| Issue |
E3S Web Conf.
Volume 328, 2021
International Conference on Science and Technology (ICST 2021)
|
|
|---|---|---|
| Article Number | 03003 | |
| Number of page(s) | 8 | |
| Section | Informatics | |
| DOI | https://doi.org/10.1051/e3sconf/202132803003 | |
| Published online | 06 December 2021 | |
Aplication of Hybrid Method for Superior cattle selection using Decision Support System
1 Department of Informatics, Universitas Musamus, Merauke 99600, Indonesia.
2 Department of Animal Husbandry, Universitas Musamus, Merauke 99600, Indonesia
* Corresponding author : lilik@unmus.ac.id
Merauke is one of seventeen districts selected for strengthening beef cattle breeding activities to provide livestock germs, especially for local livestock, through domestic procurement. The sustainability of domestic beef production supplies must be supported by the availability of quality beef breeds. Superior beef cattle are one of the determining factors and have a strategic value in the effort to develop beef cattle. Criteria for evaluating the quality of cattle breeds, including body size or morphology, health and defects in livestock, are in accordance with Indonesian national standards for good beef cattle breeding guidelines. Selection of cattle breeds is done by the traditional breeders community only by visually paying attention to the size of cattle. This study aims to develop decision support tools for farmers in selecting prospective high-quality beef cattle, to analyze the criteria data for cattle using a combination of two methods; AHP and SMART, that alternative solutions can be obtained that will be recommended to farmers. The local beef cattle of Merauke that are used as research samples are PO cattle, system provides information on bull superior which farmers can use as supporting information in making decisions.
Key words: Decision Support System / Hybrid / AHP / SMART
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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