Abstract

The carp (Osphronemus Goramy) including fish that was seeded in cultivation. In addition to the price of carp that are relatively more expensive than other fish and it has been easy to carp also has a higher value compared to other freshwater fish. But in the cultivation of carp diseases is one of the serious problems encountered by the fish farmers because it could potentially cause harm. Diseases that attack the carp both are still in the larval or adult forms of which are caused by parasitic infections in the form of fungi, protozoa, worms as well as bacterial infection of Aeromonas hydrophylla, Flexybacter colomnaris, and Mycobacterium sp. The multiplicity of types of disease that can attack the carp and the difficult process of detection because of the similarity of the symptoms caused fish farmers making it difficult to determine the methods of prevention and control of the right to address the disease. Detection of disease of carp is seen on the surface of the body of the fish. Therefore, it takes expert system to detect disease carp by involving technology. One of the methods used in the expert system of fuzzy inference system Mamdani. Fuzzy inference system Mamdani reasoning used in this study because of the handling of the value and accuisition of knowledge representation experts can directly representation in the form of rules, which can be understood when placed on the machine inference. The result of this reasoning is to detect diseases of the carp while delivering the right solution to tackle the disease of carp.

Highlights

  • Produksi perikanan budidaya di Indonesia tahun 2014 mencapai 14,3 juta ton atau mengalami kenaikan sebesar 7,96% dibandingkan tahun 2013 yakni sebesar 13,3 juta ton (Kementrian Kelautan dan Perikanan, 2015)

  • including fish that was seeded in cultivation

  • also has a higher value compared to other freshwater fish

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Summary

PENDAHULUAN

Produksi perikanan budidaya di Indonesia tahun 2014 mencapai 14,3 juta ton atau mengalami kenaikan sebesar 7,96% dibandingkan tahun 2013 yakni sebesar 13,3 juta ton (Kementrian Kelautan dan Perikanan, 2015). Banyaknya jenis penyakit yang dapat menyerang ikan gurame serta sulitnya proses deteksi karena adanya kemiripan gejala yang ditimbulkan membuat para petani ikan sulit menentukan metode pencegahan dan pengendalian yang tepat untuk mengatasi penyakit tersebut. Penalaran fuzzy digunakan pada penelitian ini karena penanganan nilai dan representasi pengetahuan yang diakuisasi dari pakar dapat langsung direpresentasi dalam bentuk aturan atau rule, yang bisa dipahami ketika dimasukan pada mesin inferensi. Berdasarkan konsep Fuzzy Mamdani dan adanya masalah dalam menentukan penyakit yang diderita oleh ikan gurame maka dibutuhkan website untuk mendiagnosa penyakit ikan gurame dengan menerapkan metode Fuzzy Mamdani.

METODELOGI PENELITIAN
Rancangan flowchart apikasi
HASIL DAN PEMBAHASAN
Aplikasi fungsi implikasi
KESIMPULAN
Full Text
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