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EXPERT SYSTEM DESIGN TO DIAGNOSE PESTS AND DISEASES ON LOCAL RED ONION PALU USING BAYESIAN METHOD

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 1 (2023) · hlm. 0371–0382

DOI
10.30598/barekengvol17iss1pp0371-0382
ISSN
2615-3017, 1978-7227
Terbit
2023-04-16
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Bayesian is a method that can be used to overcome the uncertainty of a situation or data. The information obtained must be continuously updated so that it can foster trust as a result of the uncertainty of those conditions. In this study, the application of the Bayesian method to detect early symptoms of diseases on local red onion Palu plants based on the symptoms that appear will be carried out. Information about pests and diseases that attack local red onion Palu is needed to help farmers. As a result, they can deal with attacked diseases quickly and precisely. This is crucial conducted by considering that this plant is one of the mainstay commodities for farmers in Central Sulawesi Province whose production must continue to be increased. Pests and diseases can be diagnosed through visible symptoms.The sample is local red onion Palu that affected by pests and disesases which planted in the AIAT of Central Sulawesi by experiment. As a result, through these symptoms an expert system can then be created to do a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The created expert system to diagnose diseases uses the Bayesian method to calculate the probability of an event occurring based on the obtained results from observations and experts. An expert system for diagnosis of pests and diseases is built on a web-based basis. This expert system has features and functions including the diagnosis of pests and diseases of the observed plants, viewing the results of the diagnosis and printing the results of the diagnosis. In addition, users can view information on pests and other diseases that attack plants. From the results of system testing that conducted by experts, this shows that the expert system is feasible to use to diagnose local red onion Palu plants which affected by pests and diseases with an accuracy point that has the largest percentage value.

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38 penulis · 97 tautan kepenulisan bersama · 20 lintas organisasi

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  • Tadulako University
  • Institut Teknologi Sepuluh Nopember
  • North Sumatra Islamic University
  • Medan Area University
  • Universitas Dharmawangsa
  • State University of Jakarta
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
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  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Hajra Rasmita NgembaAfiliasi tidak diketahui4
Rahmah LailaAfiliasi tidak diketahui2
Virga DamayantiTadulako University2
Junaidi JunaidiInstitut Teknologi Sepuluh Nopember2
Dini Aprilia AfrizaTadulako University2
Rais RaisTadulako University2
Hartayuni SainTadulako University2
Yudhi PurwanantoInstitut Teknologi Sepuluh Nopember1
Chastine FatichahInstitut Teknologi Sepuluh Nopember1
Syafruddin RitongaMedan Area University1
Hasrat Efendi SamosirNorth Sumatra Islamic University1
Muhammad LuthiUniversitas Dharmawangsa1
Eko NugrohoState University of Jakarta1
Yayang MatiraAfiliasi tidak diketahui1
JunaidiAfiliasi tidak diketahui1
Ghina Rizqa RaihanahTadulako University1
Junaidi JunaidiTadulako University1
Junaidi JunaidiTadulako University1
Nurul Fiskia GamayantiTadulako University1
Nur'eni Nur'eniTadulako University1
Rais RaisTadulako University1
Eliani ElianiTadulako University1
Muhammad Fajar RifaiAfiliasi tidak diketahui1
Ryfial AzharAfiliasi tidak diketahui1
Jonathan Albert UswaryAfiliasi tidak diketahui1
Anita Ahmad KasimAfiliasi tidak diketahui1
Yuri Yudhaswana JoefrieAfiliasi tidak diketahui1
Muh Alif AlghifariAfiliasi tidak diketahui1
Junus WidjajaAfiliasi tidak diketahui1
Muhammad YazdiAfiliasi tidak diketahui1
Syahrullah SyahrullahAfiliasi tidak diketahui1
Muhammad JindanAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">EXPERT SYSTEM DESIGN TO DIAGNOSE PESTS AND DISEASES ON  LOCAL RED ONION PALU USING BAYESIAN METHOD</dc:title>
	<dc:creator>Junaidi, Junaidi</dc:creator>
	<dc:creator>Fadjryani, Fadjryani</dc:creator>
	<dc:creator>Setiawan, Iman</dc:creator>
	<dc:creator>Batara, Mohammad</dc:creator>
	<dc:creator>Hendra, Syaiful</dc:creator>
	<dc:creator>Ismail, Nurmasita</dc:creator>
	<dc:description xml:lang="en-US">Bayesian is a method that can be used to overcome the uncertainty of a situation or data. The information obtained must be continuously updated so that it can foster trust as a result of the uncertainty of those conditions. In this study, the application of the Bayesian method to detect early symptoms of diseases on local red onion Palu plants based on the symptoms that appear will be carried out. Information about pests and diseases that attack local red onion Palu is needed to help farmers. As a result, they can deal with attacked diseases quickly and precisely. This is crucial conducted by considering that this plant is one of the mainstay commodities for farmers in Central Sulawesi Province whose production must continue to be increased. Pests and diseases can be diagnosed through visible symptoms.The sample is local red onion Palu that affected by pests and disesases which planted in the AIAT of Central Sulawesi by experiment. As a result, through these symptoms an expert system can then be created to do a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The created expert system to diagnose diseases uses the Bayesian method to calculate the probability of an event occurring based on the obtained results from observations and experts. An expert system for diagnosis of pests and diseases is built on a web-based basis. This expert system has features and functions including the diagnosis of pests and diseases of the observed plants, viewing the results of the diagnosis and printing the results of the diagnosis. In addition, users can view information on pests and other diseases that attack plants. From the results of system testing that conducted by experts, this shows that the expert system is feasible to use to diagnose local red onion Palu plants which affected by pests and diseases with an accuracy point that has the largest percentage value.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-04-16</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7234</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss1pp0371-0382</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications; 0371-0382</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss1year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7234/5543</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Junaidi Junaidi, Fadjryani Fadjryani, Iman Setiawan, Mohammad Batara, Syaiful Hendra, Nurmasita Ismail</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>