PENENTUAN SAPI BERKUALITAS DENGAN METODE SMART (SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE) DI PASAR NGORO BERBASIS WEB

Authors

  • Ahmad Stevent Andreuw Program Studi S1 Teknik Informatika Fakultas Teknologi Informasi Universitas Hasyim Asy’ari Tebuireng Jombag
  • Aries Dwi Indriyanti Program Studi S1 Teknik Informatika Fakultas Teknologi Informasi Universitas Hasyim Asy’ari Tebuireng Jombag

Abstract

Determination of quality cow is a very important aspect in the livestock industry. To help meet this need, we have developed a web-based system that uses the SMART (Simple Multi Attribute Rating Technique) method to help determine quality cow in the Ngoro Market. This system is designed to provide the best cow recommendations based on the preferences of three respondents. The SMART method is used to overcome challenges in making multi-criteria decisions by considering the relevant attributes. In our system, we integrate cow attribute information such as legs, back, ears, tail, hump, lips and rump. This data was collected through interviews with the three respondents, who have experience in the trade in selecting quality cow. The test results show that the application can run smoothly and according to what is required. This system is able to provide the best cow recommendations based on respondents' preferences with Pak Darmin's results of 0.45. Thus assisting buyers in selecting quality cow more efficiently. By using this system, buyers can quickly obtain information on the cows that meet their criteria, and can make smarter and more informed decisions. The use of this system in the Ngoro Market is expected to increase the effectiveness and efficiency of the process of determining quality cow. With a system that provides recommendations based on respondents' preferences, buyers can save time and effort that was previously used to find quality cow manually. This system also benefits farmers, as it helps increase the visibility and sales of their quality cow in the market.
Keywords: SPK, SMART Method, Quality Cow, WEB

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Published

2024-04-02