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Panduan Adriansyah, Andi
Reviewer Vol 1, No 1 (2018)
Publisher : Reviewer

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Panduan Penulisan
PROPOSE SAFETY ENGINEERING CONCEPT SPEED LIMITER AND FATIGUE CONTROL USING SLIFA FOR TRUCK AND BUS Pranoto, Hadi; Adriansyah, Andi; Feriyanto, Dafit; Wahab, Abdi; Zakaria, Supaat
SINERGI Vol 24, No 3 (2020)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2020.3.009

Abstract

In 2015, there were 55 deaths from 6,231 accident cases that occurred in Jakarta. A severe problem in Indonesia is the absence of a unique safety device in both commercial transport or personal vehicles and the very high complexity problem of human highways. Consequently, there are many traffic accidents caused by the negligence of the driver, such as driving a vehicle in a drunken, tired, drowsy, or over-limit speed. Therefore, it needs to be innovative using devices to increase speed but able to detect the level of tired or sleepy drivers. This paper tries to propose a concept of improving safety engineering by developing devices that can control the speed and level of safety of trucks and buses, named SLIFA. The proposed device captures the driver's condition by looking at the eyes, size of mouth evaporating, and heart rate conditions.  Theses condition will be measured with a particular scale to determine the fatigue level of the driver. Some performance tests have been carried out on truck and bus with 122 Nm and 112 Nm torque wheels and 339 HP and 329 HP power values, respectively, and the minimum speed is 62 km/h. At a top speed of 70 km / h, the torque and power of the truck are 135Nm and 370HP, with average fuel consumption of 3.43 liters/km before SLIFA installation and average fuel consumption of 4.2 liters/km after SLIFA installation. SLIFA can be said to have functional eligibility and can cut fuel consumption by 81 percent.
THE ACA-BASED PID CONTROLLER FOR ENHANCING A WHEELED-MOBILE ROBOT Suwoyo, Heru; Thong, Zhou; Tian, Yingzhong; Adriansyah, Andi; Ibnu Hajar, Muhammad Hafizd
TEKNOKOM Vol. 5 No. 1 (2022): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (734.663 KB) | DOI: 10.31943/teknokom.v5i1.74

Abstract

Wall-following control of mobile robot is an important topic in the mobile robot researches. The wall-following control problem is characterized by moving the robot along the wall in a desired direction while maintaining a constants distance to the wall. The existing control algorithms become complicated in implementation and not efficient enough. Ant colony algorithm (ACA), in terms of optimizing parameters, has a faster convergence speed and features that are easy to integrate with other methods. This paper adopts ant colony algorithm to optimize PID controller, and then selects ideal control parameters. The simulation results based on MATLAB show that the control system optimized by ant colony algorithm has higher efficiency than the traditional control systems in term of RMSE.
Design of Health Monitoring Framework Model using oneM2M Standard Adriansyah, Andi; Amrullah , Ahmad Ghozali
International Journal of Electrical, Energy and Power System Engineering Vol. 4 No. 1 (2021): International Journal of Electrical, Energy and Power System Engineering (IJEEP
Publisher : Electrical Engineering Department, Faculty of Engineering, Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/ijeepse.4.1.107-112

Abstract

The causes of traffic accidents are affected by human factors. Driver’s illness, such as exhaustion, drowsiness, and other chronic diseases, are the critical reasons for this. The creation of the Internet of Things (IoT) technology has tried to resolve these issues. The emphasis is on tracking and regulating driving safety and conditions. Unfortunately, there is no uniform IoT standard for this device. This study aims to provide a model for monitoring and handling the situation of drivers by combining the E-Health Tracking (EHM) and the Automotive Health and Safety (AHS) frameworks. The results of the system design are referred to as In-vehicle E-Health Monitoring (IV-EHM). The IV-EHM framework model analysis based on the oneM2M standard has been carried out. Based on the study, it can be said that the system has the specified requirements.
Fuzzy logic assessment of X-ray tube risks in robotic C-arm angiography: a failure mode and effect analysis study Firdaus, Ade; Adriansyah, Andi; Ferdana, Nanda; Suhartina, Rahmalisa; Surakusumah, Rino Ferdian; Haekal, Jakfat; Zulhamidi, Zulhamidi; Shamsudin, Abu Ubaidillah
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp506-514

