Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Science Information System and Technology
Sarmidi Sarmidi
Universitas Muhammadiyah Tasikmalaya
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Sistem Pakar Diagnosa Penyakit Pada Ayam Pedaging Berbasis Web Menggunakan Metode Certainty Factor Evi Dewi Sri Mulyani; Teuku Mufizar; Yusuf Sumaryana; Sarmidi Sarmidi; Robby Awaludin
E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Vol 12 No 1 (2023): e-Jurnal JUSITI
Publisher : Universitas Dipa Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pada industri ayam pedaging, deteksi dan diagnosa penyakit pada ayam merupakan faktor kritis dalam menjaga kesehatan dan produktivitas ternak.Keterbatasannya pengetahuan para peternak mengenai macam-macam gejala dan penyakit pada ayam pedaging serta minimnya seorang pakar/ahli mengenai penyakit pada ayam pedaging.Penelitian ini menjelaskan proses pengembangan sistem pakar dengan menggunakan ESDLC (Expert System Development Life Cycle), yang meliputi perancangan basis pengetahuan yang mencakup gejala-gejala penyakit, aturan-aturan diagnosa, serta basis pengetahuan tentang faktor kepastian. Metode Certainty Factor digunakan untuk menghitung tingkat keyakinan dalam proses diagnosa, dengan mempertimbangkan keterkaitan antara gejala-gejala dan penyakit yang mungkin terjadi. Hasil pengujian sistem ini menunjukkan bahwa metode Certainty Factor dapat memberikan diagnosa yang akurat dalam waktu yang singkat. Sistem ini memberikan bantuan yang berharga bagi peternak ayam pedaging dalam mengidentifikasi penyakit dan mengambil tindakan yang tepat secara cepat serta dapat memberikan dampak yang baik khususnya untuk para peternak yang ada di daerah Cigalontang, terutama dalam hal pengetahuan mengenai macam-macam gejala dan jenis penyakit, peternak bisa lebih mengetahui macam-macam gejala dan jenis penyakit pada ayam yang bersumber dari sistem pakar tersebut, serta mempermudah peternak untuk mendiagnosa penyakit pada ayam.
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.
Co-Authors Ade Bastian Adnan Arshad Evi Dewi Sri Mulyani Muhammad Taufiq Ristina Siti Sundari Robby Awaludin Teuku Mufizar Volodymyr Rusyn Yusuf Sumaryana