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All Journal Bit (Fakultas Teknologi Informasi Universitas Budi Luhur)
Prayoga, Rio Agung
Universitas Muhammadiyah Sukabumi
Computer Science & IT Electrical & Electronics Engineering

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Channa Fish Disease Consultation Using The Certainty Factor Algorithm Web Based Prayoga, Rio Agung; Apriandari, Winda; Pambudi, Agung
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 21, No 1 (2024): APRIL 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v21i1.2722

Abstract

The health of Channa fish is a fundamental foundation for successful cultivation. Accurate diagnosis of diseases remains a serious challenge for cultivators. Lack of understanding about diseases, difficulty accessing reliable knowledge sources, and limited information on Channa fish health issues are concerning factors. This research aims to diagnose Channa fish diseases based on observed symptoms and identifiable behaviors and conditions in the fish. Challenges include cultivators' lack of knowledge about Channa fish diseases, difficulty obtaining assistance from aquatic veterinarians, and limited information on Channa fish diseases from previous research. The objective of this study is to support Channa fish cultivators, especially in disease control, to achieve successful reproduction and reduce reproductive losses. The research utilizes knowledge obtained from experts experienced in Channa fish disease control, implementing it into a web-based expert system to address these issues. The Certainty Factor method is employed to measure the confidence level of Channa fish disease diagnoses in this research. The results show that the expert system is capable of diagnosing Gyrodactylus sp disease in Channa fish with an accuracy of 89.25%, equivalent to the manually calculated percentage. The novelty of this research lies in its focus on developing a Channa fish disease diagnosis system using the Certainty Factor algorithm. The system integrates inference engines and the Certainty Factor algorithm, presenting results through a website interface. Thus, this system successfully combines the Certainty Factor for Channa fish disease diagnosis and can be used as a guide for fisheries practitioners.
Co-Authors Pambudi, Agung Winda Apriandari