Abstract

This research examines the integration of robotic C-arm technology in angiography, a critical tool for treating cardiac conditions. The robotic C-arm, which includes an X-ray tube, is essential for scanning patients during procedures. The study also investigates the associated risks, specifically in Indonesian hospitals with cardiac facilities. Angiography is used to diagnose and treat heart disease by visualizing blood vessels and facilitating catheterization procedures. However, its mobility poses hazards and can impact the process. To address potential risks, failure mode and effect analysis (FMEA) is utilized. Traditionally, risk assessment using risk priority numbers (RPN) is conducted, but these may not accurately reflect failures due to complex evaluating processes. To overcome this limitation, fuzzy logic is employed, enhancing risk assessment accuracy. Through this approach, twenty-seven failure modes are identified across two brands, with ten major ones prioritized using fuzzy logic. These findings facilitate the development of preventive measures to mitigate future failures and enhance patient safety during angiography in hospitals. In conclusion, the study underscores the importance of robust risk management in medical equipment, particularly in dynamic environments. By integrating fuzzy logic into risk assessment, the study improves prioritization accuracy, enabling effective allocation of resources for preventive actions.
Lighting System Optimisation Design using Solatube with GA-PID Controller ADRIANSYAH, ANDI; KOERNIAWAN, SETYA DWI; SHAMSUDIN, ABU UBAIDAH
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 11, No 3: Published July 2023
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v11i3.744

Abstract

ABSTRAKSolatube adalah sebuah sistem pencahayaan ruangan yang digunakan untuk menghemat listrik yang dihasilkan dari energi yang tidak terbarukan. Namun, jumlah sinar matahari yang masuk ke ruangan melalui Solatube belum diatur. Tujuan riset ini adalah menghasilkan intensitas cahaya yang lebih stabil pada 350 Lux sepanjang hari selama 24 jam. Penelitian ini mencoba merancang sistem optimasi pencahayaan dengan metode desain eksperimental berbasiskan pengendali PID. Sistem terdiri dari sebuah mikrokontroller, sebuah sensor cahaya dan beberapa motor dengan penggeraknya. Penalaan parameter PID dimulai dengan metode Ziegler-Nichols dan mengoptimalkannya dengan metode Algoritma Genetika (GA). Hasil terbaik diperoleh dengan metode GA dengan jumlah populasi 50, dengan nilai Kp = 0.105210, Ki 0.052901, dan Kd = 0.046443, dengan waktu tuning 94 detik. Nilai penghematan dalam penggunaan energi listrik adalah 22,07% per tahun.Keywords: Solatube, Pencahayaan Lampu, Pengendali PID, Algoritma Genetika (GA), Pengehamatan EnergiABSTRACTA Solatube is a daylight system that used to save electricity generated from nonrenewable energy sources. However, the amount of solar entering the room via the Solatube had not been controlled. The goal of the research is maintaining a more consistent light intensity of 350 Lux for 24 hours. The study attempts to create a lighting optimization system based on an experimental design based on a PID controller. The system consists of a microcontroller, a light sensor, some motors and drivers. The PID parameter is tune beginning with the Ziegler-Nichols method and optimizing it with the Genetic Algorithm (GA) approach. The GA approach produced the best results with a population of 50, a Kp value of 0.105210, a Ki of 0.052901, a Kd of 0.046443, and a tuning time of 94 seconds. The annual savings value of using electrical energy is 22.07%.Keywords: Solatube, Lighting Lamps, PID Controllers, Genetic Algorithm (GA), Energy Saving
A HBMO-based batch beacon adjustment for improving the Fast-RRT Suwoyo, Heru; Tian, Yingzhong; Adriansyah, Andi; Andika, Julpri
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.pp107-119

