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All Journal Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo) JURNAL TEKNIK INDUSTRI
Arief Suryadi Satyawan
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Other

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Pengembangan Software Aplikasi Pendeteksian Objek Berbasis LiDAR (Light Detection and Ranging) (Development of Lidar-Based Object Detection Software) Raden Aditya Satria Nugraha; Denden Mohammad Arifin; Arief Suryadi Satyawan; Mohammed Ikrom Asysyakuur; Nafisun Nufus; Ni Nyoman Ayu Marlina Santi; Achmadan Habibi
Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (SENASTINDO) Vol 3 (2021): Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo)
Publisher : Akademi Angkatan Udara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (502.889 KB) | DOI: 10.54706/senastindo.v3.2021.120

Abstract

The car is a means of transportation whose needs are getting higher. This situation is not only happening abroad but also in Indonesia. However, the car's existence is currently complained about because of the pollution it produces and the level of comfort. Expectations in the future seem to be more directed at electric cars with deficient pollution levels and convenience in their use, such as autonomous electric cars. Therefore, we must master the technology of autonomous electric vehicles to enter the era of Mobility in Society 5.0. One form of related technology is a LiDAR-based object detection software system. Sometimes, the software accompanying a tool cannot provide various facilities according to the field's application needs. This condition is due to the manufacturer's limitations, likewise with 2D LiDAR products widely marketed, for example, YDLiDAR. For object detection applications, the provided software has limitations in data storage, flexibility in data presentation, and the ability to reduce noise when the LiDAR is operated under certain conditions. This study developed LiDAR-based object detection software to overcome the shortcomings mentioned above by adding the functions discussed above and applying them to object detection and distance recognition. In general, this system combines a software system developed on a laptop with a hardware system consisting of YDLiDAR G4 and a serial data interface. This software system was also created using the python programming language. The measurement results show that the performance of the software developed has good visual performance. This software can store detection data for a specified duration and suppress noise, which is quite good. The noise reduction capability of this software system can reduce errors up to 19.2%.
Adaptive Occupational Safety Mechanism for Autonomous Material Handling: A Zone-Based Dynamic Risk Assessment Approach Fathin, Muhammad Alif Fathin; Azhima , Silmi Ath Thahirah Al Azhima; Arief Suryadi Satyawan; Haritman, Erik Haritman
JURNAL TEKNIK INDUSTRI Vol. 16 No. 1 (2026): March 2026
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Indusri Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/jti.v16i1.24922

Abstract

The integration of Autonomous Guided Vehicles (AGVs) into shared industrial workspaces requires robust safety mechanisms to mitigate collision risks without compromising operational efficiency. Conventional binary safety systems often trigger abrupt emergency stops, leading to mechanical wear and production bottlenecks. This study aims to develop an adaptive decision-making framework for AGV safety based on real-time spatial risk assessment. The proposed approach uses a 3D LiDAR sensor to map unstructured environments and employs the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to identify dynamic obstacles. A multi-tiered risk zone logic—comprising Danger, Caution, and Ready zones—is implemented to regulate braking responses compliant with ISO 12100 standards autonomously. Experimental validation was conducted through static, linear, and complex non-linear trajectory scenarios. Results indicate that the system successfully eliminates environmental noise and maintains continuous object tracking during erratic movements, triggering gradual deceleration rather than abrupt halts in non-critical situations. This research contributes a scalable safety protocol that enhances Occupational Health and Safety (OHS) compliance while maintaining smoother intralogistics flow on the production floor.
Co-Authors Achmadan Habibi Azhima , Silmi Ath Thahirah Al Azhima Denden Mohammad Arifin Fathin, Muhammad Alif Fathin Haritman, Erik Haritman Mohammed Ikrom Asysyakuur Nafisun Nufus Ni Nyoman Ayu Marlina Santi Raden Aditya Satria Nugraha