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All Journal Budimas : Jurnal Pengabdian Masyarakat Inspiring: English Education Journal Jurnal Sosiohumaniora Kodepena (JSK) Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Tarling : Journal of Language Education Jurnal Teknologi dan Manajemen Industri Terapan Jurnal Ilmu Pendidikan dan Sosial Open Community Service Journal Lentera El-Mujtama: Jurnal Pengabdian Masyarakat Journal of Informatics and Computer Engineering Research
Rahmayani
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Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Public Health Social Sciences Other

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ANALISIS DIAGNOSA PENYAKIT PADA TANAMAN KAKAO DENGAN MENGGUNAKAN METODE YOLOV8 Syahrir, Syahrir; Hamzidah, Nurul Khaerani; Rahmayani
Journal of Informatics and Computer Engineering Research Vol. 2 No. 2 (2025)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v2i2.6017

Abstract

One of Indonesia's most important commodities, cocoa plants play a crucial role in both the agricultural and financial sectors. In any event, this plant is particularly susceptible to a variety of diseases that can completely reduce its effectiveness, including stem cancer, VSD, natural product spoilage, and others. This article discusses how to use the YOLOv8 technique to develop a framework for sickness conclusion research in cocoa plants. The YOLOv8 computation was selected for this analysis due to its emphasis on handling speed and object recognition with high accuracy. The results showed that the YOLOv8 demonstration could accurately identify damage, reaching a 90% mAP. As a result of these developments, the produced show may be a useful tool to help farmers better monitor and control pest attacks. It is expected that using YOLOv8 to identify damage to cocoa natural products will result in a more effective plan for reducing the likelihood of lower yields from insect attacks.
Co-Authors Abdul Aziz Afrahul Fadilah AMZAH SELLE, AMZAH Andini Sinaga Andre Anwar Sani Arqam asupa, rani Athilya Putri Cah Dayani Saragih Caska - Cici Saleha malik Daimon Syukri Desniarti Haris Sunubi, Abd. Hendrika, Yan Husin Pratama, Rapli Indiraswari, Tika Jihan Farisa Karima, Raisa Kiswanda, Ratri Kuryani Leni Rosmita LINDAWATI Magdahalena Tjalla, Magdahalena Mutiara Namira Yusuf Nur Fika Herlina Nurul Khaerani Hamzidah Rahmawati Rama Wijaya, Rahmat Randi Reni Koja Rhamadani, Fitrah Risa Oktaviona Rizkyanto, Ridwan Rona Handayani Rosita Dongoran Rozi Thoyyiba Tampi Sandra Sept Sartika Dewi Septina, Ratna Sri Rosita Syahrir Syahrir Titok Wilyanzah Widia Fransiska Wiwit Yusnida Ritonga Zulfa