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All Journal Agents: Journal of Artificial Intelligence and Data Science
Muh.Sahib
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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SISTEM CERDAS PEMELIHARAAN DAN DIAGNOSA PENYAKIT HEWAN TERNAK SAPI BERBASIS ANDROID Syahraeni; Muh.Sahib
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 1 (2022): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (796.366 KB) | DOI: 10.24252/jagti.v2i1.27

Abstract

The livestock industry's development is an integral part of agricultural sector growth and holds significant strategic importance in meeting the rising demand for animal feed due to Indonesia's increasing population. The motivation behind this research stems from the inadequate knowledge among numerous breeders when it comes to livestock maintenance. This knowledge gap leads many breeders to rely solely on their experience due to the unavailability of information or accessible knowledge resources. To address this issue, a qualitative research approach was employed, utilizing an experimental programming method following the waterfall model. Data sources included various books, journals, theses, e-books, websites, and data collection through observations and interviews with employees from the District Livestock and Animal Health Service in Sinjai, as well as the involved breeders. The study's outcome is the development of an Android-based Livestock Maintenance System Application. This application serves as a valuable resource for obtaining information related to livestock maintenance. Additionally, it offers a platform for determining appropriate treatments and diagnosing diseases during livestock care. Furthermore, this system streamlines information dissemination from the Department of Animal Husbandry and Animal Health, eliminating the need for constant field visits to stay updated on livestock rearing developments.
Co-Authors Syahraeni