposition (73.78) and Multiple Linear Regression (103.57). Based on these results, the Nonlinear Regression model is identified as the most suitable approach for forecasting rainfall in the Wonorejo Basin for the subsequent 24 months. This study recommends the application of the Nonlinear Regression method for rainfall forecasting in this specific case study area.
Co-Authors Asyraf Kamilul Basyar M. Bagus Ansori