Article Per Year (5 Year)
p-Index From 2021 - 2026
1.288
P-Index
This Author published in this journals
All Journal Media Teknik Sipil Jurnal Mahasiswa Jurusan Teknik Sipil Journal of Degraded and Mining Lands Management Jurnal Tata Kota dan Daerah Jurnal Teknik Pengairan: Journal of Water Resources Engineering Rekayasa Sipil AGRIVITA, Journal of Agricultural Science Civil and Environmental Science Journal (CIVENSE) Astonjadro
Agus Suharyanto
Department of Civil Engineering, University of Brawijaya
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Engineering Environmental Science Social Sciences Transportation

Published : 24 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 24 Documents
Search

 1   2   3 
Resource Leveling Optimization Using Different Objective Functions on Building Project Irvania, Artya; Pujiraharjo, Alwafi; Suharyanto, Agus
ASTONJADRO Vol. 13 No. 1 (2024): ASTONJADRO
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

One of the problems that often occur in allocating labor is fluctuations arising from the uneven allocation of labor, so resource leveling optimization is needed to avoid these problems. This study investigates the impact of five objective functions to determine which objective function can produce an efficient labor histogram and determine the effect of resource leveling on changes in labor cost fluctuations based on case studies. The research was conducted using the symbiotic organisms search (SOS) algorithm. The results of this study show that objective function 4 (the minimum amount of the sum of the squared deviations in the use of resources between time intervals) is more effective than other objective functions by producing the most significant average increase in fitness value of 61.64% and can produce a smoother labor allocation histogram compared to other objective functions. Resource leveling also affects cost fluctuations, with a decrease in efficiency of 47%, so that it can improve project implementation efficiency and effectiveness.
Effects of land cover, slope, and soil physical properties on runoff coefficient in Upper Brantas Sub-watershed Cahya, Utik Tri Wulan; Utomo, Wani Hadi; Nugroho, Waego Hadi; Suharyanto, Agus
Journal of Degraded and Mining Lands Management Vol. 12 No. 5 (2025)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2025.125.8593

Abstract

Management of water resources in watersheds requires an in-depth understanding of the factors that influence the runoff coefficient. This study aimed to analyze the influence of land cover, slope, and soil physical properties on the runoff coefficient in the Upper Brantas Sub-watershed and develop a prediction model using multiple linear regression. The research was conducted in Pesanggrahan Village, Batu City, using nine observation plots consisting of three types of land cover (dense canopy, moderate canopy, and sparse canopy) with three slope classes (15%, 25%, and 35%). Surface runoff measurements were conducted using 150 m² plots during the rainy season. Pearson correlation analysis showed that the runoff coefficient was significantly negatively correlated with land cover percentage (r = -0.551; p<0.001) and Dry Microaggregate Ratio (DMR) index (r = -0.439; p<0.001), and significantly positively correlated with slope (r = 0.265; p<0.001) and sand content (r = 0.410; p<0.001). The selected regression model (C = -0.031 - 0.074X1 + 0.015X2 - 0.001X4 + 0.110X6) showed land cover/X1 had the strongest influence (? = -0.074, p<0.0001), followed by slope class/X2 (? = 0.015, p<0.0001), bulk density/X4 (? = 0.110, p<0.001), and silt content/X6 (? = -0.001, p<0.036). The model performed well with a validation R² of 46.3% and a Root Mean Square Error (RMSE) of 0.0331. This research presents a practical model for estimating runoff coefficients, supporting soil and water conservation planning in mountainous areas.
THE USE OF SATELLITE REMOTE SENSING DATA AND GEOGRAPHIC INFORMATION SYSTEMS ON CRITICAL LAND ANALYSIS Suharyanto, Agus; Suhartanto, Ery; Pudyono, Pudyono
AGRIVITA Journal of Agricultural Science Vol 35, No 2 (2013)
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v35i2.182

