SYSTEMATIC LITERATURE REVIEW (SLR): DISEASE DETECTION IN MELONS USING DIGITAL IMAGE PROCESSING

Authors

  • Frieyadie Frieyadie STMIK Nusa Mandiri
(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v3i1.52

Keywords:

digital image, leaves, melon disease, stematic literature review

Abstract

Abstract¾Systematic Literature Review (SLR) is a technique used in this study that is used to study techniques for identifying leaf diseases using digital images as a basis for obtaining an understanding of disease identification techniques in melon leaves with digital images. Based on data from the Central Statistics Agency for the last 3 years from 2017-2019, melon production has increased considerably. Melon production data in 2017 was 92.43 tons, in 2018 was 118,708 and in 2019, overall melon production was 122,105 tons collected from 34 provinces in Indonesia. The problem that is often encountered in melon cultivation is the presence of plant pests that can harm and not maximize the yields of farmers. Several viruses cause mosaic disease that infects Cucurbitaceae plants, namely Cucumber aphid borne yellows virus (CABYV), Cucumber green mottle mosaic virus (CGMMV), Cucumber mosaic virus (CMV), Papaya ringspot virus (PRSV), Squash mosaic virus (SqMV), Squash leaf curl virus (SLCV), Watermelon mosaic virus (WMV). Information technology has now developed to be able to manage digital image data to identify problems faced by farmers. Several classification methods that can be used to answer problems include SVM, Artificial Neural Network, Decision Tree, Convolutional Neural Network.

Downloads

Download data is not yet available.

References

Alfio, V. S., Costantino, D., & Pepe, M. (2020). Influence of image tiff format and jpeg compression level in the accuracy of the 3d model and quality of the orthophoto in UAV photogrammetry. Journal of Imaging, 6(5). https://doi.org/10.3390/jimaging6050030

Bhat, M. (2014). Digital Image Processing. International Journal of Scientific & Technology Research, 3(1), 1–5. Retrieved from http://www.ijstr.org/paper-references.php?ref=IJSTR-0114-8118

Chandrashekar, G., & Sahin, F. (2014). A survey on feature selection methods. Computers and Electrical Engineering, 40(1), 16–28. https://doi.org/10.1016/j.compeleceng.2013.11.024

Desai, B., Kushwaha, U., & Jha, S. (2020). Image Filtering-Techniques, Algorithm, and Applications. GIS Science Journal, 7(11), 970–975.

Dey, S. (2018). No CNN application on structured data-Automated Feature Extraction. Retrieved from Towards Data Science website: https://towardsdatascience.com/cnn-application-on-structured-data-automated-feature-extraction-8f2cd28d9a7e

Encyclopedia.com. (2019, April 16). Analogue Image. Retrieved April 20, 2021, from A Dictionary of Earth Sciences website: https://www.encyclopedia.com/science/dictionaries-thesauruses-pictures-and-press-releases/analogue-image

Fisher, R., Perkins, S., Walker, A., & Wolfart, E. (2000). Glossary - Color Images. Retrieved April 20, 2021, from homepages.inf.ed.ac.uk website: https://homepages.inf.ed.ac.uk/rbf/HIPR2/colimage.htm

Jayapriya, P., & Hemalatha, S. (2019). Comparative Analysis of Image Segmentation Techniques and Its Algorithm. International Journal of Scientific and Technology Research, 8(10), 2209–2212.

Jumeilah, F. S. (2017). Penerapan Support Vector Machine (SVM) untuk Pengkategorian Penelitian. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 1(1), 19. https://doi.org/10.29207/resti.v1i1.11

Karthick, S., Sathiyasekar, D. K., & Puraneeswari, A. (2014). A Survey Based on Region-Based Segmentation. International Journal of Engineering Trends and Technology, 7(3), 143–147. https://doi.org/10.14445/22315381/ijett-v7p262

Khuluq, M., Phabiola, T. A., & Wijaya, I. N. (2020). Penularan Virus Bergejala Mosaik Pada Tanaman Melon (Cucumis melo L.) Secara Mekanis dan Melalui Vektor Kutu Daun. Jurnal Agroekoteknologi Tropika, 9(1), 76–86.

Langgeni, D. P., Abdurahman Baizal, Z. K., & Firdaus, Y. (2010). Clustering Artikel Berita Berbahasa Indonesia Menggunakan Unsupervised Feature Selection. Seminar Nasional Informatika 2010 (SemnasIF 2010) , 1(4), 1–10. Yogyakarta: UPN ”Veteran” Yogyakarta. Retrieved from http://jurnal.upnyk.ac.id/index.php/semnasif/article/view/1175

Mutlag, W. K., Ali, S. K., Aydam, Z. M., & Taher, B. H. (2020). Feature Extraction Methods: A Review. Journal of Physics: Conference Series, 1591(1). https://doi.org/10.1088/1742-6596/1591/1/012028

Neetu Rani. (2017). Image Processing Techniques: A Review. Journal on Today’s Ideas - Tomorrow’s Technologies, 5(1), 40–49. https://doi.org/10.15415/jotitt.2017.51003

Solikin. (2020). Deteksi Penyakit Pada Tanaman Mangga Dengan Citra Digital : Tinjauan Literatur Sistematis ( SLR ). Bina Insani Ict Journal, 7(1), 63–72.

The University of Michigan Library. (2021, February 11). Image File Formats - All About Images. Retrieved April 20, 2021, from Research Guides at University of Michigan Library website: https://guides.lib.umich.edu/c.php?g=282942&p=1885348

Wedianto, A., Sari, H. L., & H, Y. S. (2016). Analisa Perbandingan Metode Filter Gaussian, Mean Dan Median Terhadap Reduksi Noise. Jurnal Media Infotama, 12(1), 21–30. https://doi.org/10.37676/jmi.v12i1.269

Wilisiani, F., Somowiyarjo, S., & Hartono, S. (2014). Identifikasi Molekuler Virus Penyebab Penyakit Daun Keriting Isolat Bantul pada Melon. Identifikasi Molekuler Virus Penyebab Penyakit Daun Keriting Isolat Bantul Pada Melon, 18(1), 47–54. https://doi.org/10.22146/jpti.15602

Downloads

Published

2020-12-13

How to Cite

Frieyadie, F. (2020). SYSTEMATIC LITERATURE REVIEW (SLR): DISEASE DETECTION IN MELONS USING DIGITAL IMAGE PROCESSING. Jurnal Riset Informatika, 3(1), 75–80. https://doi.org/10.34288/jri.v3i1.52

Most read articles by the same author(s)