Web Based Cattle Disease Expert System Diagnosis with forward Chaining Method

Zamsuri, Ahmad; Syafitri, Wenni; Sadar, Muhamad

doi:10.1088/1755-1315/97/1/012046

Cited by 7 publications

(3 citation statements)

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“…Jenis penyakit pada ternak domba antara lain brucellosis, mastitis, orf, pink eye, scabies (gatal), bloat (kembung), diare, tetanus, myiasis (belatungan), foot rot (busuk kaki) dan lainnya (Azmi & Ismail, 2020). Minimnya pengetahuan peternak mengenai informasi tentang domba baik pakan, perawatan, maupun penyakit (Andika et al, 2022).…”

Section: Inti Nusa Mandiriunclassified

Sistem Pakar Diagnosa Penyakit Pada Domba Dengan Menggunakan Metode Fuzzy Mamdani

Kardila,

Muttaqin,

Resmi

2023

j. inti nm

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Abstract—The decreasing sheep population has raised serious concerns regarding its impact on both the livestock industry and export opportunities. One of the main factors contributing to this decline is the prevalence of diseases among sheep. These illnesses present a significant problem as they can lead to reduced meat production, animal fatalities, and economic losses. The limited knowledge among farmers regarding these diseases and sheep care makes it challenging to diagnose and treat the conditions effectively. To address this issue and aid farmers in easily diagnosing diseases, a web-based expert system utilizing the fuzzy Mamdani method was developed. The selection of the fuzzy Mamdani method was based on its ability to handle uncertainty in disease diagnosis, providing reasonably accurate results by evaluating symptoms, determining disease severity, and recommending appropriate treatments. Through the fuzzy Mamdani method and the web-based platform, this system offers convenient access for farmers to diagnose diseases in their sheep online. According to the analysis results, reproductive health disorders are the primary cause of the decline in the sheep population. Consequently, the expert system for diagnosing sheep diseases serves as an alternative for early prevention and suitable treatment. System testing indicates an accuracy rate of 80%, signifying the system's capability to provide reasonably accurate diagnoses. The main goal of this research is to support the livestock and fisheries department in Purwakarta in diagnosing sheep diseases, preventing epidemic outbreaks, and implementing proper measures to mitigate the negative impacts on the livestock industry while promoting sustainable growth of the sheep population

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Section: Inti Nusa Mandiriunclassified

Sistem Pakar Diagnosa Penyakit Pada Domba Dengan Menggunakan Metode Fuzzy Mamdani

Kardila,

Muttaqin,

Resmi

2023

j. inti nm

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“…Intelligent systems are built with the rules of artificial intelligence, including expert systems. Expert systems are smart computer programs that use an expert's knowledge and inference procedures to solve a complex problem and produce solutions for them [3] [4]. Expert systems have two components: the knowledge base and intelligent machines [5].…”

Section: Introductionmentioning

confidence: 99%

A Proposed Model Expert System for Disease Diagnosis in Children to Make Decisions in First Aid

Henderi¹,

Khudhorie²,

Maulani³

et al. 2022

intensif

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Children have a weaker immune system than adults. They are susceptible to disease. Therefore, this study proposes an expert system model of disease diagnosis in children. We develop expert strategies to meet the needs of alternative diagnostic tools in making decisions and first aid for children suffering from illness. The development of an expert system model for diagnosing children's diseases using forwarding chaining based on If-Then as an inference engine. We chose the forward chaining method because it has a framework for thinking like a doctor's when diagnosing and concluding the disease. We made testing to model by doctors with 35 patients. The test results show that the expert systems model of disease diagnosis in children in this research has to be used as an alternative or comparison diagnostic tool with an accuracy rate of 79%.

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“…[8] developed a web-based expert system to diagnose infectious and non-infectious cattle diseases using rule-based reasoning. [9] developed an android application expert system to simplify disease detection and show brief information about cattle's using a rule-based forward reasoning engine. [10] developed a mobile-based diagnosis of skin diseases using case-based reasoning with image processing to detect diseases.…”

Section: Introductionmentioning

confidence: 99%

Application of Artificial Intelligence Algorithm in Image Processing for Cattle Disease Diagnosis

Lake¹,

Getahun²,

Teshome³

2022

JILSA

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Livestock is a critical socioeconomic asset in developing countries such as Ethiopia, where the economy is significantly based on agriculture and animal husbandry. However, there is an enormous loss of livestock population, which undermines efforts to achieve food security and poverty reduction in the country. The primary reason for this challenge is the lack of a reliable and prompt diagnosis system that identifies livestock diseases in a timely manner. To address some of these issues, the integration of an expert system with deep learning image processing was proposed in this study. Due to the economic significance of cattle in Ethiopia, this study was only focused on cattle disease diagnosis. The cattle disease symptoms that were visible to the naked eye were collected by a cell phone camera. Symptoms that were identified by palpation were collected by text dialogue. The identification of the symptoms category was performed by the image analysis component using a convolutional neural network (CNN) algorithm. The algorithm classified the input symptoms with 95% accuracy. The final diagnosis conclusion was drawn by the reasoner component of the expert system by integrating image classification results, location, and text information obtained from the users. We developed a prototype system that incorporates the image classification algorithms and the reasoner component. The evaluation result of the developed system showed that the new diagnosis system could provide a rapid and effective diagnosis of cattle diseases.

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Web Based Cattle Disease Expert System Diagnosis with forward Chaining Method

Cited by 7 publications

References 0 publications

Sistem Pakar Diagnosa Penyakit Pada Domba Dengan Menggunakan Metode Fuzzy Mamdani

Sistem Pakar Diagnosa Penyakit Pada Domba Dengan Menggunakan Metode Fuzzy Mamdani

A Proposed Model Expert System for Disease Diagnosis in Children to Make Decisions in First Aid

Application of Artificial Intelligence Algorithm in Image Processing for Cattle Disease Diagnosis

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