Sistem Deteksi Penyakit Alternaria Leaf Spot Pada Daun Apel Berdasarkan Warna dan Operasi Morfologi

  • Mutmainnah Muchtar Universitas Sembilanbelas November Kolaka http://orcid.org/0000-0002-1423-5375
  • Nur Fajriah Muchlis Universitas Sembilanbelas November Kolaka
  • Muliyadi Muliyadi Universitas Sembilanbelas November Kolaka
  • Rahmat Karim Universitas Sembilanbelas November Kolaka
  • Rima Ruktiari Universitas Sembilanbelas November Kolaka

Abstract

Indonesia is an agrarian country heavily reliant on agricultural commodities. Apples, in particular, hold significant importance in this agricultural context, making a substantial contribution to the nation's agricultural prosperity. However, the agricultural sector faces challenges, notably in the form of diseases like Alternaria Leaf Spot, which have the potential to adversely affect crop yields. This research introduces a system for detecting Alternaria Leaf Spot disease on apple leaves, utilizing RGB color space and mathematical morphology operations. Implementing a GUI-based approach through Matlab software, the system efficiently detects infected areas, achieving good performance with a precision value of 96.22% and a recall of 88.74%. The color-based segmentation process, combined with morphological operations, results in the generation of bounding boxes around infected areas. Evaluation using a dataset of 45 apple leaf images demonstrates success in detecting and quantifying leaf spots. These positive outcomes underscore the practical potential of the system in automating efficient monitoring of apple plant diseases, paving the way for further developments in image-based plant disease detection.

References

[1] D. Husen, K. Kusrini, and K. Kusnawi, “Deteksi Hama Pada Daun Apel Menggunakan Algoritma Convolutional Neural Network,” JURNAL MEDIA INFORMATIKA BUDIDARMA, vol. 6, no. 4, p. 2103, Oct. 2022, doi: 10.30865/mib.v6i4.4667.
[2] M. Afriansyah, J. Saputra, Y. Sa’adati, and V. Y. P. Ardhana, “Optimasi Algoritma Naive Bayes Untuk Klasifikasi Buah Apel Berdasarkan Fitur Warna RGB.,” Bulletin of Computer Science Research, vol. 3, no. 3, pp. 242–249, 2023, doi: 10.47065/bulletincsr.v3i3.251.
[3] S. Un Nabi, J. Iqbal Mir, W. Hassan Raja, M. A. Sheikh, O. Chand Sharma, and D. Beer Singh, “European Journal of Biotechnology and Alternaria leaf and fruit spot in apple: Symptoms, cause and management,” 2020, [Online]. Available: www.biosciencejournals.com
[4] J. Cabrefiga, M. V. Salomon, and P. Vilardell, “Improvement of Alternaria Leaf Blotch and Fruit Spot of Apple Control through the Management of Primary Inoculum,” Microorganisms, vol. 11, no. 1, Jan. 2023, doi: 10.3390/microorganisms11010101.
[5] X. Chao, G. Sun, H. Zhao, M. Li, and D. He, “Identification of apple tree leaf diseases based on deep learning models,” Symmetry (Basel), vol. 12, no. 7, Jul. 2020, doi: 10.3390/sym12071065.
[6] M. Astiningrum, P. P. Arhandi, and N. A. Ariditya, “IDENTIFIKASI PENYAKIT PADA DAUN TOMAT BERDASARKAN FITUR WARNA DAN TEKSTUR,” Jurnal Informatika Polinema, vol. 6, no. 2, pp. 47–50, 2020.
[7] M. Muchtar, “Penggabungan Fitur Dimensi Fraktal dan Lacunarity untuk Klasifikasi Daun,” Institut Teknologi Sepuluh Nopember, Surabaya, 2015.
[8] Y. P. Pasrun, M. Muchtar, A. N. Basyarah, and Noorhasanah, “Indonesian License Plate Detection Using Morphological Operation,” in IOP Conference Series: Materials Science and Engineering, Institute of Physics Publishing, Jun. 2020. doi: 10.1088/1757-899X/797/1/012037.
[9] D. A. Priandini, J. Nangi, M. Muchtar, and J. Y. Sari, “DETEKSI AREA PLAT MOBIL MENGGUNAKAN OPERASI MORFOLOGI CITRA,” in Semin. Nas. Teknol. Terap. Berbas. Kearifan Lokal, 2018, pp. 294–302.
[10] M. Muchtar, “DETEKSI AREA KERUSAKAN PADA CITRA TERUMBU KARANG AKIBAT CORAL BLEACHING BERBASIS PENGOLAHAN CITRA DIGITAL,” Jurnal Innovation and Future Technology (IFTECH) P-ISSN, vol. 5, pp. 2656–1719, 2023.
[11] H. D. Adoe, A. Y. Rahman, and I. Istiadi, “SEGMENTASI CITRA BURUNG LOVEBIRD MENGGUNAKAN K-MEANS,” Jurnal Teknik Informatika dan Sistem Informasi, vol. 10, no. 1, pp. 706–718, 2023.
[12] M. Muchtar, Y. P. Pasrun, R. Rasyid, N. Miftachurohmah, and M. Mardiawati, “PENERAPAN METODE NAÏVE BAYES DALAM KLASIFIKASI KESEGARAN IKAN BERDASARKAN WARNA PADA CITRA AREA MATA,” Jurnal Informatika dan Teknik Elektro Terapan, vol. 12, no. 1, Jan. 2024, doi: 10.23960/jitet.v12i1.3879.
[13] Y. Yohannes and R. Wijaya, “Klasifikasi Makna Tangisan Bayi Menggunakan CNN Berdasarkan Kombinasi Fitur MFCC dan DWT,” JATISI (Jurnal Teknik Informatika dan Sistem Informasi), vol. 8, no. 2, pp. 599–610, Jun. 2021.
[14] A. Jalil, I. P. Ningrum, and M. Muchtar, “SPK pemberian kredit menggunakan metode wp (weighted product) pada BMT Mu’amalah sejahtera kendari,” Jurnal Semantik, vol. 3, no. 1, pp. 173–180, 2017.
Published
2024-06-10