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All Journal Indonesian Journal of Geography Teknotan: Jurnal Industri Teknologi Pertanian Journal of Degraded and Mining Lands Management Jurnal Keteknikan Pertanian Tropis dan Biosistem Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Litbang Kota Pekalongan
Chandra Setyawan, Chandra
Departemen Teknik Pertanian Dan Biosistem, Fakultas Teknologi Pertanian, Universitas Gadjah Mada
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Mechanical Engineering Public Health Other

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Rice Fields Suitability Zonation in North Penajam Paser Regency Using Multicriteria-Based Simple Additive Weighting (SAW) and GIS Fitriana, Lely; Susanto, Sahid; Supadmo, Sigit; Ngadisih, Ngadisih; Setyawan, Chandra; Zaki, Khoiru
Indonesian Journal of Geography Vol 57, No 1 (2025): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.93784

Abstract

The East Kalimantan Provincial Government has designated North Penajam Paser Regency as one of rice food supports for the National Capital City (IKN) of the Archipelago. This decision is based the domestic production which met and even exceeded demand in 2020. One step to support rice production is to identify land with the greatest potential for cultivation. Therefore, this study aimed to analyze land suitability zonation for rice production using the criteria of climate, topography, and soil properties, as well as infrastructure. Land suitability was evaluated using simple additive weighting (SAW), multicriteria, and GIS methods taking into account the factors of drainage, soil depth, texture, type, rainfall, temperature, slope, distance from road, distance from river, and land use land cover. Suitability zonation (classes) were arranged based on land suitability classification outlined by the Food and Agriculture Organization (FAO, 1976) in Minister of Agriculture Regulation No. 79 of 2013, namely Very Suitable (S1), Moderately Suitable (S2), Marginally Suitable (S3), Not Suitable (N1). The results showed that the areas classified as highly, moderately, marginally, and not suitable were 4,960 ha (3.1%), 103,738 ha (65.5%), 44,889 ha (28.4%), and 4,708 ha (3.0 %) respectively.Received:2024-02-01 Revised:2024-09-26 Accepted:2025-03-11 Published: 2025-04-27
Analisis Water Supply-Demand Index Assessment untuk Produksi Padi Berkelanjutan di Daerah Aliran Sungai (DAS) Serayu Hilir, Provinsi Jawa Tengah, Indonesia: Analysis of Water Supply-Demand Index Assessment for Sustainable Rice Production in Downstream Watershed of Serayu Central Java Province Indonesia Yuzanni, M. Yusfan; Setyawan, Chandra; Susanto, Sahid
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 13 No. 2 (2025): August 2025
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jkptb.2025.013.02.09

Abstract

Sumber daya air merupakan elemen penting dalam proses produksi padi khususnya di wilayah tropis seperti Indonesia. Penelitian ini bertujuan untuk menganalisis water supply demand index (WSDI) untuk mendukung produksi padi di Daerah Aliran Sungai (DAS) Serayu Hilir, Jawa Tengah. Evaluasi WSDI didasarkan pada perbandingan ketersediaan dan kebutuhan air di wilayah DAS. Analisis ketersediaan air di DAS dilakukan dengan menggunakan model hidrologi tank, sedangkan kebutuhan air irigasi padi ditentukan dengan menggunakan metode Penman-Monteith dengan bantuan software CROPWAT 8.0. Pada proses perhitungan ditetapkan debit andalan 80% sebagai nilai yang mewakili ketersediaan air minimum untuk memenuhi kebutuhan air irigasi tanaman padi. Berdasarkan hasil analisis, WSDI untuk musim tanam pertama (MT1) dan kedua (MT2) diklasifikasikan sebagai “sangat baik”, tetapi musim tanam ketiga (MT3) mengalami ketersediaan air dengan kategori “buruk”, terutama pada tahun 2018, 2019, dan 2020. Hal ini mengindikasikan bahwa terdapat banyak variasi musiman terkait ketersediaan air yang sangat dipengaruhi oleh pola curah hujan. Studi ini merekomendasikan pola tanam padi-padi-hortikultura untuk memaksimalkan penggunaan air, terutama pada MT3 ketika risiko kekeringan meningkat. Analisis WSDI memberikan informasi yang berguna untuk eksplorasi spasial dan terestrial serta menyoroti pentingnya strategi konservasi dalam mengatasi kekeringan di musim kemarau. Pemilihan tanaman hortikutura pada MT3 didasarkan pada kebutuhan air rata-rata tanaman yang lebih rendah, masa tanam singkat, Penelitian ini berkontribusi pada pengembangan strategi pengelolaan sumber daya air yang berguna untuk meningkatkan produksi beras di wilayah DAS yang mengalami perubahan iklim dan tata guna lahan.
Rainfall-Runoff Modelling in Tropical River Basin for Water Conservation Planning Using Water Recharge Ponds Yuzanni, M Yusfan; Setyawan, Chandra; Susanto, Sahid; Nugraheni, Yekti
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 4 (2024): December 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i4.1171-1181

Abstract

Land conversion in river basins poses a threat to future water availability. This research aims to estimate water availability, particularly stream flow for planning of water conservation. Water availability was analyzed using a hydrology tank model. The model was calibrated by using stream flow data measured in a reservoir and then used to estimate water availability in the reservoir's catchment area. The value of model parameters such as wet infiltration coefficient (WIC), dry infiltration coefficient (DIC), soil moisture capacity (SMC), initial soil moisture (ISM), initial groundwater storage (IGWS), groundwater recession constant (k) was determined through the calibration process. The results showed that the model has good accuracy for stream flow calculation indicated by the value of statistical parameters i.e. coefficient of correlation (R) = 0.93, a volume of error (VE) = 0.04, and a coefficient of efficiency (CE) = 1.00. During the wet season, the specific maximum discharge is 0.11 m3s–1km–2. Meanwhile, the minimum specific discharge is 0.030 m3s–1km–2. These differences indicate that optimizing rainwater harvesting during the wet season is required. Rainfall-runoff modeling reveals the potential for surface runoff during the wet season is 1,139 mm. This finding provides an essential reference for water conservation, especially using water recharge ponds. Keywords: Hydrology tank model, Stream flow, Tropical river basin, Water availability, Water conservation.
Modeling River Water Levels in Tidal Swamp Areas using HEC–RAS to Determine the Hydrotopography of Tidal Farmland Faiz Afnan Nurrahman; Chandra Setyawan; Hanggar Ganara Mawandha
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 2 (2025): April 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v14i2.685-700

