Adam Jordan Lumbangaol


The main purpose of this study is to diagnose the types of pests and diseases on shallot plants due to climate change and weather carried out at the Department of Agriculture, Humbang Hasundutan district. Pests and diseases of shallot plants can be disturbed or infected by pests and diseases to other shallot plants so that farmers need to be wary of. Therefore, the dissemination of information about pests and diseases is very necessary to find out early on the types of pests and diseases in shallot plants due to climate and weather changes. Types of pests and diseases of shallots due to climate and weather changes are onion caterpillar (Spodoptera exiqua), leaf miner fly (Liriomyza chinensis), bodas pest (Thrips tabaci), purple spot (Alternaria porri), anthracnose (Cholletorichum gloesprorioiodes), dew , Mosaic disease or mole. So that it aims to produce an application-based expert system to diagnose pests and diseases on shallot plants due to climate and weather changes through the symptoms that occur in shallot plants. The methodology used for this research is the Bayes Theorem method. References from internet books and experts in their fields are Sumurung Toga Torop, who works at the Humbang Hasundutan Agriculture Service. As for the software using Visual Basic 2010 as its programming language, as well as Microsoft Access 2010.


How to Cite
Lumbangaol, A. J. (2020). Expert System for Diagnosing Pests and Diseases on Onion Crops due to Climate Change and Weather using Bayes’ Theorem Method. International Journal of Basic and Applied Science, 9(2), 29–33. https://doi.org/10.35335/ijobas.v9i2.12
A. Sumiahadi, M. Direk, and R. Acar, “Potential agro-industrial commodities for the development of Indonesia-Turkey economic partnership,” in IOP Conference Series: Earth and Environmental Science, 2021, vol. 637, no. 1, p. 12089.
L. Rist, L. Feintrenie, and P. Levang, “The livelihood impacts of oil palm: smallholders in Indonesia,” Biodivers. Conserv., vol. 19, no. 4, pp. 1009–1024, 2010.
P. B. M. M. B. BOTANI and V. TAMPO, “Sebagai Salah Satu Syarat Untuk Memperoleh Gelar Sarjana Pertanian Strata Satu (S-1).”
L. HERLINA, R. REFLINUR, S. SOBIR, A. MAHARIJAYA, and S. WIYONO, “The genetic diversity and population structure of shallots (Allium cepa var. aggregatum) in Indonesia based on R gene-derived markers,” Biodiversitas J. Biol. Divers., vol. 20, no. 3, pp. 696–703, 2019.
K. Prasetyowati, R. D. Kartikasari, and A. Prasetyo, “A feasibility study on cultivating shallots (Allium ascalonicum L) in Selo District, Boyolali Regency, Indonesia,” in IOP Conference Series: Earth and Environmental Science, 2021, vol. 824, no. 1, p. 12111.
N. S. Arifin, Y. Ozaki, and H. Okubo, “Genetic diversity in Indonesian shallot (Allium cepa var. ascalonicum) and Allium× wakegi revealed by RAPD markers and origin of A.× wakegi identified by RFLP analyses of amplified chloroplast genes,” Euphytica, vol. 111, no. 1, p. 23, 2000.
A. Supriyadi, I. R. Sastrahidayat, and S. Djauhari, “Kejadian penyakit pada tanaman bawang merah yang dibudidayakan secara vertikultur di Sidoarjo,” J. Hama dan Penyakit Tumbuh., vol. 1, no. 3, pp. 27–40, 2013.
R. Sunarya and D. D. S. Fatimah, “Pengembangan Sistem Pakar Diagnosis Hama dan Penyakit Pada Tanaman Bawang Merah Berbasis Android,” J. Algoritm., vol. 13, no. 1, pp. 84–91, 2016.
N. Sumarni, G. A. Sopha, and R. Gaswanto, “Respons tanaman bawang merah asal biji true shallot seeds terhadap kerapatan tanaman pada musim hujan,” J. Hortik., vol. 22, no. 1, pp. 23–28, 2012.
S. H. Poromarto, “Moler Disease of Shallot in the Last Three Years at Brebes Central Java: The Intensity and Resulting Yields Losses is Increasing,” in IOP Conference Series: Earth and Environmental Science, 2021, vol. 810, no. 1, p. 12004.
B. K. Udiarto, W. Setiawati, and E. Suryaningsih, “Pengenalan hama dan penyakit pada tanaman bawang merah dan pengendaliannya,” Pandu. Tek. PTT Bawang Merah, no. 2, 2005.
F. Sulvai, B. J. M. Chaúque, and D. L. P. Macuvele, “Intercropping of lettuce and onion controls caterpillar thread, Agrotis ípsilon major insect pest of lettuce,” Chem. Biol. Technol. Agric., vol. 3, no. 1, pp. 1–5, 2016.
W. S. Ginanjar, S. Bayu, and S. Aris, “Aplikasi Sistem Pakar Untuk Simulasi Diagnosa Hama dan Penyakit Tanaman Bawang Merah dan Cabai Menggunakan Forward Chaining dan Pendekatan Berbasis Aturan.” Master of Information System, 2011.
T. K. Moekasan, “SeNPV, Insektisida Mikroba untuk Pengendalian Hama Ulat Bawang (Spodoptera exigua),” Balai Penelit. Tanam. Sayuran. Lembang-Bandung, 1998.
M. W. Woolrich et al., “Bayesian analysis of neuroimaging data in FSL,” Neuroimage, vol. 45, no. 1, pp. S173–S186, 2009.
Z. Zhang, F. Hamagami, L. Lijuan Wang, J. R. Nesselroade, and K. J. Grimm, “Bayesian analysis of longitudinal data using growth curve models,” Int. J. Behav. Dev., vol. 31, no. 4, pp. 374–383, 2007.
N. Christensen, R. Meyer, L. Knox, and B. Luey, “Bayesian methods for cosmological parameter estimation from cosmic microwave background measurements,” Class. Quantum Gravity, vol. 18, no. 14, p. 2677, 2001.