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Control System for U-Arm Robot Arm Movement with Linear Gripper Based on Inverse Kinematic Method Prasetyo, Aditya Putra Perdana; Rahmatullah, Ikang; Exaudi, Kemahyanto; Rendyansyah, Rendyansyah
JITCE (Journal of Information Technology and Computer Engineering) Vol 8 No 2 (2024): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.2.97-103.2024

Abstract

This research presents the development of a U-Arm model robot with three degrees of freedom, utilizing Inverse Kinematic calculations. The novelty of this project lies in its precise control of the robot arm's movements through advanced kinematic algorithms. Inverse Kinematics is a mathematical process used to determine the joint angles of the robot arm from known (x, y, z) coordinates of the end-effector and the lengths of each link. The robotic arm consists of four links with lengths of 8.2 cm, 15 cm, 16 cm, and 18.4 cm, respectively, and is equipped with a gripping module for object manipulation. The methodology involves calculating the joint angles required for the desired end-effector position, ensuring accurate and efficient movement. Testing results indicate an average coordinate error of 7.13%, demonstrating the system's precision and reliability. This error rate provides valuable insights into the performance and potential areas for improvement in the kinematic model. Additionally, this research includes the development of a program to control the servo motor speed using For and delay functions. This program enhances the robot's operational efficiency by allowing precise speed adjustments, which are crucial for various applications. Overall, this study contributes to the field of robotics by offering a detailed analysis of kinematic control and program development for a multi-link robotic arm, highlighting its potential for practical applications.
Control System for U-Arm Robot Arm Movement with Linear Gripper Based on Inverse Kinematic Method Prasetyo, Aditya Putra Perdana; Rahmatullah, Ikang; Exaudi, Kemahyanto; Rendyansyah, Rendyansyah
JITCE (Journal of Information Technology and Computer Engineering) Vol. 8 No. 2 (2024)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.2.97-103.2024

Abstract

This research presents the development of a U-Arm model robot with three degrees of freedom, utilizing Inverse Kinematic calculations. The novelty of this project lies in its precise control of the robot arm's movements through advanced kinematic algorithms. Inverse Kinematics is a mathematical process used to determine the joint angles of the robot arm from known (x, y, z) coordinates of the end-effector and the lengths of each link. The robotic arm consists of four links with lengths of 8.2 cm, 15 cm, 16 cm, and 18.4 cm, respectively, and is equipped with a gripping module for object manipulation. The methodology involves calculating the joint angles required for the desired end-effector position, ensuring accurate and efficient movement. Testing results indicate an average coordinate error of 7.13%, demonstrating the system's precision and reliability. This error rate provides valuable insights into the performance and potential areas for improvement in the kinematic model. Additionally, this research includes the development of a program to control the servo motor speed using For and delay functions. This program enhances the robot's operational efficiency by allowing precise speed adjustments, which are crucial for various applications. Overall, this study contributes to the field of robotics by offering a detailed analysis of kinematic control and program development for a multi-link robotic arm, highlighting its potential for practical applications.
Design of a Drowsiness Prevention Helmet with Vibration and IoT-Based Theft Detection Alarms Prasetyo, Aditya Putra Perdana; Sitorus, Harlis Richard; Isnanto, Rahmat Fadli; Hermansyah, Adi
JITCE (Journal of Information Technology and Computer Engineering) Vol. 8 No. 1 (2024)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.1.19-29.2024

Abstract

Ensuring safety while riding a motorbike is an imperative task. Currently, safety products such as helmets have the capability to provide protection to users without the additional feature of issuing warnings. Consequently, a preemptive alert system is developed to offer timely notifications to drivers. The experimental setup involves the utilization of a Max30100 sensor that is linked to a microcontroller and integrated into a helmet. The objective of this final project is to offer a timely alert to the rider and utilize the Max30100 sensor for pulse detection in order to ascertain the normalcy of the rider's pulse. In instances where the rider encounters tiredness and fatigue, it is common for the pulse intensity to exhibit a reduction. The Blynk application presents the detection pulse findings on the smartphone screen, while the buzzer on the helmet will activate in response to vibrations and sounds once the pulse has diminished. Based on testing, the average pulse rate on quiet road conditions is 78.58 BPM. On busy road conditions, the average pulse rate is 73.25 BPM. While in traffic conditions, the average pulse rate is 73.5 BPM. The helmet theft detector uses a Sharp GP2Y0A21 sensor that can only detect object distances up to 10 cm.
Heart Rate and Oxygen Saturation Internet of Things System (HROS-IoT) Uses Fuzzy Logic Hermansyah, Adi; Habibi, Ismail; Afifah, Nurul; Azhar, Iman Saladin B; Prasetyo, Aditya Putra Perdana; Maulida, Mutia Nadra
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4330

