Pengembangan Aplikasi Sistem Pakar Deteksi Dini Hama dan Penyakit Tanaman Jagung

Mohamad  Lihawa; Zulzain Ilahude; Mukhlisulfatih Latief; Mohamad  Ikbal Bahua; Hayatiningsih  Gubali; Nikmah  Musa; Salmawaty  Tansa

doi:10.25181/jppt.v24i1.3039

Authors

Mohamad Lihawa Jurusan Agroteknologi Fakultas Pertanian Universitas Negeri Gorontalo
Zulzain Ilahude Universitas Negeri Gorontalo
Mukhlisulfatih Latief Jurusan Tekhnik Elektro Fakultas Tekhnik Universitas Negeri Gorontalo
Mohamad Ikbal Bahua Jurusan Agroteknologi Fakultas Pertanian Universitas Negeri Gorontalo
Hayatiningsih Gubali Jurusan Agroteknologi Fakultas Pertanian Universitas Negeri Gorontalo
Nikmah Musa Jurusan Agroteknologi Fakultas Pertanian Universitas Negeri Gorontalo
Salmawaty Tansa Jurusan Agroteknologi Fakultas Pertanian Universitas Negeri Gorontalo

DOI:

https://doi.org/10.25181/jppt.v24i1.3039

Abstract

Pests and diseases of maize plants have the potential to cause crop failure. Lack of information and knowledge about plant pests and diseases and limited field extension workers lead to errors in diagnosing maize pests and diseases. This results in inappropriate crop management that decreases production. Therefore, farmers need a tool to detect pest and disease attacks through physical symptoms seen on plants in the field. This research aims to produce an Agricultural Information System, namely an android-based expert system to detect pests and diseases in corn plants. The method used is software with prototyping to get an overview of the application to be built through a prototype application design and then evaluated by the user. The research stages include; gathering needs, building prototypes, evaluating protoype, coding the system, testing the system, evaluating the system, and using the system. The result is the symptoms of pest and disease attacks on corn plants in the field, can be detected through the form of symptoms that are matched with images and characteristics of symptoms displayed on the Agricultural Information System software installed on android-based mobile phones or Tablets. Test results from 28 respondents showed that the success rate of detection of pest symptoms on corn plants was 75%, and for disease symptoms was 90%.

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