Abstract

Critical land classification can be analyzed using combination between Top Soil Thickness - Land erosion method, and BRLT methods. Both methods are needed soil erosion data as one of input data. The soil erosion data can be analyzed using USLE and MUSLE methods. The combination of two critical land analyses methods with input soil erosion data from two analyses methods will be produced four combinations of critical land classification. In this research, four of the critical land classification and two soil erosion classification will be analyzed using GIS. The best method to classify critical land will be investigated in this research. The best classified critical land is the classified critical land data is nearest with the field condition.Percentage of vegetation cover (PVC) is one of the most important input data in the critical land classification analysis using BRLKT method. This data have 50% weight. PVC condition is classified into five categories i.e. very good, good, fair, poor, and very poor. Each category have score 5, 4, 3, 2, 1 respectively. To analyze this PVC classification, NDVI generated from satellite remote sensing data is used in this research. From the four methods of land critical classification analyses used in this research, critical land classified using BRLKT method with input soil erosion analyzed using method is produced the critical land classification nearest with the critical land condition in the field.Keywords: Critical land, Land erosion, GIS, Satellite Remote Sensing Data, NDVI
Optimization of the Number and Type Composition of Houses in Housing Development Using the Simplex Method (Case Study: Pesona Arjuna Residence, Malang Regency) Abdullah, Ali; Suharyanto, Agus; Suryo, Eko Andi
Rekayasa Sipil Vol. 19 No. 1 (2025): Rekayasa Sipil Vol. 19 No. 1
Publisher : Department of Civil Engineering, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.rekayasasipil.2025.019.01.7

Abstract

The rising population in Indonesia has led to an increasing demand for housing, presenting opportunities and challenges for property developers. Although luxury homes yield higher profits, most consumers favor affordable housing. This study aims to optimize the quantity and type composition of homes in Pesona Arjuna Residence, Malang Regency, using the Simplex Method to maximize profits. Developers need to balance market demand and government regulations, which require including affordable and middle-income homes alongside luxury units. The Simplex Method is applied in this study to determine the ideal composition of housing units by factoring in key constraints such as available land, production costs, and market demand. The findings reveal that houses in buildings 12 type A, 18 type B, and 23 type C yield the highest profitability. The Net Present Value (NPV) of Rp 610,940,579.76 at a 10% discount rate confirms the project’s financial success, while the Internal Rate of Return (IRR) of 13.49% indicates a solid annual return on investment. A Benefit-Cost Ratio (BCR) of 1.617 further supports the project’s financial viability, though careful consideration of market fluctuations and risks is advised. This research contributes to sustainable urban planning by offering a flexible approach to housing development, enabling developers to better adapt to market trends and optimize profits while addressing community housing needs.
Co-Authors A'izzatul Khiyana Achendri M. Kurniawan Achmad Wicaksono Akhriadi, Akhriadi Ali Abdullah, Ali Alwafi Pujiraharjo Anandia, Reza Arief Rachmansyah Beselly Putra, Sebrian Mirdeklis Birka, Ahmam Budi Sugiarto Waluyo Cahya, Utik Tri Wulan Dwi Yanti, Anggi Ayu Eko Andi Suryo Emma Irawati Ery Suhartanto Gholiqul Amrodh Alawy Gustianto, Garindra Harnen Sulistio Hartasantoso, Fakhrul Ibrahim, Tsabita Imania Ilham Adam Admaja Indradi Widjatmiko Indradi Wijatmiko Irvania, Artya Ludfi Djakfar Lutfi Djakfar M. Bisri M. Hamzah Hasyim M. Ruslin Anwar M. Zainul Arifin Muhammad Hafis Adli Rahman, Muhammad Hafis Nuzul Wahyunita R, Nuzul Pamungkas, Harya Panji Saputra, Cita Ahmat Pudjiraharjo, Alwafi Pudyono . Puspa Permanasari Rina Puspita Wahyuningaji, Rina Puspita Rumatarai, Marthina Hermina Waego Hadi Nugroho Wani Hadi Utomo Wicaksono ., Wicaksono Wiguna, Raynaldy Arya Yatnanta Padma Devia Yulvi Zaika