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All Journal JIEET (Journal of Information Engineering and Educational Technology) JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Jurnal Minfo Polgan (JMP) Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Informatika Polinema (JIP) Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Gameology and Multimedia Expert
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Universitas Malikussaleh
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Journal : Jurnal Computer Science and Information Technology (CoSciTech)

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Implementasi Metode Forward Chaining Dan Case Based Reasoning (CBR) Pada Sistem Pakar Diagnosa Penyakit Tanaman Padi (Oryza Sativa.L) Berbasis Web -, Cut Agusniar
Computer Science and Information Technology Vol 5 No 2 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i2.7361

Abstract

Rice is a plant that is very important for human survival, so this plant is widely cultivated in almost all regions of Indonesia. One of the obstacles in rice farming is pests and diseases that attack rice plants. However, rice farmers' knowledge about rice pests and diseases and their control is still lacking, especially for novice farmers. On the other hand, the number of instructors/experts regarding rice pests and diseases is still limited. Therefore, an expert system is needed which can be a problem solver in identifying pests and diseases of rice plants. In expert systems there are several methods that can be used, including the forward chaining method and case based reasoning (CBR). These two methods were chosen because they can solve problems easily, quickly and precisely. The greater the knowledge stored in the system, the more skilled the system becomes at finding a solution to a case. The result of this research is a website-based expert system using forward chaining and case based reasoning methods. The research used 10 types of rice diseases with 32 symptoms and tested the system using 20 test data resulting in an accuracy value of 95%, so that this system was declared able to be used to diagnose rice plant diseases.
Co-Authors Achriadi Sukiman, T Sukma Alaiya, Azna Aryanti, Leni Asran Asran b, bustami Dahlan Abdullah Dalimunthe, Rodiatul Adawiyah Della Adelia, Della Eva Darnila Ezwarsyah Ezwarsyah Fazira, Ira Fidyatun Nisa Fitri, Anisa Amelia Gemasih, Husna Ginting, Andriyan Herfia Rhomadhona Khaira, Raziatul laili wahyunita, laili Maryana Mochamad Ari Saptari Muhammad Rizki Mulya Ulfa, Septia Munauwarah, Munauwarah Munirul Ula Muslimah Siregar, Khanifa Mutammimul Ula Muthmainnah Muthmainnah Nisa Ul Fadila Nurdin Nurdin Nurdin Nurdin Qasos, Lailil Rahma Fitria, Rahma Ramadan, Rifki Rasmiati Rasyid Rini Meiyanti Rizal S.Si., M.IT, Rizal Safwandi Safwandi Sahputra, Ilham Sinambela, Ilmi Suciani Sujacka Retno Syibral Malasyi Syukriah Syukriah, Syukriah Ulfa, Nur Saufani Veri Ilhadi Yurni, Irma Zubaedah, Reza Zuraida