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All Journal JURNAL ILMU DAN TEKNOLOGI PETERNAKAN AGRIEKONOMIKA JITRO (Jurnal Ilmiah dan Teknologi Peternakan Tropis) E-Dimas: Jurnal Pengabdian kepada Masyarakat Mimbar Agribisnis: Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis JPM (Jurnal Pemberdayaan Masyarakat) Jurnal Pengabdian Pada Masyarakat Jurnal Pertanian Agros Comment: an International Journal of Community Development Logista: Jurnal Ilmiah Pengabdian Kepada Masyarakat Jurnal MEBIS (Manajemen dan Bisnis) Jurnal Sosiologi Pertanian dan Agribisnis Jurnal Keuangan dan Akuntansi Terapan (KUAT) Science Information System and Technology J-DEPACE (Journal of Dedication to Papua Community) Jurnal Pengabdian Masyarakat
Ristina Siti Sundari
Universitas Perjuangan Tasikmalaya
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Veterinary Other

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Journal : Science Information System and Technology

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Advancing Animal Health: A Web-Based Expert System Utilizing Forward Chaining for Disease Diagnosis Sarmidi Sarmidi; Ade Bastian; Muhammad Taufiq; Volodymyr Rusyn; Adnan Arshad; Ristina Siti Sundari
West Science Information System and Technology Vol. 2 No. 02 (2024): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v2i02.1207

Abstract

The increasing prevalence of animal diseases, along with the increasing need for animal products, highlights the urgent need for efficient diagnostic tools in veterinary medicine. The aim of this research is to create an expert system that uses a forward chaining algorithm to diagnose animal diseases. The forward chaining algorithm is a deductive reasoning approach that starts with existing facts and uses expert tree rules for hypotheses. This process continues until the desired goal is achieved or no additional conclusions can be drawn. Even though there are developments in expert systems, there are still shortcomings in implementing the forward chain for rapid and precise diagnosis of livestock diseases. This work aims to fill this gap by developing an expert system that improves the accuracy and efficiency of disease diagnosis in the livestock industry. A database of animal diseases and symptoms was created by observing and interacting directly with farmers. The system architecture is specifically intended to optimize data processing and user engagement, enabling rapid diagnosis and treatment recommendations. This test shows a level of accuracy and precision, thereby reducing the possibility of misdiagnosis. The capacity of expert systems to provide fast and reliable diagnoses has the potential to improve livestock health management, thereby helping farmers maintain animal welfare and productivity. The results of this work advance the field of veterinary diagnostics and propose other uses of expert systems in animal health management.
Advancing Animal Health: A Web-Based Expert System Utilizing Forward Chaining for Disease Diagnosis Sarmidi, Sarmidi; Bastian, Ade; Taufiq, Muhammad; Rusyn, Volodymyr; Arshad, Adnan; Siti Sundari, Ristina
West Science Information System and Technology Vol. 2 No. 02 (2024): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v2i02.1207

Abstract

The increasing prevalence of animal diseases, along with the increasing need for animal products, highlights the urgent need for efficient diagnostic tools in veterinary medicine. The aim of this research is to create an expert system that uses a forward chaining algorithm to diagnose animal diseases. The forward chaining algorithm is a deductive reasoning approach that starts with existing facts and uses expert tree rules for hypotheses. This process continues until the desired goal is achieved or no additional conclusions can be drawn. Even though there are developments in expert systems, there are still shortcomings in implementing the forward chain for rapid and precise diagnosis of livestock diseases. This work aims to fill this gap by developing an expert system that improves the accuracy and efficiency of disease diagnosis in the livestock industry. A database of animal diseases and symptoms was created by observing and interacting directly with farmers. The system architecture is specifically intended to optimize data processing and user engagement, enabling rapid diagnosis and treatment recommendations. This test shows a level of accuracy and precision, thereby reducing the possibility of misdiagnosis. The capacity of expert systems to provide fast and reliable diagnoses has the potential to improve livestock health management, thereby helping farmers maintain animal welfare and productivity. The results of this work advance the field of veterinary diagnostics and propose other uses of expert systems in animal health management.
Co-Authors Ade Bastian Adnan Arshad Adnan Arshad Adnan Arshad Adnan Arshad Andri Kusmayadi Arshad, Adnan Budhi Wahyu Fitriadi D Yadi Heryadi Dedi Dedi Dona Setia Umbara Dona Setya Umbara Euis Kurniasih Hani Naziah Irsyad Padjari Kamiel Roesman Bachtiar Muhammad Taufiq Muhammad Taufiq Reny Hidayati Reny Hidayati Rusyn, Volodymyr Sarmidi Sarmidi Sarmidi Sarmidi Setia Umbara, Dona Siti Nurhidayah Soni Ariana Volodymyr Rusyn Wiyanto, Andi Yudhi Arie Priyanto Yusuf Sumaryana