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All Journal Indonesia Berdaya Journal of Soft Computing Exploration
Rosyida, Miftahurrahma
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Training on the Use of Batik Waste Processing Equipment to Enhance Productivity for the Wijirejo Pandak Bantul Batik Group Amelia, Shinta; Evitasari, Rachma Tia; Rosyida, Miftahurrahma; Sabila, Liya Yusrina; Sabilihaq, Roby; Lestari, Betty Novia; Aini, Siti Nur
Indonesia Berdaya Vol 5, No 4 (2024)
Publisher : UKInstitute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ib.2024906

Abstract

The batik industry is one that continues to develop over time. One of the ongoing concerns is the waste generated by the batik industry, particularly the dye content in batik dyes. Reactive dyes, if not processed properly, can have a very negative impact on the environment. They can pollute water sources, harm the surrounding environment, and even kill aquatic biota. Currently, liquid batik waste is stored in holding tanks and allowed to seep into the ground without further processing. Given the environmental impact of batik dyes, efforts must be made to minimize these effects before the waste is discharged into water bodies. A batik waste processing method currently under development is the Heterogeneous Fenton method. This method can degrade batik waste into compounds that are less harmful to the environment. The implementation of this service involves socialization and introduction of the program to the service partners, as well as training. This includes technology introduction, tool usage, and the transfer of scientific and technological knowledge to the service partners.
Quadrotor height control system using LQR and recurrent artificial neural networks Rahani, Faisal Fajri; Rosyida, Miftahurrahma
Journal of Soft Computing Exploration Vol. 5 No. 2 (2024): June 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i2.379

Abstract

The quadorotor is a type of unmanned flying vehicle known as Unmanned Aerial Vehicle (UAV). In recent years, quadrotors have attracted much attention from researchers around the world due to their excellent maneuverability. A good control system in this quadrotor system is needed for ease of use of this quadrotor. One control system that is often used is the Linear Quadratic Regulator (LQR) control system. This control system has challenges for dynamic system disturbances in quadrotor control. Researchers proposed a recurrent artificial neural network (RNN) system to address these challenges.RRN is used to change the value of the feedback component in the LQR control system. The nature of the feedback component in LQR, which is static, is changed based on the system error value based on changes in the error value entered into the RNN. The result of this RNN is a change in the value of the LQR feedback component based on the input of the system. The results of this research show that LQR control with RNN produces a faster system response of 0.075 seconds and a faster settling time of 0.221 seconds. Compensation for the system response speed produces a higher overshot value.
Co-Authors Amelia, Shinta Evitasari, Rachma Tia Faisal Fajri Rahani Lestari, Betty Novia Sabila, Liya Yusrina Sabilihaq, Roby Siti Nur Aini, Siti Nur