Abstract

Fast-RRT improves on the original rapidly-exploring random trees (RRT) by incorporating two main stages: improved-RRT and fast-optimal. The improved-RRT stage enhances the search process through fast-sampling and random steering, while the fast-optimal stage optimizes the path using fusion and path arrangement. However, path fusion can only be optimal when the newly found path is unique and different from previous paths. This uniqueness rarely occurs in cases with narrow corridors, so path fusion only provides suboptimal conditions. To address this, the study explores using honey bee mating optimization (HBMO) to optimize or replace the fusion stage. HBMO helps determine new beacon coordinates, which are nodes between the start and goal points along the path, through a batch beacon adjustment approach. The results show that integrating HBMO into FastRRT improves its optimality, with a 21.85% reduction in path cost and a 5.22% decrease in completion time across environments with varying difficulty levels. This hybrid algorithm outperforms previous methods in terms of both path optimality and convergence rate, demonstrating its effectiveness in enhancing Fast-RRT’s performance.
An Effective Way for Repositioning the Beacon Nodes of Fast RRT Results Utilizing Grey Wolf Optimization Suwoyo, Heru; Adriansyah, Andi; Andika, Julpri; Shamsudin, Abu Ubaidah; Tian, Yingzhong
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.22062

Abstract

Conceptually, Fast-RRT applies fast sampling and random steering which makes the initial path quickly obtained. Referring to the initial path, the optimality of the path is improved by applying path fusion and path optimization. Theoretically, path fusion will only be optimal if there is always a unique/different path to be fused with the previously obtained path. However, in the conditions of solving path planning problems in narrow corridors, the potential for obtaining a different path from the previous one is very small. So that fusion does not run properly, but checking the relationship between nodes to nodes still occurs. Instead of getting an optimal path in conditions like this, the computation will increase, the solution time will be long, and the resulting path will still be sub-optimal. As an effort to solve this problem, Grey Wolf Optimization (GWO) is involved through this study. While an initial path is found, the beacons are repositioned. From the path, the number of nodes is unpredictable, causing the decision variables in optimization to become large. For this reason, the GWO is chosen because it is independent of population representation and is not affected by the number of decision variables. This proposed method is claimed to be more effective in solving path planning problems in terms of convergence rate and optimality. Therefore, the proposed method is evaluated and compared with previous methods and gives the result that the average working speed of Fast-RRT is improved by 90.25% and the optimality average increased by 5.67%.
Design a capacitor bank using load flow analysis to improve power factor correction in the food industry Malik, Mochamad Irlan; Adriansyah, Andi; Yanti, Yanti
Journal of Integrated and Advanced Engineering (JIAE) Vol 4, No 2 (2024)
Publisher : Akademisi dan Saintis Indonesia (ASASI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51662/jiae.v4i2.159

Abstract

The impact of installing a capacitor bank on the performance of an electrical system is evaluated through the analysis of changes in active power, reactive power, voltage, and power factors at various buses. The analysis indicates that the addition of the capacitor bank results in a significant increase in active power and a substantial reduction in reactive power. At Bus 1 (20 kV), active power increased from 648.93 kW to 687.38 kW, while reactive power decreased from 613.19 kVAR to 124.24 kVAR. At Bus 2 (0.4 kV), active power from 635.65 kW to 679.25 kW, and reactive power dropped from 560.59 kVAR to 92.046 kVAR. Voltage levels remained stable or slightly increased, and the power factor showed significant improvement, rising from 72.684% to 98.046% on Bus 1 and from 75.000% to 99.094% at Bus 2. Overall, the capacitor bank enhances system efficiency by optimizing power usage and reducing reactive power.
Design of path planning robot simulator by applying sampling based method Suwoyo, Heru; Andika, Julpri; Adriansyah, Andi
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.016

Abstract

This research aims to create a simulator for solving the global path planning of mobile robots. Various sampling-based methods such as Rapidly-exploring Random Tree (RRT), RRT*, and Fast-RRT, along with other derivative algorithms, have been widely used to solve path-planning problems in mobile robots. The level of computational efficiency, path optimality, and the ability to adapt to variant environments are some of the issues that still arise, although these techniques have shown good results in many cases. Although the existing solutions are innovative, comparison between the existing methods is still difficult due to significant differences in convergence speed, implementation complexity, and quality of the resulting paths. This makes choosing the most suitable method for a particular application difficult. The simulator uses sampling-based path planning algorithms such as RRT*, Fast RRT*, RRT*-Smart, informed-RRT*, and Honey Bee Mating Optimization-based Fast-RRT*. With this simulator, users can easily compare the performance of each algorithm and see the characteristics and efficiency of each algorithm in various situations. By running all methods through this simulator, the user can easily compare the methods based on convergence speed and optimality. Therefore, it will effectively help users understand robot navigation, improve the quality of learning, and promote the development of path-planning technology for mobile robots.