YOLOv8 Based Object Detection for Chili Plant Diseases
DOI:
https://doi.org/10.56480/jln.v5i3.1600
Abstract View:
64
PDF downloads:
67
Keywords:
Yolov8, Object Detection, Leaf Disease, Cayenne PepperAbstract
Indonesia is classified as an agricultural country, where agriculture plays an important role in supporting national development and meeting the needs of the population. Among horticultural crops, cayenne pepper (Capsicum annuum L.) has high economic value and is an important source of income for farmers. Indonesia is also one of the largest chili consumer countries in the world. According to data from the Central Statistics Agency (BPS), national cayenne pepper production reached 1.55 million tons in 2022, an increase of 11.5% from 1.39 million tons in the previous year. However, the price of cayenne pepper can fluctuate significantly, often rising sharply when production declines. One of the main factors causing a decrease in yields is the prevalence of plant diseases such as curly leaves, leaf spots, and yellowing. These diseases greatly affect plant health and reduce the quality and quantity of the harvest. To answer this, this study aims to detect and classify diseases in cayenne pepper leaves using the YOLO (You Only Look Once) version 8 object detection algorithm. YOLO is a well-known computer vision model and is used to detect objects in real-time because it has speed and accuracy in identifying objects in images and video frames. With the application of YOLO, the types of diseases that attack chili plants can be identified accurately, so that monitoring and management of diseases can be carried out more effectively. The best level of accuracy obtained with YOLOv8 object detection has a large detection accuracy or mAP (Mean Average Precision) value of up to 0.887 or 88.7%.
References
Arsi, A., Octariati, N., Shk, S., Gunawan, B., Herlinda, S., Pujiastuti, Y., Suwandi, S., Irsan, C., Hamidson, H., Efendi, R. A., & Budiarti, L. (2020). Pengaruh Teknik Budidaya terhadap Serangan Penyakit Pada Tanaman Cabai Rawit (Capsicum frutescens L.) Di Kecamatan Lempuing, Kabupaten Ogan Komering Ilir: Effect of Cultural Technique on Disease of Cayenne Pepper (Capsicum frutescens L.) in Sub District Lempuing, Distict Ogan Komering Ilir. J-Plantasimbiosa, 2(2), Article 2. https://doi.org/10.25181/jplantasimbiosa.v2i2.1741 Hussain, M. (2023). YOLO-v1 to YOLO-v8, the Rise of YOLO and Its Complementary Nature toward Digital Manufacturing and Industrial Defect Detection. Machines, 11(7), Article 7. https://doi.org/10.3390/machines11070677 Ibrahim, M. A. F., Ahmad, R. A., Ansir, V. R., & Latif, A. (2022). Analisis Eksistensi Hasil Produksi Cabai Rawit di Provinsi Gorontalo. YUME : Journal of Management, 5(3), Article 3. https://doi.org/10.37531/yum.v5i3.3318 Paulus A., P., & Ellen G., T. (2016). FAKTOR-FAKTOR YANG MEMPENGARUHI HARGA CABAI RAWIT DI KOTA MANADO. AGRI-SOSIOEKONOMI, 12(2), Article 2. https://doi.org/10.35791/agrsosek.12.2.2016.12278 Polii, M. G. M., Sondakh, T. D., Raintung, J. S. M., Doodoh, B., & Titah, T. (2019). KAJIAN TEKNIK BUDIDAYA TANAMAN CABAI (Capsicum annuum L.) KABUPATEN MINAHASA TENGGARA. EUGENIA, 25(3), Article 3. https://doi.org/10.35791/eug.25.3.2019.31402 Rachmawati, F., & Widhyaestoeti, D. (2020). Deteksi Jumlah Kendaraan di Jalur SSA Kota Bogor Menggunakan Algoritma Deep Learning YOLO. PROSIDING LPPM UIKA BOGOR. https://pkm.uika-bogor.ac.id/index.php/prosiding/article/view/657 Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You Only Look Once: Unified, Real-Time Object Detection. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 779–788. https://doi.org/10.1109/CVPR.2016.91 Reis, D., Kupec, J., Hong, J., & Daoudi, A. (2024). Real-Time Flying Object Detection with YOLOv8 (arXiv:2305.09972). arXiv. https://doi.org/10.48550/arXiv.2305.09972 Simbolon, T. G. (n.d.). Data Harga Pangan: Daging Ayam hingga Beras Naik, Cabai Rawit Turun (23 Mei 2025). Data Indonesia: Data Indonesia for Better Decision. Valid, Accurate, Relevant. Retrieved June 12, 2025, from https://dataindonesia.id/komoditas/detail/data-harga-pangan-23-mei-2025 Wehfany, F. Y., Timisela, N. R., & Luhukay, J. M. (2022). Analisis Faktor Yang Mempengaruhi Pendapatan Usahatani Cabai Rawit (Capsicum frutescens L.). JURNAL AGRICA, 15(2), Article 2. https://doi.org/10.31289/agrica.v15i2.7314
Downloads
Published
How to Cite
License
Copyright (c) 2025 Muhammad Rima Mustaghfirin Bil Ashar, Basuki Rahmat , Hendra Maulana
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright Notice
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
