The leachate coming from the landfill is a serious problem. This is because the leachate water can contaminate the wells of the residents around the landfill. This research was conducted at Jabon Landfill located in Jabon District of Sidoarjo Regency, East Java Province, Indonesia. Jabon Landfill has been operating since 2003 with a controlled landfill system that has triggered environmental risks due to the leachate output. The purpose of this study was to determine the classification of the shallow groundwater quality status based on the pollution index (PI) around Jabon Landfill at a distance of around 250 meters, 500 meters and 1,000 meters from the landfill. The pollution index was determined by analyzing the pollutant concentration consisting of these following parameters: pH, BOD, COD and Fe. The results of the analysis show that the pH parameter had a higher value than the pH at Jabon Landfill of 7.2-7.5. The pH at Jabon Landfill was 6.35. The Fe parameter shows that the value of 1.694 in the groundwater well closest to Jabon Landfill and the wells further away indicates that the Fe concentration was lower for the latter, namely 0.081 at a distance of up to 200 meters. On the basis of the Pollution Index, the highest value was 5.45 at Well 7 is located 196 m from Jabon Landfill. Meanwhile, the well furthest from Jabon Landfill at a distance of 1,000 m showed a lightly polluted status with a Pollution Index of 1.91. The further the location of the well away from Jabon Landfill, the Pollution Index value tended to decrease. This means that the pollution status generally improves. Overall, the pollution status of the 18 wells shows that 2 wells are moderately polluted, 15 wells are lightly polluted and 1 well is in good condition.
The hassle of analytical and numerical solution for liquefaction modeling, repetitive laboratory testing and expensive field observations, have opened opportunities to develop simple, practical, inexpensive and valid prediction of wave-induced liquefaction. In this study, Artificial Neural Network (ANN) regression modeling is used to predict the depth of liquefaction. Despite of using Back Propagation (BP) to train ANN, a modified Genetic Algorithm (called as Wide GA, WGA) is used as ANN training method to improve ANN prediction accuracy and to overcome BP weaknesses such as premature convergence and local optimum. WGA also aim to avoid conventional GA weaknesses such as low population diversity and narrow search coverage. Key WGA operations are Wide Tournament Selection, Multi-Parent BLX-? Crossover, Aggregate Mate Pool Mutation and Direct Fresh Mutation-Crossover. ANN prediction accuracy measured by Median APE (MdAPE). Global optimum solution of WGA is best ANN connections weights configuration with smallest MdAPE.
There are still much potency of levee breaches in Indonesia. The levee strength is mostly influenced by the changing of its constituents. One of the key parameter of this phenomenon is the changing of soil water content in levee body. The increasing of soil water content will loosen the bonds among soil granules that may increase the potential of the levee breaches. The sequence of the changing parameter before levee breach is a crucial data. In this research, a monitoring system have been designed to collect the changing of soil water content using moisture sensor and to examine the changing of water level using ultrasonic sensor. These data will be further processed using fuzzy logic to identify the dangerous state describing the real of levee strength as an early warning system.
The Port of 2 × 110 MW Nagan Raya Coal Fired Steam Power Plant is one of the facilities constructed by the State Electricity Company in Aceh Province, Indonesia. During its operation, which began in 2013, the port has dealt with large amounts of sedimentation within the port and ship entrances. The goal of this study is to mitigate the sedimentation problem in the Nagan Raya port by evaluating the effect of maintenance dredging. Field measurements, and hydrodynamic and sediment transport modeling analysis, were conducted during this study. Evaluation of the wind data showed that the dominant wind direction is from south to west. Based on the analysis of the wave data, the dominant wave direction is from the south to the west. Therefore, the wave-induced currents in the surf zone were from south to north. Based on the analysis of longshore sediment transport, the supply of sediments to Nagan Raya port was estimated to be around 40,000–60,000 m3 per year. Results from the sediment model showed that sedimentation of up to 1 m was captured in areas of the inlet channel of Nagan Raya port. The use of a passing system for sand is one of the sedimentation management solutions proposed in this study. The dredged sediment material around the navigation channel was dumped in a dumping area in the middle of the sea at a depth of 11 m, with a distance of 1.5 km from the shoreline. To obtain a greater maximum result, the material disposal distance should be dumped further away, at least at a depth of 20 m or a distance of 20 miles from the coastline.
Pondasi tiang pancang merupakan salah satu faktor penting dalam struktur bangunan pantai, salah satunya adalah dermaga. Sebelum melaksanakan tahap konstruksi, perlu diketahui daya dukung tiang pancang axial yang merupakan besaran beban yang akan diterima. Studi ini dilakukan dengan menghitung perbedaan kapasitas daya dukung tiang pancang dengan diameter 600 mm yang digunakan pada Proyek Jetty Barge Loading Conveyor di Meulaboh dengan memperbandingan metode persamaan Meyerhof (1956) dan regulasi yang tertuang dalam The Overseas Coastal Area Development Institute Of Japan, OCDI (2002). Hasil perbandingan ke dua metode tersebut diperoleh daya dukung pondasi tiang pancang dengan menggunakan Metode Meyerhof yang menghasilkan daya dukung seberat 139,17 ton dan Metode OCDI menghasilkan daya dukung seberat 125,55 ton. Hasil studi ini merekomendasikan penggunaan persamaan dari Metode OCDI (2002) dikarenakan daya dukung tiang pancang yang digunakan dihitung berdasar kondisi kritis dan berada di lokasi yang rawan.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.