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All Journal Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika
Huda, Khoirul Huda Dwi Putra
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science

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ANALISIS PENYAKIT PADA TUMBUHAN HIDROPONIK SELADA MENGGUNAKAN METODE FORWARD CHAINING Huda, Khoirul Huda Dwi Putra; Arbansyah, Arbansyah; Yulianto, Fendy
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 18 No. 2 (2024): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v18i2.14957

Abstract

This research, titled "Analysis of Diseases in Hydroponic Lettuce Plants Using the Forward Chaining Method," focuses on the process of identifying diseases in hydroponic lettuce plants through an expert system. Hydroponic lettuce plants can be affected by various diseases such as soft root, root rot, yellowing leaves, and others. Therefore, there is a need to facilitate farmers and laypeople in detecting diseases in hydroponic lettuce plants and easily identifying them by simply answering diagnostic questions about the disease symptoms. This research develops the results of the disease analysis in hydroponic lettuce plants using the Forward Chaining method through an expert system. The Forward Chaining method is used due to its high effectiveness and accuracy in identifying diseases through IF-THEN Rule s by finding facts from the established Rule s. The data presented includes disease data and symptom data obtained from hydroponic lettuce cultivation on Jalan Muang RT 47 Lempake. This research involves data collection, data analysis, and BlackBox testing. The development of the website for analyzing diseases in hydroponic lettuce plants using the Forward Chaining method employs PHP, HTML, CSS, and MySQL programming languages. The results of this research are satisfactory because the Forward Chaining method can accurately detect diseases, and the website runs smoothly and also got an accuracy of 79,16% on the calculation system using the website.
Co-Authors Arbansyah, Arbansyah Fendy Yulianto