Abstract

Swamp land is a natural resource that can be utilized to improve community welfare, because swamp land is one of the potential natural resources and can be used as agricultural land development. The aim of this research is to analyze the tidal water movement patterns of rivers and channels in the swamp irrigation area of Palingkau. The stages in this research included the installation of an Automatic Water Level Recorder (AWLR) to collect real-time water level data, then modeling the tidal movement of river water level using HEC–RAS modeling. The results of this research showed that the pattern of tidal water flow movement in the swamp irrigation area of Palingkau is diurnal tide, characterized by the existence of one high tide and one low tide in one day. Furthermore, HEC–RAS modeling can be used to describe the tide of water levels in the swamp irrigation area of Palingkau. Validation of the HEC–RAS model shows that the tidal flow modeling simulation is good and very suitable for use. Based on the hydrotopography class, the land at the research location is classified into 3 classes, namely hydrotopography classes of B, C, and D. Keywords: Agriculture, HEC–RAS Modeling, Hydrotopography, Land, Swamp.
Assessment of Soil and Water Conservation Potential Using Vetiver Crops (Chrysopogon zizanioides) as a Nature-Based Solution for Watershed Restoration Chandra Setyawan; Yekti Nugraheni; Ngadisih Ngadisih; Rizki Maftukhah; Devi Safrina
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 5 (2025): October 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v14i5.1785-1797

Abstract

Watersheds play an important role in the hydrological cycle to ensure water availability and support food security. Currently, many watersheds are experiencing degradation due to excessive agricultural practices without the implementation of soil and water conservation measures. This study aims to assess the potential of Vetiver crops (Chrysopogon zizanioides L.) for soil and water conservation as a nature-based solution for watershed protection.n. This research use Geographic Information System (ArcGIS) tools to analyze land suitability for Vetiver cultivation. A multi-criteria evaluation approach was applied using a scoring system based on key environmental indicators including rainfall, temperature, slope gradient, land use type, soil type, and organic matter content. The results indicate that most of the study area was classified as moderately suitable (61.98%) and marginally suitable (38.00%) for vetiver plants, with only 0.01% falling into the highly suitable and not suitable categories, respectively. The integration of spatial analysis and environmental indicators allowed for the identification of priority areas where Vetiver could be effectively implemented to enhance watershed resilience, mitigate erosion, and support sustainable land management. The finding of this study provides a reference for vegetation method development using crops with economic value which is suitable for tropical areas.
Rainfall Prediction with Radial Basis Function Neural Network and Its Correlation with Bird's Eye Chili (Capsicum frutescens) Production in Sawangan Subdistrict Magelang Regency Azka Sinatrya; Bayu Dwi Apri Nugroho; Chandra Setyawan
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 15 No. 3 (2026): June 2026
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v15i3.1241-1253

Abstract

Climate change causes rainfall anomalies that directly impact the decline in horticultural crop productivity, particularly bird's eye chili (Capsicum frutescens). This study aimed to analyze the effect of global rainfall indices in Sawangan Subdistrict through the development a prediction model. Modeling was performed using Radial Basis Function Neural Network (RBFNN) method with Principal Component Analysis (PCA) integration to simplify the climate index input variables. Model accuracy was evaluated using the Root Mean Squared Error (RMSE), Nash-Sutcliffe Efficiency (NSE), and R2. Furthermore, the prediction results were correlated with chili production data to test the relevance of the model to actual conditions. Results showed that model configurations provide varying performance. The best model based on evaluation is the model in the 15-year range using PCA 3 global climate indices and training percentage of 90% (RMSE: 101.39; NSE: 0.7268). However, for validation and correlation with production, it was found that the 15-year range using PCA 5 global climate indices and training percentage of 70% was the best model with highest R2 value of 0.8572 and correlation value close to actual value. Variations in data period, number of climate indices, and training data proportion affect model performance. Adding data volume and variable complexity does not always improve accuracy, so it is necessary to identify the optimum point to get the most reliable prediction model.
Co-Authors Antonius Wahyu W Azka Sinatrya Bayu Dwi Apri Nugroho Brigitta Ery Septiyanti Chin-Yu Lee dan Sukirno Devi Safrina Dimas Prabowo Harliando Donnie Koes Nugraha Faiz Afnan Nurrahman Fitriana, Lely Hanggar Ganara Mawanda Hanggar Ganara Mawandha M Yusfan Yuzanni Muhamad Khoiru Zaki Muhammad Khoiru Zaki Muhammad Wiji Nur Huda Huda Murtiningrum Murtiningrum Ngadisih Ngadisih Ngadisih Ngadisih Ngadisih Ngadisih Ngadisih Ngadisih Nugraheni, Yekti Prieskarinda Lestari Rizki Maftukhah Sahid Susanto Sahid Susanto Sahid Susanto Sigit Supadmo, Sigit Wini Prayogi Abdila Yekti Nugraheni Yekti Nugraheni Yuzanni, M Yusfan Yuzanni, M. Yusfan Zaki, Khoiru