Abstract

Emergencies in hospitals, including in-hospital cardiac arrest (IHCA), necessitate effective response systems for monitoring vital signs such as heart rate and oxygen saturation. This study aims to develop and evaluate a Heart Rate and Oxygen Saturation Internet of Things (HROS-IoT) system utilizing the MAX30102 sensor and ESP32 microcontroller for real-time health monitoring. The system transmits data to the Blynk application via WiFi, enabling remote monitoring. Testing involved comparing the HROS-IoT system's performance against the commercial LK87 oximeter in measuring heart rate and oxygen saturation before and after meals with five participants. Results indicated that the HROS-IoT system produced heart rate measurements with an average error of 5.2 BPM before meals and 11.3 BPM after meals. Oxygen saturation readings showed an average error of 1% before meals and after meals. Despite minor discrepancies influenced by individual physiological differences and environmental conditions, the HROS-IoT system consistently delivered reliable data. The system's real-time monitoring capability and remote data access enhance proactive health management in hospitals. This study demonstrates the potential of the HROS-IoT system to improve patient outcomes and safety, suggesting further refinements for better accuracy and integration into healthcare settings.
Sistem Kendali Sirkulasi Udara dan Pembatasan Jumlah Pelanggan Toko Berbasis IoT Hanif, Labiq Al; Prasetyo, Aditya Putra Perdana; Ubaya, Huda
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.02.81-92.2021

Abstract

The emergence of the COVID-19 pandemic in early 2020 had a major impact on human life on a global scale. Many actions and policies are aimed at anticipating transmission and breaking the chain of the spread of the COVID-19 virus, thus requiring store owners to implement various health protocols. This study discusses the monitoring system for the condition of the storeroom in real-time with the IoT concept, and the implementation of Sugeno fuzzy logic in controlling the speed of the exhaust fan motor to circulate air in the room and limit the number of customers during the COVID-19 pandemic based on conditions of temperature, humidity, and many people in the storeroom. The actual test results from the implementation of Sugeno fuzzy logic show that the system has good performance in controlling the speed of the exhaust fan and limiting the number of customers based on the level of danger of the potential COVID-19 transmission in the room automatically and can monitor the condition of the room through the Thinger.io website in real time.
The Role of Image Generative Artificial Intelligence in Optimizing Digital Visual Assets for Animation and Motion Graphics Content B Azhar, Iman Saladin; Sari, Winda Kurnia; Exaudi, Kemahyanto; Prasetyo, Aditya Putra Perdana
REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Vol 6, No 2 (2025): Reka Elkomika
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/rekaelkomika.v6i2.162-172

Abstract

This Community Service Program (PKM) was conducted to introduce and promote the use of Motion Graphics and Image Generative AI technologies as innovative tools to support digital content creation, particularly in the context of industry and government institutions. Through a workshop format, participants were provided with an overview of how these technologies can improve the quality, clarity, and appeal of visual communication. The session included a conceptual explanation of Image Generative AI, such as Adobe Firefly, which allows users to generate visual assets through text prompts, and Adobe After Effects, a powerful tool for producing dynamic animations and motion graphics. Participants actively followed the material presented and showed interest in how these tools can be applied in real-world promotional or branding efforts. The workshop concluded that integrating these technologies holds great potential for enhancing institutional communication strategies. Future programs are expected to include more hands-on and practice-oriented sessions to further develop participants’ digital production skills.
Implementation of Feature Selection for Optimizing Voice Detection Based on Gender using Random Forest Abdurahman; Vindriani, Marsella; Prasetyo, Aditya Putra Perdana; Sukemi; Buchari, M. Ali; Sembiring, Sarmayanta; Firnando, Ricy; Isnanto, Rahmat Fadli; Exaudi, Kemahyanto; Dudifa, Aldi; Riyuda, Rafki Sahasika
Computer Engineering and Applications Journal (ComEngApp) Vol. 14 No. 2 (2025)
Publisher : Universitas Sriwijaya

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

Abstract

Gender-based voice detection is one of the machine learning applications that has various benefits in technology and services, such as virtual assistants, human-machine interaction systems, and voice data analysis. However, the use of too many features, including irrelevant features, can cause a decrease in accuracy and model performance. This research aims to optimize voice-based gender detection by applying a feature selection method to select significant features based on their correlation value to the target. Experimental results show that by using only the significant features selected through correlation analysis, the accuracy of the model is significantly improved compared to using all available features. This research confirms the importance of feature optimization to support the development of more efficient and accurate gender-based speech detection models.