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Jonathan Widodo Wiji Saputra
Universitas Negeri Malang, Indonesia
Religion Aerospace Engineering Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

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Implementasi Yolo V8 pada Prototipe Autonomous Underwater Robot Berbasis Raspberry Pi 5 Guna Menanggulangi Pencemaran Sampah Plastik di Daerah Perairan Jonathan Widodo Wiji Saputra; Muhammad Allam Naufal; Oditya Andalas Putra
Jurnal Syntax Admiration Vol. 5 No. 11 (2024): Jurnal Syntax Admiration
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jsa.v5i11.1775

Abstract

Plastic waste pollution in aquatic environments threatens marine ecosystems and human health. This study developed a prototype Autonomous Underwater Robot (AUR) based on Raspberry Pi 5, equipped with the YOLO V8 algorithm for real-time detection and classification of plastic waste. Additionally, the AUR uses a PID control system that enables movement stabilization and accurate navigation towards the target. Testing was conducted to evaluate object detection accuracy using mAP and IoU metrics, as well as the PID control performance in maintaining orientation stability. Results indicate that YOLO V8 on the AUR can detect and classify objects with an mAP of 0.6772 at IoU 0.5 and a detection accuracy of 89.6%. The PID control system, with an optimal parameter setting (Kp:Ki:Kd = 125:12:8), achieved an object center accuracy of 96.4%, orientation stability of 90.8%, and a completion time of 2 seconds, demonstrating the efficiency of the AUR in addressing plastic waste in aquatic environments effectively and sustainably.
Prototype of Smartglasses English Translator in the LSTM-Based Tourism Sector and Speech Recognition and Speech Synthesis Technology Jonathan Widodo Wiji Saputra; Achmad Hamdan
Jurnal Impresi Indonesia Vol. 4 No. 4 (2025): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v4i4.6420

Abstract

Language barriers remain a significant challenge in the tourism sector, particularly in Indonesia, where communication between international tourists and local service providers often faces difficulties due to limited English proficiency. Existing translation tools, such as mobile apps and standalone devices, suffer from limitations like reliance on internet connections, one-way communication, and the need for additional devices. This research aims to develop a smart glasses prototype that integrates speech recognition, Long Short-Term Memory (LSTM)-based translation, and speech synthesis technologies to offer real-time, bidirectional communication. The prototype development involved several stages: literature review, design, tool collection, prototyping, and testing using the Tatoeba dataset, which includes 13,570 English-Indonesian sentence pairs. The smart glasses prototype was tested for translation accuracy, speech recognition, and synthesis performance, yielding BLEU scores of 36.5% for Indonesian-English and 39.8% for English-Indonesian, with accuracy rates of 80.8% and 87.8%, respectively. The prototype demonstrated effective real-time translation with speech-to-text and text-to-speech functionalities. These results show that the smart glasses prototype can significantly improve the quality of communication between tourists and local communities, enhancing the competitiveness of Indonesia's tourism industry. The study implies that wearable translation devices could become essential tools in tourism, reducing language barriers and fostering better cross-cultural interactions.
Co-Authors Achmad Hamdan Muhammad Allam Naufal Oditya Andalas Putra