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All Journal BioEksakta : Jurnal Ilmiah Biologi Unsoed INTECH (Informatika dan Teknologi)
Anton Maulana Ibrahim
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Immunology & microbiology Veterinary

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Identifikasi Penyakit Tanaman Bawang Merah Varietas Bima Menggunakan Metode Forward Chainning Dan Certainty Factor Anton Maulana Ibrahim; Abdul Rahman
INTECH Vol 2 No 1 (2021): INTECH (Informatika Dan Teknologi)
Publisher : Program Studi Informatika Fakultas Teknik dan Komputer Universitas Baturaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (304.02 KB) | DOI: 10.54895/intech.v2i1.825

Abstract

Among the many causes of crop failure in shallots are pests and diseases, the symptoms of shallots that are attacked by pests are difficult to identify so only experts are able to correctly identify them. Shallots that are attacked by pests can actually be identified from the beginning until harvest, so that prevention and treatment can be done early on. This pest identification expert system documents expert skills into a computer. An expert system for identifying red onion diseases of the Bima Brebes variety was made using the forward chaining method based on the symptoms of the shallot plant. The certainty factor method is used to determine the level of expert confidence. System testing was carried out on 30 farmers and 5 extension workers to observe 12 samples of shallots that were attacked by pests and diseases. The system test results show that the system's accuracy level is 97%.
Keanekaragaman Serangga pada Tanaman Cabai Merah Di Desa Kubangwungu Kecamatan Ketanggungan Kabupaten Brebes Dwi Yuliani; Devi Ayu Susilowati; Anton Maulana Ibrahim
BioEksakta : Jurnal Ilmiah Biologi Unsoed Vol 3 No 2 (2021): BioEksakta
Publisher : Fakultas Biologi Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.bioe.2021.3.2.4278

Abstract

The increasing number of population and the growing food industry that requires raw material for red chilies have led to an increase in demand for red chilies. The research was conducted using a survey method which was carried out from February 2021 to April 2021. Sampling of insect diversity was carried out on 1,000 m2 of red chili plantations. The land for the red chili plants was determined by 10 points randomly. Each sampling point consisted of 2 pitfall traps, 1 light trap, and 1 insect net with 4 replications. Insect sampling was carried out when the chili plants began to enter the generative period (44-50 days after planting) for 6 consecutive days, in this phase the insect pests began to be seen in many chili plants. The results of the sampling were then identified using the J. Borror (1992) determination key book. Analysis of insect diversity data was carried out by calculating the diversity index (diversity) based on Magurran (1988) using the Shannon-Evenness Index and the Shannon-Evenness Index. The results showed that 28 species consisted of the order hemiptera, coleopteran, prthoptera, diptera, hymenoptera, odonata, mantodea, and Lepidoptera. The results showed that the diversity index of insect pollinators on red chili agricultural land using the pit fall method (H´ = 2.874) was lower than the light (H '= 3.029) and netting methods (H' = 3.0159), while the evenness index on land The pit fall method of red chili farming (E = 0.8627) was lower than the light method (E = 0.909) and netting method (E = 0.9481). Keywords: diversity, insects, red chilies
Identifikasi Penyakit Tanaman Bawang Merah Varietas Bima Menggunakan Metode Forward Chainning Dan Certainty Factor Anton Maulana Ibrahim; Abdul Rahman
INTECH (Informatika dan Teknologi) Vol 2 No 1 (2021): INTECH (Informatika Dan Teknologi)
Publisher : Informatics Study Program, Faculty of Engineering and Computers, Baturaja University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54895/intech.v2i1.825

Abstract

Among the many causes of crop failure in shallots are pests and diseases, the symptoms of shallots that are attacked by pests are difficult to identify so only experts are able to correctly identify them. Shallots that are attacked by pests can actually be identified from the beginning until harvest, so that prevention and treatment can be done early on. This pest identification expert system documents expert skills into a computer. An expert system for identifying red onion diseases of the Bima Brebes variety was made using the forward chaining method based on the symptoms of the shallot plant. The certainty factor method is used to determine the level of expert confidence. System testing was carried out on 30 farmers and 5 extension workers to observe 12 samples of shallots that were attacked by pests and diseases. The system test results show that the system's accuracy level is 97%.
Co-Authors Abdul Rahman Devi Ayu Susilowati Dwi YULIANI