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All Journal Sinergi Indonesian Journal of Electrical Engineering and Computer Science Journal of the Civil Engineering Forum
Wang, Qian
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Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Water Quality Modelling with Industrial and Domestic Point Source Pollution: a Study Case of Cikakembang River, Majalaya District Kent, Steven; Yudianto, Doddi; Gao, Cheng; Fitriana, Finna; Wang, Qian
Journal of the Civil Engineering Forum Vol. 10 No. 2 (May 2024)
Publisher : Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jcef.11807

Abstract

Rapid industrial development is one of the leading causes of environmental degradation. The textile industries and the domestic activities in Majalaya District produce wastewater directly discharged into the Cikakembang River. As a result, the Cikakembang River’s water quality has decreased to the point that the water quality cannot be used for daily needs. This study modeled three main parameters in water quality modelling, namely Dissolved Oxygen (DO), Biological Oxygen Demand (BOD), and Chemical Oxygen Demand (COD). Using MATLAB, the three-water quality governing equations originating from the Advection-Dispersion Equation were solved using the Runge Kutte-4 discretization scheme. The numerical modelling was carried out along 2.36 km of the Cikakembang River. All water quality coefficients, such as the DO Saturation (DOsat), the Reaeration Rate (ka), the Dispersion Coefficient (D), the Deoxygenation Rate (kd), and the Decomposition Rate (kc), for the Cikakembang River were estimated using equations developed by existing studies. The estimation of ka and D coefficients requires hydraulic parameters, which in this study were estimated using the HEC-RAS simulation. Meanwhile, kd and kc values were obtained from the calibration and verification process. The Relative Root Mean Square Error (RRMSE) objective function was used to evaluate the results of water quality modelling at three sampling points. In the calibration process, the resultsof water quality modelling produced RRMSE values for the DO, BOD, and COD parameters of 1.99%, 0.36% and 0.92%, respectively. Meanwhile, for the verification process, the RRMSE values for the DO, BOD, and COD parameters are 1.95%, 1.02% and 1.86%. All water quality parameters produce small RRMSE values in the calibration and verification processes. Hence, the water quality model created has good accuracy and stability.
Experimental research on text CAPTCHA of fine-grained security features Wang, Qian; Ibrahim, Shafaf; Wan, Xing; Idrus, Zainura
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp535-545

Abstract

CAPTCHA is a cybersecurity measure that distinguishes between humans and automated scripts. Researchers have employed various security features to thwart automated program identification by hackers. However, previous research on the attack resistance of CAPTCHAs has used roughly quantitative analysis instead of a fine-grain quantitative study. This study implemented comparative experiments based on CAPTCHA recognition algorithms to find the best-mixed security features. A multi-stage best parameter selection (MBPS) mechanism was proposed in this study. Experiment results indicated that mixed security features of “overlap + scale + rotate + bg (background)” were the best, with an average machine recognition accuracy of only 4.81%. The contrast experiment result illustrated that the anti-attack ability of mixed security features was better than adding adversarial noise, with machine recognition accuracy decreased by 2.2%. Moreover, by investigating the efficacy of security feature parameters, this study provides practical guidelines for designing robust CAPTCHAs. Furthermore, this study also presents valuable insights into the security of image generation technology.
Cikakembang River Restoration from the Perspective of Numerical Modelling Kent, Steven; Yudianto, Doddi; Gao, Cheng; Fitriana, Finna; Wang, Qian
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.020

Abstract

The poor condition of the Citarum River demands more significant pollution control. One alternative for controlling pollution can be limiting the amount of wastewater entering one of the tributaries of the Citarum River, namely the Cikakembang River. This study is a follow-up study that will model heavy metal parameters in the Cikakembang River. Data collection was carried out six times, where the heavy metal parameter detected was copper. Numerical modelling for copper parameters was carried out using MATLAB software with the Runge Kutte-4 discretisation scheme. The study location covers 2.36 km upstream of the Cikakembang River, with 12 textile industry wastewater disposal points. Numerical modelling results for copper parameters show a settling rate of heavy metal particles of 40 day-1, with a maximum RRMSE value of 9.97%. Combining the water quality models for organic and heavy metal parameters created, pollution control simulations can be run in both seasons. The pollution control scenario aims to find the maximum amount that enters the Cikakembang River without passing the class four river water quality standards. The selection of the standard is based on the use of Cikakembang River water, namely for irrigation purposes. Based on the results of pollution control simulations, the pollutant carrying capacity for BOD, COD and copper parameters in the Cikakembang River is 199.43 kg/day, 1103.80 kg/day and 4.06 kg/day, respectively.
Co-Authors Doddi Yudianto Fitriana, Finna Gao, Cheng Ibrahim, Shafaf Idrus, Zainura Kent, Steven Wan, Xing