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All Journal JOIV : International Journal on Informatics Visualization
Siti Hawa Anurddin
Lee Veterinary Clinic, Selangor, Malaysia
Computer Science & IT

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A Rule-based Mobile Application for Diagnosing Pet Disease: Design and Implementation Ling Li Ng; Hanayanti Hafit; Ruhaya Ab. Aziz; Nur Liesa Mohammad Azemi; Siti Hawa Anurddin
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1325

Abstract

Animals kept in homes for personal enjoyment rather than for work or sustenance are typically referred to as "pets." A pet's daily schedule can include exercising its muscles and going outside to relieve stress. Pets may occasionally be drink from community water dishes that could be contaminated with other animals' bacteria, viruses, or parasites. The pets may unknowingly get infections due to this opening up their bodies to bacteria or viruses. Pet's behavior and condition need to be periodically checked. An animal's behavior is directly impacted by its health and vice versa. A pet disease diagnosis application is crucial for pet owners to receive consistent and suitable pet health care. It will help pet owners identify potential illnesses before their animals develop chronic ones. Thus, the construction of a mobile application for diagnosing pet diseases is presented in this paper. This application offers pet owners information on their animals' health and safety. Pet owners can contact veterinarians for rare cases or crises in this application's chat room. The rule-based inference is used to determine the possible diseases based on the pet's symptoms. System prototyping methodology is applied to develop this Android mobile application using Visual Studio Code and Firebase database. User acceptance testing is performed on the users to test how much further their satisfaction with the proposed pet disease diagnosis application is before the application is shifted to the production process.  
Co-Authors Hanayanti Hafit Ling Li Ng Nur Liesa Mohammad Azemi Ruhaya Ab. Aziz