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All Journal JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Sela Agnes Aprilia
Prodi Sistem Informasi, FTIKOM, Institut Bakti Nusantara, Lampung
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Desain Prototype Sistem Pakar Mendeteksi Penyakit Tanaman Kakao Berbasis Web Mobile Didi Susianto; Sela Agnes Aprilia; Muhamad Muslihudin; Siti Mukodimah
JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi) Vol 6, No 3 (2023): JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Publisher : Institut Bakti Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jtksi.v6i3.1601

Abstract

Cocoa (Theobroma cacao) is a plant with high economic value. Cocoa beans can be processed into various high-value products, such as chocolate. In addition to its high market value, cocoa also has health benefits due to its antioxidant content, which enhances the immune system. However, cocoa plants often face challenges from pest infestations and diseases. In the village of Rantau Tijang, where cocoa is the main source of income, farmers struggle to obtain guidance and information on the development of diseases such as vascular streak dieback, Phytophthora palmivora (Cocoa Pod Rot), Phytophthora palmivora (Stem Canker), and Marasmius sp (Thread Blight). The limited availability of agricultural experts has a negative impact on the farmers. Therefore, the proposed solution is for researchers to design an expert system for diagnosing cocoa plant diseases using the certainty factor method specifically for cocoa farmers in the Rantau Tijang village. The system developed is capable of diagnosing cocoa plant diseases and providing appropriate solutions to the common issues faced by cocoa farmers. The end result is an information system for diagnosing cocoa plant diseases using the certainty factor method, which can identify the type of disease based on the farmers' complaints. The application was tested for accuracy, yielding a diagnostic accuracy rate of 85.7% for cocoa plant diseases. The web-based mobile expert system for detecting and providing solutions for cocoa plant diseases is expected to assist users, especially farmers, in easily and efficiently conducting their own diagnoses. With the adoption of the web-based expert system, users can access it more easily through the internet.
Co-Authors Didi Susianto Muhamad Muslihudin Siti Mukodimah