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All Journal Jurnal Buana Informatika Indonesian Journal of Information System Journal of Computer System and Informatics (JoSYC) J-Intech (Journal of Information and Technology)
Saragih, Raymond Erz
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Library & Information Science

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Utilizing Lightweight YOLOv8 Models for Accurate Determination of Ambarella Fruit Maturity Levels Simanjuntak, Nurchaya; Saragih, Raymond Erz; Pernando, Yonky
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5123

Abstract

In the agricultural sector, accurately determining fruit ripeness remains a crucial yet challenging task. Among intriguing Indonesian fruits, the Ambarella presents a particular difficulty. In Ambarella fruit, the peel changes from green to golden yellow as it ripens, serving as a visual indicator for optimal harvest time, thus determining the maturity is crucial for harvesting the Ambarella fruit. Traditionally, ripeness assessment relies on manual methods, which suffer from drawbacks like high labor costs, significant time investment, and inconsistency in results. This work explores the potential of employing YOLOv8, a cutting-edge deep learning model, to automate Ambarella fruit ripeness classification. This work focuses on the YOLOv8n, YOLOv8s, and YOLOv8m, lightweight models within the YOLOv8 family. Our results are promising: all three models achieved 100% accuracy on the training set, with YOLOv8s demonstrating the lowest loss at 0.00286. The web application was utilised to deploy the trained models, allowing users to upload images of Ambarella fruit and run the model for inference.
Mango and Banana Ripeness Detection based on Lightweight YOLOv8 Saragih, Raymond Erz; Purnajaya, Akhmad Rezki; Syafrinal, Ilwan; Pernando, Yonky; Yodi
Jurnal Buana Informatika Vol. 15 No. 2 (2024): Jurnal Buana Informatika, Volume 15, Nomor 02, Oktober 2024
Publisher : Universitas Atma Jaya Yogyakarta

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Abstract

Fruits like bananas and mangoes are harvested after reaching a specific ripeness stage. Traditionally, farmers rely on manual inspection to determine ripeness, a process that can be tedious, time-consuming, expensive, and subjective. This work proposes an automatic bananas and mangoes ripeness detector utilizing computer vision technology. The detected bananas and mangoes fall into two classes: ripe and unripe. The state-of-the-art YOLOv8 architecture serves as the core of the detector. Three YOLOv8 variants, YOLOv8n, YOLOv8s, and YOLOv8m, were investigated for their performance. Results show that YOLOv8s achieved the highest overall performance, 0.9991 recall, and a mean Average Precision (mAP) of 0.8897. While YOLOv8m achieved the highest precision of 0.9995, YOLOv8n is the most miniature model, making it suitable for deployment on devices with limited resources.
Perancangan Aplikasi Manajemen Proyek Pada PT. Sintech Berkah Abadi Berbasis Web Roza, Yuni; Pernando, Yonky; Saragih, Raymond Erz; Kaharuddin, Kaharuddin; Verdian, Ihsan
J-INTECH (Journal of Information and Technology) Vol 11 No 1 (2023): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v11i1.868

Abstract

Project management is the activity of organizing, leading, and controlling company resources to achieve desired goals. PT. Sintech Berkah Abadi greatly needs such a system to support and improve services for the satisfaction of both employees and customers in their company's project activities. As a company operating in the software provider industry in the global market, offering business solutions with advanced technology, they face various challenges in data processing. These challenges include data errors or losses occurring in various stages such as application creation, data processing, approval processes, and project reporting. Therefore, PT. Sintech Berkah Abadi requires a web-based project management system application. The data collection methods used in this research are observation, interviews, and literature review, while the analysis method used is SWOT. The implementation of this project management system application can provide a solution for the company, making work processes more effective and efficient.
Coral Detection based on Optimised Lightweight YOLO Model Saragih, Raymond Erz; Husin, Husna Sarirah; Mursalim, Muhammad Khairul Naim; Yodi
Indonesian Journal of Information Systems Vol. 8 No. 1 (2025): August 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v8i1.11628

Abstract

Coral reefs are essential marine ecosystems that face significant threats due to climate change, pollution, and overfishing. Effective monitoring is crucial for conservation efforts, but traditional methods are labor-intensive and inefficient. This study proposes a deep learning-based coral detection model built based on the YOLOv8 architecture, specifically for nano and small. In addition, the Ghost modules and Ghost bottlenecks were utilized to modify the original YOLOv8 small. The proposed model was trained on an underwater coral dataset and evaluated in terms of precision, recall, and mean Average Precision (mAP) metrics. Experimental results demonstrate that the YOLOv8 small model and YOLOv8 small model with Ghost modules achieved a mAP of 53.675% and 55.88%, respectively, while maintaining a compact model size. This work contributes to developing efficient and lightweight coral detection systems to support conservation efforts.
Co-Authors Husin, Husna Sarirah Ilwan Syafrinal Kaharuddin MUHAMMAD KHAERUL NAIM MURSALIM Pernando, Yonky Purnajaya, Akhmad Rezki Roza, Yuni Simanjuntak, Nurchaya Verdian, Ihsan Yodi