Decision Support System for Selecting Market-Ready Buffalo Using the SAW Method: A Case Study of Livestock Farms in Tulang Bawang Regency

Sistem Pendukung Keputusan Pemilihan Kerbau Siap Jual Menggunakan Metode SAW: Studi Kasus Peternakan Di Kabupaten Tulang Bawang

  • Ryan Dermawan Program Studi Sistem Informasi, Fakultas Teknik Dan Ilmu Komputer, Universitas Teknokrat Indonesia, Bandar Lampung, Indonesia
  • Reflan Nuari Program Studi Sistem Informasi, Fakultas Teknik Dan Ilmu Komputer, Universitas Teknokrat Indonesia, Bandar Lampung, Indonesia
Keywords: Decision Support System, Simple Additive Weighting, Buffalo Selection, Multi-Criteria, Animal Husbandry

Abstract

Tulang Bawang Regency has significant potential for buffalo farming, but the process of determining marketable buffalo is still carried out conventionally based on the farmers' experience. This approach has the potential to lead to less objective decisions because it does not consider all criteria in a structured manner. This study aims to develop a decision support system using the Simple Additive Weighting (SAW) method to assist in the more systematic selection of marketable buffalo. The criteria used include weight, age, health condition, height, and price, weighted based on their level of importance. The research data consisted of ten alternative buffaloes obtained from farms in Tulang Bawang Regency. Process analysis was carried out through decision matrix normalization and preference value calculations to produce a final ranking. The results show that the SAW method is able to provide the best alternative recommendations based on the highest preference values, thus helping farmers make more objective, measurable, and transparent decisions compared to conventional methods

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Published
2026-04-24
How to Cite
Dermawan, R., & Nuari, R. (2026). Decision Support System for Selecting Market-Ready Buffalo Using the SAW Method: A Case Study of Livestock Farms in Tulang Bawang Regency. Jurnal Media Computer Science, 5(2), 917-930. https://doi.org/10.37676/jmcs.v5i2.11157
Section
Articles